Prevalence of treatment outcomes and associated factors of diabetic ketoacidosis among adult diabetic patients admitted to Debre Markos comprehensive specialized hospital, Northwest Ethiopia: A cross-sectional study

Prevalence of treatment outcomes and associated factors of diabetic ketoacidosis among adult diabetic patients admitted to Debre Markos comprehensive specialized hospital, Northwest Ethiopia: A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence of treatment outcomes and associated factors of diabetic ketoacidosis among adult diabetic patients admitted to Debre Markos comprehensive specialized hospital, Northwest Ethiopia: A cross-sectional study Fenta Limenih, Feriehiwot Molla, Muluken Teshome, Melesse Belayneh Yayeh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7114400/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Dec, 2025 Read the published version in European Journal of Medical Research → Version 1 posted 9 You are reading this latest preprint version Abstract Background Diabetic ketoacidosis emergencies are serious acute complications of diabetes mellitus, and their health and economic impacts have been increasing among adult diabetic patients. Despite the growing burden of emergencies from diabetic ketoacidosis among adults with diabetes, its outcome and predictors of treatment have not been well studied in Ethiopia. Objective To assess the prevalence of poor treatment outcome of diabetic ketoacidosis and associated factors among adult diabetic patients admitted to the Debre Markos comprehensive specialized hospital, northwest Ethiopia. Methods A hospital-based cross-sectional study was conducted at Debre Markos comprehensive specialized hospital from April 8, 2025 to April 28, 2025. A total of 360 patients with diabetic DKA who were admitted from August 28, 2019 to September 30, 2024 participated in the study. A simple random sampling technique was used to select study participants. Data were extracted using a pre-tested data collection tool adapted from different literatures. The data were entered into epi-data version 4.6.0 and exported to SPSS version 26 for analysis. Both bivariable and multivariable binary logistic regression analysis were done. Statistical significance was declared at a p-value < 0.05 with an odds ratio of 95% confidence interval. Results The prevalence of poor treatment outcomes was 15.5% (95%, CI: 11.5%, 19.3%). Factors, such as severe DKA (AOR: 1.482, 95% CI: 1.324, 4.872), the presence of comorbidities (AOR: 1.752, 95% CI: 1.215, 3.865), and underlying infections (95% CI: 1.362, 4.125), discontinuation of drugs (AOR: 2.115, 95% CI: 1.245, 3.865), treatment complications (AOR: 1.356, 95% CI: 1.253, 4.125), ketone levels > 3 (AOR: 1.213, 95% CI: 1.052, 2.876), and hospital stays of less than five days (AOR: 1.29, 95% CI: 1.022, 3.254) were also significant predictors of poor outcomes in patients with DKA. Conclusions This study found that a high number of patients with DKA in the Debre Markos comprehensive specialized hospital experienced poor treatment outcomes. Significant factors included severe DKA, comorbidities, infections, drug discontinuation, treatment complications, high ketone levels and short hospital stays. To improve treatment outcomes, early identification and proactive management of high-risk DKA patients, particularly those who present with severe illness, comorbidity conditions, or infections, shall be prioritized. Diabetic keto-acidosis poor treatment outcome associated factors hospital Ethiopia Figures Figure 1 Text box 1. Contributions to the literature · Highlights there is limited evidence on treatment outcomes of diabetic ketoacidosis (DKA) among diabetic patients, particularly in Ethiopia. · Identifies preventable factors, such as infections, poor adherence to treatment guidelines, and inadequate ketone management as key contributors to poor outcomes, including mortality. · Emphasizes the urgent need for improved hospital-based DKA management and targeted public health strategies to address these challenges in the affected population. 1. Introduction Diabetes mellitus is a group of metabolic disorders characterized by the presence of hyperglycaemia due to impaired insulin secretion, action, or both, which results in alteration of carbohydrate, protein, and fat metabolism [ 1 ]. Diabetes mellitus is most commonly associated with older age, obesity, family history of diabetes mellitus, genetic susceptibility, hypertension, dyslipidaemia, autoimmunity, and physical inactivity [ 2 ]. Diabetes is one of the largest global public health emergencies of the 21st century. According to the report of the International Diabetes Federation, 536.6 million adults (10.5%) lived with diabetes mellitus worldwide in 2021, and this number is expected to increase to 783.2 million (12.2%) by 2045 [ 3 ]. According to the IDF 2021 estimate, 24 million adults aged 20–79 years lived with diabetes in Africa [ 4 ]. Diabetic ketoacidosis is an emergency that encompasses the spectrum of preventable acute diabetic complications, which can occur in patients with type 1 and type 2 diabetes mellitus. DKA in the setting of relative or absolute insulin deficiency, excessive counter regulatory hormone levels, progressive volume depletion, and loss of electrolytes [ 5 ]. According to the World Health Organization treatment guideline, diabetic ketoacidosis is a common and potentially fatal acute complication of diabetes mellitus during diagnosis and follow-up [ 6 ]. The poor outcome of the DKA treatment can lead to a debilitating and potentially fatal complication, including cerebral oedema and severe hypoglycaemia. Mortality of DKA has been reported to be less than 5% in centres of treatment experienced in the Americas, Europe, and Asia [ 7 ] and in Riyadh, Saudi Arabia, King Abdul-Aziz Medical City (2%) [ 8 ]. However, in developing countries, high poor treatment outcomes are observed. For instance, in Malaysia 24%. Of which 17.6% of DKA patients died (Usman et al., 2015), Kenya, Tanzania and Ghana between 26% and 29% [ 10 ], in Liberia 19.2% [ 11 ], Zambia 21% [ 12 ], Kenya’s Kenyatta National Hospital 29.8% [ 13 ]. Similar studies in Ethiopian countries showed a high prevalence of poor treatment outcomes. Nekemte referral hospital 11.4% [ 14 ], Shashemene referral hospital, 26.2% [ 15 ], Addis Addis Ababa, at St. Luke Catholic Hospital, 13% [ 16 ], Adama General Hospital 15.1% [ 17 ], Jima University Hospital 9.8% [ 18 ],Hiwot Fana Specialized University Hospital 17.8% [ 19 ] and Debre Tabor General Hospital, 20% [ 20 ]. This magnitude imposes a high national and individual economic burden associated with medication, bed occupancy, long hospital stays, and mortality. The average treatment and laboratory cost is significantly higher among Diabetic ketoacidosis emergencies compared to other emergency cases [ 21 ]. Common causes of CKD are missed insulin dose, illness or infection, and undiagnosed or untreated diabetes. The main clinical features of DKA are hyperglycaemia, dehydration, loss of electrolytes, and acidosis [ 7 ]. Different researches indicated that; socio-demographic characteristics, behavioural factors, treatment-related factors, use of alternative medications, and clinical factors were risk factors for diabetic ketoacidosis among patients with DM [ 15 , 20 ] In the study area, limited studies have been conducted on the outcome of the treatment of diabetic ketoacidosis and the associated factor. Therefore, this study aims to assess the prevalence of poor treatment outcome of diabetic ketoacidosis and associated factors among adult diabetic patients admitted to the Debre Markos comprehensive specialized hospital, northwest Ethiopia. This study provides valuable information for health policy, health system managers, healthcare providers, and patients to reduce the occurrence of diabetic ketoacidosis and associated factors. 2. Methods 2.1 Study area and period Debre Markos Comprehensive Specialized Hospital is one of the governmental hospitals which is located in the Amhara region, East Gojame Zone, in Debre Markos town, which is 300 km from Addis Ababa, the capital city of Ethiopia, and 255 km from Bahirdar (the capital city of the Amhara Regional state) in North West Ethiopia. It provides preventive, diagnostic, curative and rehabilitative service for millions of people in the region with 9 wards, 29 different outpatient units and 143 beds. Currently there are more than 2301 diabetic patients who receive regular follow-up care at the hospital. From August 28, 2019 to September 30, 2024, the number of patients with DM2 1060 and DM1 980 and 480 patients were patients with DKA. Outpatient, emergency and surgical care service is provided to diabetes patients. The study was carried out at the Debre Markos specialized hospital in North West Ethiopia from April 8, 2025 to April 28, 2025. 2.2 Study design A hospital-based cross-sectional study was conducted. 2.3 Population 2.3.1 Source population All admitted adults (age ≥18 years old) DM patients who had developed ketoacidosis at Debre Markos Comprehensive specialized Hhospital. 2.3.2 Study population All adults (age ≥ 18 years old) diagnosed with DM1 and DM2 and who have diabetic ketoacidosis admitted from August 28, 2019 to September 30, 2024 in Debre Markos Comprehensive specialized hospital. 2.4 Inclusion and Exclusion criteria All adults < 18 years of age who were diagnosed with type 1 or type 2 diabetes mellitus and admitted with diabetic ketoacidosis between August 28, 2019, and September 30, 2024, at Debre Markos Comprehensive Specialized Hospital were included in the study. Individuals with incomplete records of key variables and pregnant women were excluded from the study. 2.5 Sample size determination and sampling procedure 2.5.1 Sample size determination The sample size was calculated using a single population proportion formula for both the outcome of diabetic ketoacidosis treatment and associated factors with a study conducted in Addis Ababa DKA treatment. The improved prevalence was 71.1% ([ 22 ] of the patients discharged. Assumption of a 95% CI, 5% marginal error (W) and P = 0.711 The sample size with the formula is:- n= \(\:\frac{\text{Z}{\left(\frac{{\alpha\:}}{2}\right)}^{2}*PQ}{{\text{W}}^{2}}\) = \(\:\frac{\text{Z}{\left(\frac{{\alpha\:}}{2}\right)}^{2}*P(1-P)}{{\text{W}}^{2}}\) = \(\:\frac{{\left(1.96\right)}^{2}*\:0.711*0.299}{{\left(0.05\right)}^{2}}\) = 327, adding 10% for non-response (incomplete chart), the final sample size for objective one was 360. For the second objective sample size determined using factors associated with treatment outcomes of DKA patients. Taking into consideration the assumption: Power 80%, one-to-one ratio between exposed and unexposed groups, AOR (lower AOR to get larger sample size), % of outcome in exposed and unexposed group were taken. It is computed using EPI-info version 7.2.6 STATCALC dialogue box using cross sectional tool bar auto calculate the sample size by entering in Table 1 data elements and the final sample size included 10% nonresponse rate. Table 1 Sample size determination using factors that affect the treatment outcomes of diabetic ketoacidosis among admitted adult diabetes patients at Debre Markos Hospital, Amhara Region, Ethiopia Variables Category % outcome Ratio CI Power % AOR Sample size Reference Infection No** 86.93% 1 95% 80 4.59 304 [ 20 ] Yes * 13.17% Smoker No** 70.7% 1 95% 80 18.1 77 [ 20 ] Yes* 29.3% Potassium replacement Yes ** 18.7% 1 95% 80 3.08 315 [ 23 ] No* 81.3 Comorbidity No** 33.3% 1 95% 80 3.24 119 [ 23 ] Yes 66.7% * Proportion of treatment outcomes for DKA patients among the exposed group ** Proportion of treatment outcomes of DKA patients among the unexposed group Therefore, the larger sample size of the first objective, 360 DKA patients, is the final sample size for this study. 2.5.2 Sampling techniques In this study, simple random sampling techniques were used to select the study samples. From the emergency and in patient registration logbook DKA patients was taken and then based on the card number was selected within a computer-generated random selection. Simple random techniques were used to select the required sample size of 360 from the study period. If a patient experienced two or more episodes of DKA, only the most recent episode was considered to assess treatment outcomes and associated factors. 2. 6 Study variables The dependent variable was the result of the treatment of diabetic ketoacidosis (poor vs. good), while the independent variables included sociodemographic characteristics (age, sex, marital status, residence, occupation and family history of diabetes mellitus); health-related factors (severity of DKA, clinical characteristics (respiratory rate, pulse rate, blood pressure, temperature, blood glucose level, urine glucose level and urine ketone level), recent acute illness, infection, duration of diabetes mellitus, type of diabetes mellitus, presence of comorbidities, and chronic diabetic complications); and treatment-related variables (type of medication used, drug discontinuation, treatment complications, glycemic control, frequency of blood glucose monitoring, and doses of diabetes medications). 2.7 Operational definitions Outcomes of DKA treatment: this study is operationalized as a good and poor treatment of the outcome as follows:- Good outcome of treatment patients who had improved at the end of treatment at discharge [ 15 ]. Poor outcome of treatment patients who were left without medical advice or referred or died in the hospital [ 15 ]. Mild DKA is defined as (arterial pH, 7.25 to 7.30 and serum bicarbonate, 15 to 18 mEq / L) [ 20 ]. Moderate DKA is defined as (arterial pH, 7.00 to < 7.25 and serum bicarbonate, and 10 to < 15 mEq/L) [ 20 ]. Long hospital stay was defined as hospital stay for more than 5 days [ 20 ]. The short hospital stay was defined as the patient stayed in the hospital for less than or equal to 5 days [ 20 ]. Hyperglycaemic emergencies - including diabetic ketoacidosis (DKA), hyperosmolar hyperglycaemic state (HHS) and defined as random plasma glucose > 200 mg/dL and DKA diagnosed when blood glucose is > 250 mg/dl, arterial pH < 7.3, bicarbonate < 15 mEq/L, in the presence of ketonuria [ 2 ]. Severe hypokalaemia is a plasma potassium level of less than 2.5 mmol/L [ 24 ]. 2.8 Data collection tool and procedure Data were collected from the patient chart using a pre-tested data extraction checklist. The data extraction checklist is developed by the principal investigator by reviewing previous literature. The data collection tools, included sociodemographic, disease-related, and treatment-related factor components. A supervisory health officer, three BSC nurses for data collection, and two medical record room workers for chart finding were temporarily recruited for twenty days and participated in the data collection process. Patient charts were retrieved using their medical registration number from the medical record room by record room workers. The data collectors collected the necessary information using the data extraction tool in the designated card room area. A supervisor and the principal investigator followed the data collection process. 2.9 Data quality assurance One day of training was given to data collectors and supervisors on the objective of the study, the content, meaning of the questionnaire/checklists and the way to collect data before the actual data collection is started. The data collection tool was pretested on 5% of the sample size (17 charts) in Fenote selam hospital a week before the actual study. After pre-test is done all modifications were implemented. The data collected were daily evaluated by the supervisors and the principal investigator. The supervisor was to check the completed data collection tool daily for its completeness. In addition to this, the principal investigator was careful to enter and thoroughly clean the data before the beginning of the analysis. 2.10 Data Processing and Analysis Data were checked and entered into the Epi-Data version 4.6 statistical software and exported to the Statistical Package for Social Science (SPSS) statistical software package, version 26 for analysis. Frequencies and proportions were used to summarize the variables. In addition to frequencies and proportions, each variable was presented using tables and figures. The association between the treatment outcomes of patients with DKA and each categorical variable was assessed using the logistic regression model. The outcome variable categorizes two forms: poor outcome and good outcome of treatment. These categories were coded as follows: 1 poor outcome treatment and 0 good outcome treatment. All independent variables with P-value < 0.25 in the bivariate analysis were the candidate adjusting the confounders for the multivariate analysis. The significance of the association was determined at a P-value of < 0.05 in multivariate analysis, while the strength of the association is indicated by the adjusted odds ratio (AOR) with a 95% confidence interval. The model was fitted and checked by the Hosmer-Lemshow fitness model, p value 0.89. 3. Results 3.1 Socio-demographic characteristics A total of 348 DKA patient charts were retrieved from those admitted (360) to DMCSH, yielding a response rate of 96.7%. The mean age of the participants was 36.5 years, with a standard deviation of 12 years. The age distribution revealed that most of the patients were between 35 and 44 years of age, with 27%. Females comprised 61.8% of the participants and the majority of the patients resided in an urban area (67.8%). In terms of marital status, the majority were married (52.6%), followed by singles (32.2%). Occupationally, the majority of the patients were merchants (47.7%), followed by employees (36.8%) and farmers (12.9%). In particular, 75.0% of the patients had unknown family histories of diabetes (Table 2 ). Table 2 Socio-demographic characteristics among DKA patients, DMCSH, north-west Ethiopia, (n = 348) Variable Category Frequency Percent Age in years 18–24 74 21.3 25–34 85 24.4 35–44 94 27.0 45–54 56 16.1 ≥ 55 39 11.2 Sex Female 215 61.8 Male 133 38.2 Residence Urban 236 67.8 Rural 112 32.2 Marital status Single 112 32.2 Married 183 52.6 Widowed 34 9.8 Divorced 19 5.5 Occupational status Merchant 166 47.7 Employee 128 36.8 Farmer 45 12.9 Student 9 2.6 Family history of DM Yes 40 11.5 No 37 13.5 Unknown 261 75.0 3.2 Baseline clinical characteristics among patients with DKA In 3 table, the majority of patients were diagnosed with known Type 1 diabetes (43.1%) or newly diagnosed Type 1 diabetes (35.6%), while 5.5% were newly diagnosed with Type 2 diabetes and 15.8% had known Type 2 diabetes. Regarding the history of diabetes, 58.9% of the patients had a known history of diabetes, while 41.1% were newly diagnosed. Most patients (88.8%) experienced diabetic ketoacidosis (DKA) two times or less, with 11.2% having more frequent occurrences. The mean duration of diabetes was 26.54 years (± 39.2 years). Pulse rates were mostly normal (72.1%), with 27.0% having tachycardia and a small percentage (0.9%) experiencing bradycardia. Mean systolic and diastolic blood pressures were 104.4 ± 15.5 and 67.8 ± 10.5, respectively, and most patients had normal blood pressure (59.8%), although 11.2% had hypotension. Respiratory rates were primarily normal (68.1%), while 31.9% had tachypnea. The average temperature was 36.5°C (± 0.95°C). Dehydration was most commonly not known (86.2%), although 10.1% had mild dehydration, and a small number had moderate (3.4%) or severe dehydration (0.3%). Most of the patients had mild DKA (76.4%), moderate DKA in 18.1% and severe DKA in 5.5% (Table 3 ). Table 3 Baseline clinical characteristics among DKA patients, DMCSH, North West Ethiopia Variable Category Frequency Percent Types of DM diagnosis New DM 1 124 35.6 New DM 2 19 5.5 Known DM 1 150 43.1 Known DM 2 55 15.8 History of DM New 143 41.1 Known 205 58.9 Frequency of DKA ≤ 2 times 309 88.8 > 2 times 39 11.2 Duration of DM Mean (± SD) 26.54 (± 39.2) Pulse rate Bradycardia 3 0.9 Normal 251 72.1 Tachycardia 94 27.0 Systolic Blood pressure Mean (± SD) 104.4 (± 15.5) Diastolic blood pressure Mean (± SD) 67.8 (± 10.5) BP status Hypotension 39 11.2 Normal 208 59.8 Elevated 12 3.4 Stage 1 64 18.4 Stage 2 25 7.2 Respiration rate Normal 237 68.1 Tachypnea 111 31.9 Temperature Mean (± SD) 36.5 (± 0.95) Dehydration status Mild dehydration 35 10.1 Moderate dehydration 12 3.4 Severe dehydration 1 0.3 Not Known 300 86.2 Severity of DKA Mild DKA 266 76.4 Moderate DKA 63 18.1 Sever DKA 19 5.5 3.3 Comorbidity and related factors that precipitate DKA in patients In this dataset, 8.3% of patients had comorbidities, with the majority (91.7%) having none. Hypertension was present in 4.0% of the patients, while the vast majority (96.0%) did not. Toxic multinodular goitre and HIV/AIDS were rare, affecting only 0.6% and 0.9% of patients, respectively, while tuberculosis in all forms was also reported by 0.9%. Asthma was found in just 0.3% of the patients. Regarding pneumonia, most of the cases were mild (3.4%) or severe (1.4%), while the majority (95.1%) did not experience pneumonia. Precipitation factors were observed in 29.3% of patients, infection the most common, reported by 13.5%, followed by urinary tract infection (UTI), which occurred in 4.6% of patients. Most of the patients did not have infections (86.5%) or UTIs (95.4%) (Table 4 ). Table 4 comorbidity and precipitating factors of DKA among DM Patients at DMCSH, Ethiopia Variable Category Frequency Percent Comorbidity Yes 29 8.3 No 319 91.7 Hypertension Yes 14 4.0 No 334 96.0 Goiter Yes 2 0.6 No 346 99.4 HIV/AIDS Yes 3 0.9 No 345 99.1 TB all forms Yes 3 0.9 No 345 99.1 Asthma Yes 1 0.3 No 347 99.7 Pneumonia Sever 5 1.4 Mild 12 3.4 No 331 95.1 Precipitating factors Yes 102 29.3 No 246 70.7 Infection Yes 47 13.5 No 301 86.5 UTI Yes 16 4.6 No 332 95.4 3.4 Complication profile of patients with DKA In Table 5 , a small proportion of patients experienced nausea (1.2%) and vomiting (18.1%), while the majority did not report these symptoms (98.9% and 81.9%, respectively). Abdominal pain was reported in 46.8% of the patients, while 53.2% did not. Fatigue was a common symptom, affecting 85.3% of patients, and polyuria and polydipsia were also prevalent, affecting 97.7% and 91.3%, respectively. Diabetic foot ulcers and pyelonephritis were rare, and only 0.6% of patients experienced each. Most of the patients had a short stay (80.2%) and 80.5% did not experience rebound ketones, with 17.5% reporting it once. Regarding the admission ketone status, 59.8% had levels below 3, while 40.2% had levels < 3. Hypoglycaemia occurred in 18.7% of the patients and pneumonia in 3.4%. Urine glucose levels varied, with most patients having a result + 2 (41.7%) or + 3 (34.2%), and the mean random blood sugar level was 445.5 ± 102.6. Finally, both the length of stay and the admission ketone status showed a distribution of short stays (80.2%) and ketone levels under 3 (59.0%) (Table 5 ). Table 5 Complication clinical characteristics of complications of patients with DKA admitted to the Debre Markos comprehensive hospital, 2025 (n = 348) Variable Category Frequency Percent Nausea Yes 4 1.2 No 344 98.9 Vomiting Yes 63 18.1 No 285 81.9 Abdominal pain No 185 53.2 Yes 163 46.8 Fatigue Yes 275 85.3 No 51 14.7 Polyuria Yes 340 97.7 No 8 2.3 Polydipsia Yes 299 91.3 No 28 8.7 DM foot ulcer No 346 99.4 Yes 2 0.6 Pyelonephritis Yes 2 0.6 No 346 .4 Length of stay Short 279 80.2 Long 69 19.8 Frequency of rebound ketone No 280 80.5 One times 61 17.5 Two and above times 7 2.0 Admitted ketone status < 3 208 59.8 ≥ 3 140 40.2 Hypoglycemia Yes 65 18.7 No 283 81.3 Pneumonia Yes 12 3.4 No 336 96.6 Urine glucose Free 2 0.6 + 1 38 10.9 + 2 145 41.7 + 3 119 34.2 + 4 8 2.3 Not measured 36 10.3 Random Blood sugar Mean (± SD) 445.5 ± 102.6 Admission Ketone status < 3 193 59.0 ≥ 3 134 41.0 3.5 Treatment-related factors of DKA patients Among the patients studied, 19.0% experienced treatment complications, while 81.0% did not, and discontinuation of the drug occurred in 15.8% compared to 84.2% who continued treatment. Regarding the glycaemic status at discharge, 33.9% had hyperglycaemia, 60.1% achieved euglycemia, and 6.0% had hypoglycaemia. Ceftriaxone was used in 7.5% of the patients, azithromycin was 4.0%, metronidazole 9.2% and other antibiotics, including vancomycin and amoxicillin, were administered to 10.3%. Enalapril, an ACE inhibitor, was used in 6.9%, while β-blockers, calcium channel blockers, and diuretics were prescribed in 13.2%. Fluid replacement with 0.9% normal saline was provided in 86.2% of the cases. All patients (100%) received an initial dose of regular insulin (RI), intravenously / intramuscularly, while 37.1% received RI combined with NPH insulin, 10.3% took metformin alone, 5.2% were treated with glibenclamide, 6.9% were on both metformin and glibenclamide, and 36.5% received NPH insulin alone (Table 6 ). Table 6 Treatment related characteristics of patients with DKA in DMCSH, Ethiopia, 2025 (n = 348) Variable Category Frequency Percent Treatment complication Yes 66 19.0 No 282 81.0 Drug discontinuation Yes 55 15.8 No 293 84.2 Glycaemia level at discharge Hyperglycemia 118 33.9 Euglycemia 209 60.1 Hypoglycemia 21 6.0 Antibiotics Ceftriaxone 1gm IV BID 26 7.5 Azithromycin 500mg 14 4.0 Metronidazole 50mg IV BID 32 9.2 Others* 36 10.3 ACE inhibitors Enalapril 5 mg per oral daily 24 6.9 Others1 β-blockers, Calcium channel Blockers & Diuretics 46 13.2 Fluid replacement 0.9% normal saline solution 300 86.2% Anti-diabetic medications RI 10 units IV and 10 units IM stat 348 100 RI + NPH 0.5 units/kg/day BID 129 37.1 Metformin 500 mg PO BID 36 10.3 Glibenclamide 5 mg PO daily 18 5.2 Metformin 500 mg PO BID + Glibenclamide 5 mg PO daily 24 6.9 NPH 0.5 units/kg/day BID 127 36.5 N.B: BID, bis in die or twice a day; KG, kilogram; NPH, neutral protamine hagedorn, it is intermediate-acting insulin; PO, per os or peroral; RI, regular insulin, it is short-acting insulin. Others*: Vancomycin, cloxacline, Amoxicillin, norfloxacillin, metformin, Augmentin 3.6 Treatment of diabetic ketoacidosis The results of this study showed that the prevalence of poor treatment outcomes among diabetic patients with DKA at Debre Markos General Specialized Hospital was 15.5% (95% CI: 11.5%, 19.3%). Among the 54 patients who experienced poor outcomes, 19 (5.5%) died, 11 (3.2%) left against medical advice, and 24 (6.9%) were referred to other institutions (Fig. 1). 3.7 Factors associated with patients with diabetic ketoacidosis In binary logistic regression analysis, variables with a p-value less than 0.25 including sex, residence, severe DKA, hypoglycaemia, comorbidities, precipitating factors, infections, discontinuation of drugs, high ketone levels, random blood sugar (RBS) and treatment complications were identified as candidate variables for multivariate logistic regression. In the multivariate analysis, seven variables were found to be significantly associated with poor outcomes from PD: severe PD, comorbidities, infections, discontinuation of the drug, elevated ketone levels, treatment complications, and length of hospital stay. Patients who developed severe DKA were 1.48 times more likely to have poor DKA treatment outcomes compared to those with mild DKA status (AOR: 1.482, 95% CI: 1.324, 4.872). Similarly, the presence of comorbidities was associated with 1.8 times higher odds of poor outcomes compared to patients without comorbidities (AOR: 1.752, 95% CI: 1.215, 3.865). Patients who developed infections were also more likely to experience poor outcomes, with an AOR of 1.521 (95% CI: 1.362, 4.125). Regarding drug adherence, those who discontinued their prescribed diabetes medication were 2.12 times more likely to have poor treatment outcomes compared to those who continued their medication (AOR: 2.115, 95% CI: 1.245, 3.865). Treatment complications increased the likelihood of poor outcomes by 1.4 times compared to patients without complications (AOR: 1.356, 95% CI: 1.253, 4.125). Furthermore, patients with a ketone level < 3 at admission had a 21.3% higher risk of poor outcomes compared to those with levels < 3 (AOR: 1.213, 95% CI: 1.052, 2.876). Finally, a hospital stay of 5 days or less was associated with a 1.3-fold increase in the odds of poor outcomes compared to stays longer than 5 days (AOR: 1.29, 95% CI: 1.022, 3.254) (Table 7 ). Table 7 Results of Bivariable and Multivariable Logistic Regression Analyses of Factors Associated with Treatment Outcomes among DKA Patients at DMCSH, Northwest Ethiopia. Variable Category Treatment outcome of DKA COR 95%CI AOR 95% CI Poor Good Sex Male 17 116 0.705 (0.37, 1.31) 1.851(0.925, 4.124) Female 37 178 1 1 Residence Urban 38 198 1.152 (0.611, 2.168) 1.845(0.725, 3.253) Rural 16 96 1 1 Severity of DKA Mild 42 224 1 1 Moderate 8 55 0.776(0.345, 2.747) 0.923( 0.914, 2.912) Sever 4 15 1.422(1.150, 4.497) 1.482(1.324, 4.872)** Hypoglycemia Yes 11 54 1.137 (0.551, 2.348) 1.25(0.864, 3.231) No 43 240 1 1 Comorbidity Yes 5 24 1.148 (0.918, 3.153) 1.752(1.215, 3.865)* No 49 270 1 1 Precipitate factors Yes 84 18 1.250(0.703, 2.323) 1.212 (0.821, 3.253) No 210 36 1 1 Infection Yes 49 252 1.633( 1.235, 3.521) 1.521(1.362, 4.125)** No 5 42 1 1 Drug discontinuation Yes 13 42 1.902 (0.941, 3.847) 2.115(1.245, 3.865)** No 41 252 1 1 Ketone status at admission < 3 31 177 1 1 ≥ 3 23 117 1.122(0.924, 2.020) 1.213(1.052, 2.876)* RBS in mg/dl < 500 15 102 1 1 ≥ 500 39 192 1.381 (0.72, 2.625) 1.923( 0.876, 2.956) Treatment complication Yes 12 54 1.270 (0.927, 2.573) 1.356(1.253, 4.125)* No 42 240 1 1 Length of Stay in hospital ≤ 5 days 48 231 2.182 (0.83, 5.330) 1.29 (1.022, 3.254) * > 5days 6 63 1 1 Note: 1: reference, * p < 0.05, **p < 0.01 4. Discussion This study found that the prevalence of poor treatment outcomes among diabetic patients with diabetic ketoacidosis (DKA) at the Debre Markos comprehensive specialised hospital was 15.5% (95% CI: 11.5%, 19.3%). Among those with poor outcomes, 5.5% died, 3.2% left without medical advice, and 6.9% were referred to other institutions. This finding aligns with similar research carried out in Ethiopia (12%) [ 14 ], Kenya (17.2%) [ 13 ], Nigeria (16 %) [ 25 ], Zabia16.66 %[ 26 ] and Malayia 17.6 %[ 9 ]. However, theprevalence observed in Ethiopia is significantly lower than that reported in other countries, such as, Kenya (29.8 %) [ 27 ], Cameroon (21. %)[ 28 ]. These findings maydiffer due to several factors, such as variations in clinical presentation, the effectiveness of DKA detection and management, the prevalence of precipitating factors, and the capacity to address complications in various healthcare settings. It is important to note that the outcomes remain higher than those reported in some other regions with a well-established medical infrastructure. For example, studies conducted in Thailand (4.3 %)[ 29 ] and Saudi Arabia (1.83 ) reported significantly lowe DKA-related mortality rates. Furthermore, in treatment-experienced facilities in Asia, Europe, and the Americas, a 5 % mortality rate for DKA has ben documented [ 30 ]. These findings suggest that poor outcomes remain a significant concern in the management of DKA within low-resource settings, although rates can vary depending on the population and the health facility. Among the 54 patients with poor treatment results, 19 (5.5%) died, 11 (3.2%) left against medical advice, and 24 (6.9%) were referred to other institutions. The mortality rate observed in this study is comparable to findings in Lusaka, Zambia [ 26 ], where the mortality rate in patients with DKA was 7.5 %, ut lower than the 9% mortality rate reported in a large U.S. cohort study [ 31 ]. The discrepancy in mortality rates could be attributed to factors such as differences in healthcare infrastructure, early intervention capabilities and patient management protocols. One of the significant findings of this study was that patients with severe DKA had significantly higher odds of poor treatment outcomes compared to those with mild DKA. This is consistent with existing literature in Debretabour[ 20 ] and Saudi Arabia [ 8 ]which consistently shows that severe DKA is associated with worse outcomes, and also reported that severe DKA, defined by higher blood glucose and ketone levels, correlates with increased mortality and morbidity rates. The severity of DKA often reflects a delayed diagnosis and inadequate treatment, factors that can contribute to worsened prognosis [ 30 ] The presence of comorbidities was another strong predictor of poor treatment outcomes, with patients having 1.8 times higher odds of poor outcomes compared to those without comorbidities. This aligns with findings from [ 14 , 24 ] who demonstrated that comorbid conditions such as hypertension, cardiovascular disease, and kidney dysfunction exacerbate the course of DKA and negatively impact patient recovery. In addition, infections were found to be significantly associated with poor outcomes in this study, reinforcing findings from [ 20 ]where infection was a key factor contributing to DKA-related complications and mortality. Residing in a developing country where hygiene is a major concern may contribute to an increased risk of urinary tract infections (UTI) in people with diabetes mellitus (DM). The study also identified discontinuation of drugs as a major risk factor for poor outcomes, with patients who discontinued their prescribed diabetes medications being 2.12 times more likely to experience poor treatment outcomes. This is consistent with the [ 31 ] guidelines, which highlight medication adherence as a crucial factor in preventing episodes of DKA and improving the prognosis of the patient. Patients who do not adhere to treatment protocols often have inadequate glycaemic control, increasing the risk of metabolic derangements such as DKA. Furthermore, treatment complications significantly increased the odds of poor DKA treatment outcomes, which is consistent with findings from [ 8 ], where complications such as electrolyte imbalances and fluid overload were associated with worse patient outcomes. Another important factor positively significant with the poor outcome of DKA treatment in patients with DKA was ketone levels < 3 at admission with a 21.3% increased risk of poor outcomes, which aligns with previous studies[ 32 , 33 ] that demonstrate that high ketone levels correlate with severe metabolic acidosis and poorer recovery in patients with DKA. Lastly, the length of hospital stay also played a role in treatment outcomes. Patients with a shorter hospital stay (5 days) were found to have 1.3 times higher odds of poor outcomes compared to those with longer stays. This finding might seem counterintuitive with support of[ 20 ] but it could reflect the complexity of cases that require longer management and the potential for quicker discharges in less complicated cases. However, it also suggests the importance of post-discharge care and follow-up to ensure patient stability after DKA treatment. The strength of this study offers valuable empirical evidence on the prevalence and associated factors of poor treatment outcomes among DKA patients in a real-world hospital setting in northwest Ethiopia, addressing a significant gap in regional data. The application of both bivariable and multivariable logistic regression analyses allowed the control of potential confounders and facilitated the identification of independent predictors. In particular, the study highlights several clinically important risk factors including severe DKA, comorbidities, infections, discontinuation of treatment, elevated ketone levels, and treatment complications that can support the development of targeted interventions and improve hospital management strategies for patients with DKA. However, the study has several limitations. Being a cross-sectional study in nature, it relied on existing medical records, which may have been incomplete or inconsistently documented, introducing the risk of information bias. Additionally, the study was conducted in a single comprehensive hospital, which may limit the generalizability of the findings to broader populations or different healthcare settings. Furthermore, certain potentially influential variables such as socioeconomic status, educational background, and long-term follow-up outcomes were not assessed, which could have provided a more comprehensive analysis. Finally, the classification of poor outcomes included heterogeneous categories (death, referral, and leave without medical advice), which may vary in clinical severity and underlying causes, but were analysed as a single group. 5. Conclusions This study revealed that the prevalence of the poor DKA treatment outcomes among diabetic patients at Debre Markos' comprehensive specialized hospital was high. The findings of this study underscore several critical factors that influence treatment outcomes in patients with DKA, including severity of the condition, comorbidities, infections, drug adherence, complications during treatment, high levels of ketones (3 < 3) at admission, and short hospital stay (5 days). Develop strategies to strengthen early detection, manage comorbidities and infections, ensure proper drug adherence, and effectively monitor complications. Improve hospital protocols, patient education, and structured follow-up to improve treatment outcomes. Abbreviations COR : Crude Odds Ratio; DKA : Diabetic Ketoacidosis; DMCSH : Debre Markos Comprehensive Specialized Hospital; FBG : Fasting Blood Glucose Level; HHS : Hyperglycaemic Hyperosmolar State; ID F: International Diabetes Federation; NPH : Neutral Protamine Hagedorn Insulin. Declarations Ethics approval and consent to participate The current study included human respondents because this ethical clearance was obtained from the Research Ethics Review Committee, Department of Medicine and Health Sciences, Debre Markos University with reference number RCSTTD/522/01/17. A permission letter was written by the Amhara Public Health Institute and a cooperation letter was obtained from Debre Markos comprehensive specialized hospital to collect the data. To keep confidentiality, names and unique card numbers were not included in the data collection tool. After entering to the computer, the data were locked by password and was not disclosed to any person other than principal investigator. All information collected from the patient chart was kept strictly confidential. Consent for publication Not applicable Availability of data and materials. The primary data contributed in this study were included in the article; Any clarity issues can be directly communicated with the corresponding author. Competing Interests The authors declare that they have no competing interests. Funding There is no any fund. Authors' Contributions MBY: Writing—original draft; writing—review & editing; conception; investigation; software; data curation; methodology; formal analysis; resources; and visualization. FL: Writing—original draft; writing—review & editing; conceptualization; investigation; data curation; methodology; supervision; project administration; funding acquisition; resources; and visualization. FM: Writing—original draft; writing—review & editing; investigation; data curation; supervision; validation; and visualization. MT: Writing—original draft; writing—review & editing; investigation; methodology; supervision; validation; and visualization. All authors read and approved the final manuscript. Acknowledgements The authors sincerely thank Debre Markos Comprehensive Specialized Hospital for facilitating data collection and providing a dedicated space. We also appreciate the efforts of our data collectors and supervisors for their dedication and hard work. References Association AD. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37(Supplement_1):S81–90. Umpierrez G, Korytkowski M. Diabetic emergencies—ketoacidosis, hyperglycaemic hyperosmolar state and hypoglycaemia. Nat Rev Endocrinol. 2016;12(4):222–32. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045., 2022, 183. DOI: https://doi org/101016/j diabres. 2021;109119. Lee SE, Kim KA, Son KJ, Song SO, Park KH, Park SH, et al. Trends and risk factors in severe hypoglycemia among individuals with type 2 diabetes in Korea. Diabetes Res Clin Pract. 2021;178:108946. Berhe KK. Diabetes-Related Distress and Associated Factors among People with Type 2 Diabetes in Mekelle City, Tigray Region, Ethiopia. 2023; Organization WH. Guidelines for the prevention, management and care of diabetes mellitus. 2006. Usher-Smith JA, Thompson MJ, Sharp SJ, Walter FM. Factors associated with the presence of diabetic ketoacidosis at diagnosis of diabetes in children and young adults: a systematic review. Bmj. 2011;343. Alotaibi A, Aldoukhi A, Albdah B, Alonazi JA, Alseraya AS, Alrasheed N. Diabetic ketoacidosis treatment outcome and associated factors among adult patients admitted to the emergency department and medical wards at King Abdulaziz Medical City, Riyadh, Saudi Arabia. Cureus. 2020;12(8). Usman A, Sulaiman SAS, Khan AH, Adnan AS. Profiles of diabetic ketoacidosis in multiethnic diabetic population of Malaysia. Tropical Journal of Pharmaceutical Research. 2015;14(1):179–85. Otieno CF, Kayima JK, Omonge EO, Oyoo GO. Diabetic ketoacidosis: risk factors, mechanisms and management strategies in sub-Saharan Africa: a review. East Afr Med J. 2005;82(12). Sherif FM. Clinical profile of Libyan patients admitted with diabetic ketoacidosis. 2024; Mahesh MG, ShIvaSwaMy RPr, ChandRa BS, Syed S. The study of different clinical pattern of diabetic ketoacidosis and common precipitating events and independent mortality factors. J Clin Diagn Res. 2017;11(4):OC42. Otieno CF, Kayima JK, Mbugua PK, Amayo AA, Mcligeyo SO. Prognostic factors in patients hospitalised with diabetic ketoacidosis at Kenyatta National Hospital, Nairobi. East Afr Med J. 2010;87(2):67–74. Mitiku Yigazu D, Lema M, Bekele F, Tesfaye Daka D, Samuel D, Addisu N. Diabetic ketoacidosis treatment outcomes and its associated factors among adult patients with diabetes mellitus admitted to public hospitals in Nekemte Town, Ethiopia: a cross-sectional study. Frontiers in Clinical Diabetes and Healthcare. 2024;5. Taye GM, Bacha AJ, Taye FA, Bule MH, Tefera GM. Diabetic ketoacidosis management and treatment outcome at medical ward of Shashemene Referral Hospital, Ethiopia: a retrospective study. Clin Med Insights Endocrinol Diabetes. 2021;14:11795514211004956. Abela AG, Magri CJ, Debono M, Calleja N, Vassallo J, Azzopardi J. An audit of the management of diabetic ketoacidosis at St Luke’s Hospital. 2008; Kassaye DA, Girsha WD, Guto GJ, Deybasso HA. Diabetic ketoacidosis treatment outcome and associated factors among adult patients admitted to medical wards of Adama Hospital Medical College, Oromia, Ethiopia. Am J Intern Med. 2018;6(2):34–42. Desse TA, Eshetie TC, Gudina EK. Predictors and treatment outcome of hyperglycemic emergencies at Jimma University Specialized Hospital, southwest Ethiopia. BMC Res Notes. 2015;8:1–8. Asfaw TP, Binega MG, Asmamaw MA, Molla TB. Treatment outcome and predictors of mortality among adult diabetic patients admitted with hyperglycemic crises at hiwot fana comprehensive specialized university hospital, eastern Ethiopia. East African Journal of Health and Biomedical Sciences. 2021;5(2):45–52. Mekonnen GA, Gelaye KA, Gebreyohannes EA, Abegaz TM. Treatment outcomes of diabetic ketoacidosis among diabetes patients in Ethiopia. Hospital-based study. PLoS One. 2022;17(4):e0264626. Bishu KG, Jenkins C, Yebyo HG, Atsbha M, Wubayehu T, Gebregziabher M. Diabetes in Ethiopia: a systematic review of prevalence, risk factors, complications, and cost. Obes Med. 2019;15:100132. Adem A, Demis T, Feleke Y. Trend of diabetic admissions in Tikur Anbessa and St. Paul’s University Teaching Hospitals from January 2005-December 2009, Addis Ababa, Ethiopia. Ethiop Med J. 2011;49(3):231–8. Bedaso A, Oltaye Z, Geja E, Ayalew M. Diabetic ketoacidosis among adult patients with diabetes mellitus admitted to emergency unit of Hawassa university comprehensive specialized hospital. BMC Res Notes. 2019;12:1–5. Derse TK, Haile MT, Chamiso TM. Outcome of Diabetic Keto Acidosis Treatment and Associated Factors Among Adult Patients Admitted to Emergency and Medical Wards at St. Paul’s Hospital, Addis Ababa Ethiopia, 2023: A Cross-Sectional Study. Diabetes, Metabolic Syndrome and Obesity. 2023;3471–80. Edo AE. Clinical profile and outcomes of adult patients with hyperglycemic emergencies managed at a tertiary care hospital in Nigeria. Nigerian Medical Journal. 2012;53(3):121–5. Kakusa M, Kamanga B, Ngalamika O, Nyirenda S. Comatose and noncomatose adult diabetic ketoacidosis patients at the University Teaching Hospital, Zambia: Clinical profiles, risk factors, and mortality outcomes. Indian J Endocrinol Metab. 2016;20(2):199–205. Mbugua PK, Otieno CF, Kayima JK, Amayo AA, McLigeyo SO. Diabetic ketoacidosis: clinical presentation and precipitating factors at Kenyatta National Hospital, Nairobi. East Afr Med J. 2005;82(12). Nkoke C, Bain LE, Makoge C, Teuwafeu D, Mapina A, Nkouonlack C, et al. Profile and outcomes of patients admitted with hyperglycemic emergencies in the Buea Regional Hospital in Cameroon. Pan African medical journal. 2021;39(1). Thewjitcharoen Y, Plianpan P, Chotjirat A, Nakasatien S, Chotwanvirat P, Wanothayaroj E, et al. Clinical characteristics and outcomes of care in adult patients with diabetic ketoacidosis: a retrospective study from a tertiary diabetes center in Thailand. J Clin Transl Endocrinol. 2019;16:100188. Association AD. Standards of medical care in diabetes—2015 abridged for primary care providers. Clin Diabetes. 2015;33(2):97. Association AD. Diabetes care in the hospital: standards of medical care in diabetes—2020. Diabetes Care. 2020;43(Supplement_1):S193–202. Yigazu DM, Lema M, Bekele F, Daka DT, Samuel D, Addisu N. Diabetic ketoacidosis treatment outcomes and its associated factors among adult patients with diabetes mellitus admitted to public hospitals in Nekemte Town, Ethiopia: A Cross-sectional study. Frontiers in Clinical Diabetes and Healthcare. 5:1446543. Hirobata T, Inaba H, Kaido Y, Kosugi D, Itoh S, Matsuoka T, et al. Serum ketone body measurement in patients with diabetic ketoacidosis. Diabetol Int. 2022;13(4):624–30. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Dec, 2025 Read the published version in European Journal of Medical Research → Version 1 posted Editorial decision: Revision requested 31 Jul, 2025 Reviews received at journal 27 Jul, 2025 Reviews received at journal 25 Jul, 2025 Reviewers agreed at journal 18 Jul, 2025 Reviewers agreed at journal 17 Jul, 2025 Reviewers invited by journal 16 Jul, 2025 Editor assigned by journal 16 Jul, 2025 Submission checks completed at journal 15 Jul, 2025 First submitted to journal 13 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7114400","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486801218,"identity":"0cbca097-0b90-4d4b-8779-eabe0ee7a235","order_by":0,"name":"Fenta Limenih","email":"","orcid":"","institution":"Dembecha Distric Health Office","correspondingAuthor":false,"prefix":"","firstName":"Fenta","middleName":"","lastName":"Limenih","suffix":""},{"id":486801219,"identity":"72e5699a-72c0-4f30-8573-85150d2bdec9","order_by":1,"name":"Feriehiwot Molla","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Feriehiwot","middleName":"","lastName":"Molla","suffix":""},{"id":486801220,"identity":"5147831a-bec2-4e55-806a-46c805b6054d","order_by":2,"name":"Muluken Teshome","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Muluken","middleName":"","lastName":"Teshome","suffix":""},{"id":486801221,"identity":"3c0bfd56-0ea0-4941-8ec1-7a3a25ef07f0","order_by":3,"name":"Melesse Belayneh Yayeh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYFAC5gYog4fxAYjkI6yFEa6F2QBEspGihU0CRBHUotve2PjwR8VheYPjvccqv+bYybAxMD98dAOPFrMzB5uNec4cNtxw5lzabdltyUCHsRkb5+DTciOxTZqx7TDjhhs5ZrcltzEDtfCwSePVcv9h+8+f/w7bb7j/xqxYcls9EVpuMLYx8DYcTtxwg8eM8eO2w0RoOZPYLM1zLD155pkcY2nGbcd52JgJ+eX44YMff9RY2/YdP2P48ee2ant+9uaHj/FpgYJmBoUDwITAA2IzE1YOAnUM8g3AWP1BnOpRMApGwSgYYQAAekxOHX1s8HsAAAAASUVORK5CYII=","orcid":"","institution":"Bahir Dar University","correspondingAuthor":true,"prefix":"","firstName":"Melesse","middleName":"Belayneh","lastName":"Yayeh","suffix":""}],"badges":[],"createdAt":"2025-07-13 16:08:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7114400/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7114400/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40001-025-03593-1","type":"published","date":"2025-12-04T15:57:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87362591,"identity":"890fb12b-8c56-433a-9d81-c699e6e6586b","added_by":"auto","created_at":"2025-07-23 05:56:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":95560,"visible":true,"origin":"","legend":"\u003cp\u003eTreatment outcomes of diabetic ketoacidosis among diabetic patients in Debre Markos comprehensive specialized hospital, 2025.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-7114400/v1/ad12ab215fac9bbe7232a548.png"},{"id":97724792,"identity":"6eee6312-0923-4142-a433-812b272f4db0","added_by":"auto","created_at":"2025-12-08 16:13:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1615400,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7114400/v1/6e907efb-fcad-4707-bfcc-197fc741855e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePrevalence of treatment outcomes and associated factors of diabetic ketoacidosis among adult diabetic patients admitted to Debre Markos comprehensive specialized hospital, Northwest Ethiopia: \u003cem\u003eA cross-sectional study\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"Text box 1. Contributions to the literature ","content":"\u003ctable border=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026middot; Highlights there is limited evidence on treatment outcomes of diabetic ketoacidosis (DKA) among diabetic patients, particularly in Ethiopia.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026middot; Identifies preventable factors, such as infections, poor adherence to treatment guidelines, and inadequate ketone management as key contributors to poor outcomes, including mortality.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026middot; Emphasizes the urgent need for improved hospital-based DKA management and targeted public health strategies to address these challenges in the affected population.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eDiabetes mellitus is a group of metabolic disorders characterized by the presence of hyperglycaemia due to impaired insulin secretion, action, or both, which results in alteration of carbohydrate, protein, and fat metabolism [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Diabetes mellitus is most commonly associated with older age, obesity, family history of diabetes mellitus, genetic susceptibility, hypertension, dyslipidaemia, autoimmunity, and physical inactivity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Diabetes is one of the largest global public health emergencies of the 21st century. According to the report of the International Diabetes Federation, 536.6\u0026nbsp;million adults (10.5%) lived with diabetes mellitus worldwide in 2021, and this number is expected to increase to 783.2\u0026nbsp;million (12.2%) by 2045 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. According to the IDF 2021 estimate, 24\u0026nbsp;million adults aged 20\u0026ndash;79 years lived with diabetes in Africa [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDiabetic ketoacidosis is an emergency that encompasses the spectrum of preventable acute diabetic complications, which can occur in patients with type 1 and type 2 diabetes mellitus. DKA in the setting of relative or absolute insulin deficiency, excessive counter regulatory hormone levels, progressive volume depletion, and loss of electrolytes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. According to the World Health Organization treatment guideline, diabetic ketoacidosis is a common and potentially fatal acute complication of diabetes mellitus during diagnosis and follow-up [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe poor outcome of the DKA treatment can lead to a debilitating and potentially fatal complication, including cerebral oedema and severe hypoglycaemia. Mortality of DKA has been reported to be less than 5% in centres of treatment experienced in the Americas, Europe, and Asia [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and in Riyadh, Saudi Arabia, King Abdul-Aziz Medical City (2%) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, in developing countries, high poor treatment outcomes are observed. For instance, in Malaysia 24%. Of which 17.6% of DKA patients died (Usman et al., 2015), Kenya, Tanzania and Ghana between 26% and 29% [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], in Liberia 19.2% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], Zambia 21% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], Kenya\u0026rsquo;s Kenyatta National Hospital 29.8% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Similar studies in Ethiopian countries showed a high prevalence of poor treatment outcomes. Nekemte referral hospital 11.4% [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Shashemene referral hospital, 26.2% [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], Addis Addis Ababa, at St. Luke Catholic Hospital, 13% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], Adama General Hospital 15.1% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Jima University Hospital 9.8% [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e],Hiwot Fana Specialized University Hospital 17.8% [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and Debre Tabor General Hospital, 20% [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This magnitude imposes a high national and individual economic burden associated with medication, bed occupancy, long hospital stays, and mortality. The average treatment and laboratory cost is significantly higher among Diabetic ketoacidosis emergencies compared to other emergency cases [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCommon causes of CKD are missed insulin dose, illness or infection, and undiagnosed or untreated diabetes. The main clinical features of DKA are hyperglycaemia, dehydration, loss of electrolytes, and acidosis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Different researches indicated that; socio-demographic characteristics, behavioural factors, treatment-related factors, use of alternative medications, and clinical factors were risk factors for diabetic ketoacidosis among patients with DM [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eIn the study area, limited studies have been conducted on the outcome of the treatment of diabetic ketoacidosis and the associated factor. Therefore, this study aims to assess the prevalence of poor treatment outcome of diabetic ketoacidosis and associated factors among adult diabetic patients admitted to the Debre Markos comprehensive specialized hospital, northwest Ethiopia. This study provides valuable information for health policy, health system managers, healthcare providers, and patients to reduce the occurrence of diabetic ketoacidosis and associated factors.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study area and period\u003c/h2\u003e\u003cp\u003e Debre Markos Comprehensive Specialized Hospital is one of the governmental hospitals which is located in the Amhara region, East Gojame Zone, in Debre Markos town, which is 300 km from Addis Ababa, the capital city of Ethiopia, and 255 km from Bahirdar (the capital city of the Amhara Regional state) in North West Ethiopia. It provides preventive, diagnostic, curative and rehabilitative service for millions of people in the region with 9 wards, 29 different outpatient units and 143 beds. Currently there are more than 2301 diabetic patients who receive regular follow-up care at the hospital. From August 28, 2019 to September 30, 2024, the number of patients with DM2 1060 and DM1 980 and 480 patients were patients with DKA. Outpatient, emergency and surgical care service is provided to diabetes patients. The study was carried out at the Debre Markos specialized hospital in North West Ethiopia from April 8, 2025 to April 28, 2025.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Study design\u003c/h2\u003e\u003cp\u003eA hospital-based cross-sectional study was conducted.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Population\u003c/h2\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 Source population\u003c/h2\u003e\u003cp\u003eAll admitted adults (age \u0026ge;18 years old) DM patients who had developed ketoacidosis at Debre Markos Comprehensive specialized Hhospital.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2 Study population\u003c/h2\u003e\u003cp\u003eAll adults (age \u0026ge; 18 years old) diagnosed with DM1 and DM2 and who have diabetic ketoacidosis admitted from August 28, 2019 to September 30, 2024 in Debre Markos Comprehensive specialized hospital.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Inclusion and Exclusion criteria\u003c/h2\u003e\u003cp\u003eAll adults\u0026thinsp;\u0026lt;\u0026thinsp;18 years of age who were diagnosed with type 1 or type 2 diabetes mellitus and admitted with diabetic ketoacidosis between August 28, 2019, and September 30, 2024, at Debre Markos Comprehensive Specialized Hospital were included in the study. Individuals with incomplete records of key variables and pregnant women were excluded from the study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Sample size determination and sampling procedure\u003c/h2\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.5.1 Sample size determination\u003c/h2\u003e\u003cp\u003eThe sample size was calculated using a single population proportion formula for both the outcome of diabetic ketoacidosis treatment and associated factors with a study conducted in Addis Ababa DKA treatment. The improved prevalence was 71.1% ([\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] of the patients discharged. Assumption of a 95% CI, 5% marginal error (W) and P\u0026thinsp;=\u0026thinsp;0.711\u003c/p\u003e\u003cp\u003eThe sample size with the formula is:-\u003c/p\u003e\u003cp\u003en=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{Z}{\\left(\\frac{{\\alpha\\:}}{2}\\right)}^{2}*PQ}{{\\text{W}}^{2}}\\)\u003c/span\u003e\u003c/span\u003e=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{Z}{\\left(\\frac{{\\alpha\\:}}{2}\\right)}^{2}*P(1-P)}{{\\text{W}}^{2}}\\)\u003c/span\u003e\u003c/span\u003e=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{\\left(1.96\\right)}^{2}*\\:0.711*0.299}{{\\left(0.05\\right)}^{2}}\\)\u003c/span\u003e\u003c/span\u003e= 327, adding 10% for non-response (incomplete chart), the final sample size for objective one was 360.\u003c/p\u003e\u003cp\u003eFor the second objective sample size determined using factors associated with treatment outcomes of DKA patients. Taking into consideration the assumption: Power 80%, one-to-one ratio between exposed and unexposed groups, AOR (lower AOR to get larger sample size), % of outcome in exposed and unexposed group were taken. It is computed using EPI-info version 7.2.6 STATCALC dialogue box using cross sectional tool bar auto calculate the sample size by entering in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e data elements and the final sample size included 10% nonresponse rate.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSample size determination using factors that affect the treatment outcomes of diabetic ketoacidosis among admitted adult diabetes patients at Debre Markos Hospital, Amhara Region, Ethiopia\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% outcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRatio\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePower %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSample size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eInfection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e86.93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e4.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.17%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSmoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e18.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePotassium replacement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e81.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eComorbidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e95%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eProportion of treatment outcomes for DKA patients among the exposed group\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003e**\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eProportion of treatment outcomes of DKA patients among the unexposed group\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTherefore, the larger sample size of the first objective, 360 DKA patients, is the final sample size for this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e\u003cb\u003e2.5.2 Sampling techniques\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eIn this study, simple random sampling techniques were used to select the study samples. From the emergency and in patient registration logbook DKA patients was taken and then based on the card number was selected within a computer-generated random selection. Simple random techniques were used to select the required sample size of 360 from the study period. If a patient experienced two or more episodes of DKA, only the most recent episode was considered to assess treatment outcomes and associated factors.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.\u003cb\u003e6 Study variables\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe dependent variable was the result of the treatment of diabetic ketoacidosis (poor vs. good), while the independent variables included sociodemographic characteristics (age, sex, marital status, residence, occupation and family history of diabetes mellitus); health-related factors (severity of DKA, clinical characteristics (respiratory rate, pulse rate, blood pressure, temperature, blood glucose level, urine glucose level and urine ketone level), recent acute illness, infection, duration of diabetes mellitus, type of diabetes mellitus, presence of comorbidities, and chronic diabetic complications); and treatment-related variables (type of medication used, drug discontinuation, treatment complications, glycemic control, frequency of blood glucose monitoring, and doses of diabetes medications).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Operational definitions\u003c/h2\u003e\u003cp\u003eOutcomes of DKA treatment: this study is operationalized as a good and poor treatment of the outcome as follows:-\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eGood outcome of treatment\u003c/strong\u003e\u003cp\u003epatients who had improved at the end of treatment at discharge [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePoor outcome of treatment\u003c/strong\u003e\u003cp\u003epatients who were left without medical advice or referred or died in the hospital [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMild DKA\u003c/b\u003e is defined as (arterial pH, 7.25 to 7.30 and serum bicarbonate, 15 to 18 mEq / L) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eModerate DKA\u003c/b\u003e is defined as (arterial pH, 7.00 to \u0026lt;\u0026thinsp;7.25 and serum bicarbonate, and 10 to \u0026lt;\u0026thinsp;15 mEq/L) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLong hospital stay\u003c/b\u003e was defined as hospital stay for more than 5 days [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe short hospital stay\u003c/b\u003e was defined as the patient stayed in the hospital for less than or equal to 5 days [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eHyperglycaemic emergencies\u003c/b\u003e- including diabetic ketoacidosis (DKA), hyperosmolar hyperglycaemic state (HHS) and defined as random plasma glucose\u0026thinsp;\u0026gt;\u0026thinsp;200 mg/dL and DKA diagnosed when blood glucose is \u0026gt;\u0026thinsp;250 mg/dl, arterial pH\u0026thinsp;\u0026lt;\u0026thinsp;7.3, bicarbonate\u0026thinsp;\u0026lt;\u0026thinsp;15 mEq/L, in the presence of ketonuria [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSevere hypokalaemia\u003c/b\u003e is a plasma potassium level of less than 2.5 mmol/L [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Data collection tool and procedure\u003c/h2\u003e\u003cp\u003eData were collected from the patient chart using a pre-tested data extraction checklist. The data extraction checklist is developed by the principal investigator by reviewing previous literature.\u003c/p\u003e\u003cp\u003eThe data collection tools, included sociodemographic, disease-related, and treatment-related factor components.\u003c/p\u003e\u003cp\u003eA supervisory health officer, three BSC nurses for data collection, and two medical record room workers for chart finding were temporarily recruited for twenty days and participated in the data collection process. Patient charts were retrieved using their medical registration number from the medical record room by record room workers. The data collectors collected the necessary information using the data extraction tool in the designated card room area. A supervisor and the principal investigator followed the data collection process.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e2.9 Data quality assurance\u003c/h2\u003e\u003cp\u003eOne day of training was given to data collectors and supervisors on the objective of the study, the content, meaning of the questionnaire/checklists and the way to collect data before the actual data collection is started. The data collection tool was pretested on 5% of the sample size (17 charts) in Fenote selam hospital a week before the actual study. After pre-test is done all modifications were implemented. The data collected were daily evaluated by the supervisors and the principal investigator. The supervisor was to check the completed data collection tool daily for its completeness. In addition to this, the principal investigator was careful to enter and thoroughly clean the data before the beginning of the analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e2.10 Data Processing and Analysis\u003c/h2\u003e\u003cp\u003eData were checked and entered into the Epi-Data version 4.6 statistical software and exported to the Statistical Package for Social Science (SPSS) statistical software package, version 26 for analysis. Frequencies and proportions were used to summarize the variables. In addition to frequencies and proportions, each variable was presented using tables and figures. The association between the treatment outcomes of patients with DKA and each categorical variable was assessed using the logistic regression model. The outcome variable categorizes two forms: poor outcome and good outcome of treatment. These categories were coded as follows: 1 poor outcome treatment and 0 good outcome treatment. All independent variables with P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in the bivariate analysis were the candidate adjusting the confounders for the multivariate analysis. The significance of the association was determined at a P-value of \u0026lt;\u0026thinsp;0.05 in multivariate analysis, while the strength of the association is indicated by the adjusted odds ratio (AOR) with a 95% confidence interval. The model was fitted and checked by the Hosmer-Lemshow fitness model, p value 0.89.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Socio-demographic characteristics\u003c/h2\u003e\u003cp\u003eA total of 348 DKA patient charts were retrieved from those admitted (360) to DMCSH, yielding a response rate of 96.7%. The mean age of the participants was 36.5 years, with a standard deviation of 12 years. The age distribution revealed that most of the patients were between 35 and 44 years of age, with 27%. Females comprised 61.8% of the participants and the majority of the patients resided in an urban area (67.8%). In terms of marital status, the majority were married (52.6%), followed by singles (32.2%). Occupationally, the majority of the patients were merchants (47.7%), followed by employees (36.8%) and farmers (12.9%). In particular, 75.0% of the patients had unknown family histories of diabetes (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-demographic characteristics among DKA patients, DMCSH, north-west Ethiopia, (n\u0026thinsp;=\u0026thinsp;348)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eAge in years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u0026ndash;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e61.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eResidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e236\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e52.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eOccupational status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMerchant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployee\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFarmer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eFamily history of DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Baseline clinical characteristics among patients with DKA\u003c/h2\u003e\u003cp\u003eIn 3 table, the majority of patients were diagnosed with known Type 1 diabetes (43.1%) or newly diagnosed Type 1 diabetes (35.6%), while 5.5% were newly diagnosed with Type 2 diabetes and 15.8% had known Type 2 diabetes. Regarding the history of diabetes, 58.9% of the patients had a known history of diabetes, while 41.1% were newly diagnosed. Most patients (88.8%) experienced diabetic ketoacidosis (DKA) two times or less, with 11.2% having more frequent occurrences. The mean duration of diabetes was 26.54 years (\u0026plusmn;\u0026thinsp;39.2 years). Pulse rates were mostly normal (72.1%), with 27.0% having tachycardia and a small percentage (0.9%) experiencing bradycardia. Mean systolic and diastolic blood pressures were 104.4\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5 and 67.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5, respectively, and most patients had normal blood pressure (59.8%), although 11.2% had hypotension. Respiratory rates were primarily normal (68.1%), while 31.9% had tachypnea. The average temperature was 36.5\u0026deg;C (\u0026plusmn;\u0026thinsp;0.95\u0026deg;C). Dehydration was most commonly not known (86.2%), although 10.1% had mild dehydration, and a small number had moderate (3.4%) or severe dehydration (0.3%). Most of the patients had mild DKA (76.4%), moderate DKA in 18.1% and severe DKA in 5.5% (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline clinical characteristics among DKA patients, DMCSH, North West Ethiopia\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eTypes of DM diagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNew DM 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNew DM 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKnown DM 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKnown DM 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHistory of DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNew\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKnown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFrequency of DKA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;2 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;2 times\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e26.54 (\u0026plusmn;\u0026thinsp;39.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePulse rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBradycardia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTachycardia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystolic Blood pressure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e104.4 (\u0026plusmn;\u0026thinsp;15.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiastolic blood pressure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e67.8 (\u0026plusmn;\u0026thinsp;10.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eBP status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHypotension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElevated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRespiration rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e237\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTachypnea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e36.5 (\u0026plusmn;\u0026thinsp;0.95)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eDehydration status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild dehydration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate dehydration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere dehydration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot Known\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eSeverity of DKA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild DKA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate DKA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSever DKA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Comorbidity and related factors that precipitate DKA in patients\u003c/h2\u003e\u003cp\u003eIn this dataset, 8.3% of patients had comorbidities, with the majority (91.7%) having none. Hypertension was present in 4.0% of the patients, while the vast majority (96.0%) did not. Toxic multinodular goitre and HIV/AIDS were rare, affecting only 0.6% and 0.9% of patients, respectively, while tuberculosis in all forms was also reported by 0.9%. Asthma was found in just 0.3% of the patients. Regarding pneumonia, most of the cases were mild (3.4%) or severe (1.4%), while the majority (95.1%) did not experience pneumonia. Precipitation factors were observed in 29.3% of patients, infection the most common, reported by 13.5%, followed by urinary tract infection (UTI), which occurred in 4.6% of patients. Most of the patients did not have infections (86.5%) or UTIs (95.4%) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ecomorbidity and precipitating factors of DKA among DM Patients at DMCSH, Ethiopia\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eComorbidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e91.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e96.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGoiter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHIV/AIDS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTB all forms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAsthma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e95.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePrecipitating factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eInfection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e86.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eUTI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e95.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Complication profile of patients with DKA\u003c/h2\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, a small proportion of patients experienced nausea (1.2%) and vomiting (18.1%), while the majority did not report these symptoms (98.9% and 81.9%, respectively). Abdominal pain was reported in 46.8% of the patients, while 53.2% did not. Fatigue was a common symptom, affecting 85.3% of patients, and polyuria and polydipsia were also prevalent, affecting 97.7% and 91.3%, respectively. Diabetic foot ulcers and pyelonephritis were rare, and only 0.6% of patients experienced each. Most of the patients had a short stay (80.2%) and 80.5% did not experience rebound ketones, with 17.5% reporting it once. Regarding the admission ketone status, 59.8% had levels below 3, while 40.2% had levels\u0026thinsp;\u0026lt;\u0026thinsp;3. Hypoglycaemia occurred in 18.7% of the patients and pneumonia in 3.4%. Urine glucose levels varied, with most patients having a result\u0026thinsp;+\u0026thinsp;2 (41.7%) or +\u0026thinsp;3 (34.2%), and the mean random blood sugar level was 445.5\u0026thinsp;\u0026plusmn;\u0026thinsp;102.6. Finally, both the length of stay and the admission ketone status showed a distribution of short stays (80.2%) and ketone levels under 3 (59.0%) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComplication clinical characteristics of complications of patients with DKA admitted to the Debre Markos comprehensive hospital, 2025 (n\u0026thinsp;=\u0026thinsp;348)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNausea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVomiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAbdominal pain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePolyuria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePolydipsia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDM foot ulcer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePyelonephritis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLength of stay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShort\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLong\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eFrequency of rebound ketone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOne times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTwo and above times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAdmitted ketone status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHypoglycemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e336\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eUrine glucose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot measured\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRandom Blood sugar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e445.5\u0026thinsp;\u0026plusmn;\u0026thinsp;102.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAdmission Ketone status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Treatment-related factors of DKA patients\u003c/h2\u003e\u003cp\u003eAmong the patients studied, 19.0% experienced treatment complications, while 81.0% did not, and discontinuation of the drug occurred in 15.8% compared to 84.2% who continued treatment. Regarding the glycaemic status at discharge, 33.9% had hyperglycaemia, 60.1% achieved euglycemia, and 6.0% had hypoglycaemia. Ceftriaxone was used in 7.5% of the patients, azithromycin was 4.0%, metronidazole 9.2% and other antibiotics, including vancomycin and amoxicillin, were administered to 10.3%. Enalapril, an ACE inhibitor, was used in 6.9%, while β-blockers, calcium channel blockers, and diuretics were prescribed in 13.2%. Fluid replacement with 0.9% normal saline was provided in 86.2% of the cases. All patients (100%) received an initial dose of regular insulin (RI), intravenously / intramuscularly, while 37.1% received RI combined with NPH insulin, 10.3% took metformin alone, 5.2% were treated with glibenclamide, 6.9% were on both metformin and glibenclamide, and 36.5% received NPH insulin alone (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTreatment related characteristics of patients with DKA in DMCSH, Ethiopia, 2025 (n\u0026thinsp;=\u0026thinsp;348)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTreatment complication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDrug discontinuation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e293\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eGlycaemia level at discharge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHyperglycemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEuglycemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e209\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHypoglycemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAntibiotics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCeftriaxone 1gm IV BID\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAzithromycin 500mg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMetronidazole 50mg IV BID\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACE inhibitors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003eEnalapril 5\u0026thinsp;mg per oral daily\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ-blockers, Calcium channel Blockers \u0026amp; Diuretics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFluid replacement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.9% normal saline solution\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eAnti-diabetic medications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRI 10 units IV and 10 units IM stat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e348\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRI\u0026thinsp;+\u0026thinsp;NPH 0.5\u0026thinsp;units/kg/day BID\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMetformin 500\u0026thinsp;mg PO BID\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlibenclamide 5\u0026thinsp;mg PO daily\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMetformin 500\u0026thinsp;mg PO BID\u0026thinsp;+\u0026thinsp;Glibenclamide 5\u0026thinsp;mg PO daily\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPH 0.5\u0026thinsp;units/kg/day BID\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eN.B: BID, bis in die or twice a day; KG, kilogram; NPH, neutral protamine hagedorn, it is intermediate-acting insulin; PO, per os or peroral; RI, regular insulin, it is short-acting insulin.\u003c/p\u003e\u003cp\u003eOthers*: Vancomycin, cloxacline, Amoxicillin, norfloxacillin, metformin, Augmentin\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Treatment of diabetic ketoacidosis\u003c/h2\u003e\u003cp\u003eThe results of this study showed that the prevalence of poor treatment outcomes among diabetic patients with DKA at Debre Markos General Specialized Hospital was 15.5% (95% CI: 11.5%, 19.3%). Among the 54 patients who experienced poor outcomes, 19 (5.5%) died, 11 (3.2%) left against medical advice, and 24 (6.9%) were referred to other institutions (Fig.\u0026nbsp;1).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e3.7 Factors associated with patients with diabetic ketoacidosis\u003c/h2\u003e\u003cp\u003eIn binary logistic regression analysis, variables with a p-value less than 0.25 including sex, residence, severe DKA, hypoglycaemia, comorbidities, precipitating factors, infections, discontinuation of drugs, high ketone levels, random blood sugar (RBS) and treatment complications were identified as candidate variables for multivariate logistic regression. In the multivariate analysis, seven variables were found to be significantly associated with poor outcomes from PD: severe PD, comorbidities, infections, discontinuation of the drug, elevated ketone levels, treatment complications, and length of hospital stay.\u003c/p\u003e\u003cp\u003ePatients who developed severe DKA were 1.48 times more likely to have poor DKA treatment outcomes compared to those with mild DKA status (AOR: 1.482, 95% CI: 1.324, 4.872). Similarly, the presence of comorbidities was associated with 1.8 times higher odds of poor outcomes compared to patients without comorbidities (AOR: 1.752, 95% CI: 1.215, 3.865). Patients who developed infections were also more likely to experience poor outcomes, with an AOR of 1.521 (95% CI: 1.362, 4.125). Regarding drug adherence, those who discontinued their prescribed diabetes medication were 2.12 times more likely to have poor treatment outcomes compared to those who continued their medication (AOR: 2.115, 95% CI: 1.245, 3.865). Treatment complications increased the likelihood of poor outcomes by 1.4 times compared to patients without complications (AOR: 1.356, 95% CI: 1.253, 4.125). Furthermore, patients with a ketone level\u0026thinsp;\u0026lt;\u0026thinsp;3 at admission had a 21.3% higher risk of poor outcomes compared to those with levels\u0026thinsp;\u0026lt;\u0026thinsp;3 (AOR: 1.213, 95% CI: 1.052, 2.876). Finally, a hospital stay of 5 days or less was associated with a 1.3-fold increase in the odds of poor outcomes compared to stays longer than 5 days (AOR: 1.29, 95% CI: 1.022, 3.254) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of Bivariable and Multivariable Logistic Regression Analyses of Factors Associated with Treatment Outcomes among DKA Patients at DMCSH, Northwest Ethiopia.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTreatment outcome of DKA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCOR\u003c/p\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAOR\u003c/p\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.705 (0.37, 1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.851(0.925, 4.124)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eResidence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.152 (0.611, 2.168)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.845(0.725, 3.253)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eSeverity of DKA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.776(0.345, 2.747)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.923( 0.914, 2.912)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.422(1.150, 4.497)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.482(1.324, 4.872)**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHypoglycemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.137 (0.551, 2.348)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.25(0.864, 3.231)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eComorbidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.148 (0.918, 3.153)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.752(1.215, 3.865)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePrecipitate factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.250(0.703, 2.323)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.212 (0.821, 3.253)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eInfection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.633( 1.235, 3.521)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.521(1.362, 4.125)**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDrug discontinuation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.902 (0.941, 3.847)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.115(1.245, 3.865)**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eKetone status at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.122(0.924, 2.020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.213(1.052, 2.876)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRBS in mg/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.381 (0.72, 2.625)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.923( 0.876, 2.956)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTreatment complication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.270 (0.927, 2.573)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.356(1.253, 4.125)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLength of Stay in hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;5 days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.182 (0.83, 5.330)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.29 (1.022, 3.254) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;5days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: 1: reference, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study found that the prevalence of poor treatment outcomes among diabetic patients with diabetic ketoacidosis (DKA) at the Debre Markos comprehensive specialised hospital was 15.5% (95% CI: 11.5%, 19.3%). Among those with poor outcomes, 5.5% died, 3.2% left without medical advice, and 6.9% were referred to other institutions. This finding aligns with similar research carried out in Ethiopia (12%) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Kenya (17.2%) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], Nigeria (16 %) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], Zabia16.66 %[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and Malayia 17.6 %[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, theprevalence observed in Ethiopia is significantly lower than that reported in other countries, such as, Kenya (29.8 %) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], Cameroon (21. %)[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These findings maydiffer due to several factors, such as variations in clinical presentation, the effectiveness of DKA detection and management, the prevalence of precipitating factors, and the capacity to address complications in various healthcare settings. It is important to note that the outcomes remain higher than those reported in some other regions with a well-established medical infrastructure. For example, studies conducted in Thailand (4.3 %)[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and Saudi Arabia (1.83 ) reported significantly lowe DKA-related mortality rates. Furthermore, in treatment-experienced facilities in Asia, Europe, and the Americas, a 5 % mortality rate for DKA has ben documented [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These findings suggest that poor outcomes remain a significant concern in the management of DKA within low-resource settings, although rates can vary depending on the population and the health facility.\u003c/p\u003e\u003cp\u003eAmong the 54 patients with poor treatment results, 19 (5.5%) died, 11 (3.2%) left against medical advice, and 24 (6.9%) were referred to other institutions. The mortality rate observed in this study is comparable to findings in Lusaka, Zambia [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], where the mortality rate in patients with DKA was 7.5 %, ut lower than the 9% mortality rate reported in a large U.S. cohort study [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The discrepancy in mortality rates could be attributed to factors such as differences in healthcare infrastructure, early intervention capabilities and patient management protocols.\u003c/p\u003e\u003cp\u003eOne of the significant findings of this study was that patients with severe DKA had significantly higher odds of poor treatment outcomes compared to those with mild DKA. This is consistent with existing literature in Debretabour[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and Saudi Arabia [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]which consistently shows that severe DKA is associated with worse outcomes, and also reported that severe DKA, defined by higher blood glucose and ketone levels, correlates with increased mortality and morbidity rates. The severity of DKA often reflects a delayed diagnosis and inadequate treatment, factors that can contribute to worsened prognosis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThe presence of comorbidities was another strong predictor of poor treatment outcomes, with patients having 1.8 times higher odds of poor outcomes compared to those without comorbidities. This aligns with findings from [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] who demonstrated that comorbid conditions such as hypertension, cardiovascular disease, and kidney dysfunction exacerbate the course of DKA and negatively impact patient recovery.\u003c/p\u003e\u003cp\u003eIn addition, infections were found to be significantly associated with poor outcomes in this study, reinforcing findings from [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]where infection was a key factor contributing to DKA-related complications and mortality. Residing in a developing country where hygiene is a major concern may contribute to an increased risk of urinary tract infections (UTI) in people with diabetes mellitus (DM).\u003c/p\u003e\u003cp\u003eThe study also identified discontinuation of drugs as a major risk factor for poor outcomes, with patients who discontinued their prescribed diabetes medications being 2.12 times more likely to experience poor treatment outcomes. This is consistent with the [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] guidelines, which highlight medication adherence as a crucial factor in preventing episodes of DKA and improving the prognosis of the patient. Patients who do not adhere to treatment protocols often have inadequate glycaemic control, increasing the risk of metabolic derangements such as DKA.\u003c/p\u003e\u003cp\u003eFurthermore, treatment complications significantly increased the odds of poor DKA treatment outcomes, which is consistent with findings from [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], where complications such as electrolyte imbalances and fluid overload were associated with worse patient outcomes.\u003c/p\u003e\u003cp\u003eAnother important factor positively significant with the poor outcome of DKA treatment in patients with DKA was ketone levels\u0026thinsp;\u0026lt;\u0026thinsp;3 at admission with a 21.3% increased risk of poor outcomes, which aligns with previous studies[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] that demonstrate that high ketone levels correlate with severe metabolic acidosis and poorer recovery in patients with DKA.\u003c/p\u003e\u003cp\u003eLastly, the length of hospital stay also played a role in treatment outcomes. Patients with a shorter hospital stay (5 days) were found to have 1.3 times higher odds of poor outcomes compared to those with longer stays. This finding might seem counterintuitive with support of[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] but it could reflect the complexity of cases that require longer management and the potential for quicker discharges in less complicated cases. However, it also suggests the importance of post-discharge care and follow-up to ensure patient stability after DKA treatment.\u003c/p\u003e\u003cp\u003eThe strength of this study offers valuable empirical evidence on the prevalence and associated factors of poor treatment outcomes among DKA patients in a real-world hospital setting in northwest Ethiopia, addressing a significant gap in regional data. The application of both bivariable and multivariable logistic regression analyses allowed the control of potential confounders and facilitated the identification of independent predictors. In particular, the study highlights several clinically important risk factors including severe DKA, comorbidities, infections, discontinuation of treatment, elevated ketone levels, and treatment complications that can support the development of targeted interventions and improve hospital management strategies for patients with DKA.\u003c/p\u003e\u003cp\u003eHowever, the study has several limitations. Being a cross-sectional study in nature, it relied on existing medical records, which may have been incomplete or inconsistently documented, introducing the risk of information bias. Additionally, the study was conducted in a single comprehensive hospital, which may limit the generalizability of the findings to broader populations or different healthcare settings. Furthermore, certain potentially influential variables such as socioeconomic status, educational background, and long-term follow-up outcomes were not assessed, which could have provided a more comprehensive analysis. Finally, the classification of poor outcomes included heterogeneous categories (death, referral, and leave without medical advice), which may vary in clinical severity and underlying causes, but were analysed as a single group.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study revealed that the prevalence of the poor DKA treatment outcomes among diabetic patients at Debre Markos' comprehensive specialized hospital was high. The findings of this study underscore several critical factors that influence treatment outcomes in patients with DKA, including severity of the condition, comorbidities, infections, drug adherence, complications during treatment, high levels of ketones (3\u0026thinsp;\u0026lt;\u0026thinsp;3) at admission, and short hospital stay (5 days). Develop strategies to strengthen early detection, manage comorbidities and infections, ensure proper drug adherence, and effectively monitor complications. Improve hospital protocols, patient education, and structured follow-up to improve treatment outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eCOR\u003c/strong\u003e: Crude Odds Ratio; \u003cstrong\u003eDKA\u003c/strong\u003e: Diabetic Ketoacidosis; \u003cstrong\u003eDMCSH\u003c/strong\u003e: Debre Markos Comprehensive Specialized Hospital; \u003cstrong\u003eFBG\u003c/strong\u003e: Fasting Blood Glucose Level; \u003cstrong\u003eHHS\u003c/strong\u003e: Hyperglycaemic Hyperosmolar State; \u003cstrong\u003eID\u003c/strong\u003eF: International Diabetes Federation; \u003cstrong\u003eNPH\u003c/strong\u003e: Neutral Protamine Hagedorn Insulin.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe current study included human respondents because this ethical clearance was obtained from\u0026nbsp;the\u0026nbsp;Research Ethics Review Committee, Department of Medicine and Health Sciences, Debre Markos University with reference number RCSTTD/522/01/17. A permission letter was written by the Amhara Public Health Institute and a cooperation letter was obtained from Debre Markos comprehensive specialized hospital to collect the data. To keep confidentiality, names and unique card numbers were not included in the data collection tool. After entering to the computer, the data were locked by password and was not disclosed to any person other than principal investigator. All information collected from the patient chart was kept strictly confidential.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials.\u003c/h2\u003e\n\u003cp\u003eThe primary data contributed in this study were included in the article; Any clarity issues can be directly communicated with the corresponding author.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;Funding\u003c/h2\u003e\n\u003cp\u003eThere is no any fund.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; Contributions\u003c/h2\u003e\n\u003cp\u003eMBY: Writing\u0026mdash;original draft; writing\u0026mdash;review \u0026amp; editing; conception; investigation; software; data curation; methodology; formal analysis; resources; and visualization.\u003c/p\u003e\n\u003cp\u003eFL: Writing\u0026mdash;original draft; writing\u0026mdash;review \u0026amp; editing; conceptualization; investigation; data curation; methodology; supervision; project administration; funding acquisition; resources; and visualization.\u003c/p\u003e\n\u003cp\u003eFM: Writing\u0026mdash;original draft; writing\u0026mdash;review \u0026amp; editing; investigation; data curation; supervision; validation; and visualization.\u003c/p\u003e\n\u003cp\u003eMT: Writing\u0026mdash;original draft; writing\u0026mdash;review \u0026amp; editing; investigation; methodology; supervision; validation; and visualization. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe authors sincerely thank Debre Markos Comprehensive Specialized Hospital for facilitating data collection and providing a dedicated space. We also appreciate the efforts of our data collectors and supervisors for their dedication and hard work.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAssociation AD. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37(Supplement_1):S81\u0026ndash;90. \u003c/li\u003e\n\u003cli\u003eUmpierrez G, Korytkowski M. Diabetic emergencies\u0026mdash;ketoacidosis, hyperglycaemic hyperosmolar state and hypoglycaemia. Nat Rev Endocrinol. 2016;12(4):222\u0026ndash;32. \u003c/li\u003e\n\u003cli\u003eSun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045., 2022, 183. DOI: https://doi org/101016/j diabres. 2021;109119. \u003c/li\u003e\n\u003cli\u003eLee SE, Kim KA, Son KJ, Song SO, Park KH, Park SH, et al. Trends and risk factors in severe hypoglycemia among individuals with type 2 diabetes in Korea. Diabetes Res Clin Pract. 2021;178:108946. \u003c/li\u003e\n\u003cli\u003eBerhe KK. Diabetes-Related Distress and Associated Factors among People with Type 2 Diabetes in Mekelle City, Tigray Region, Ethiopia. 2023; \u003c/li\u003e\n\u003cli\u003eOrganization WH. Guidelines for the prevention, management and care of diabetes mellitus. 2006. \u003c/li\u003e\n\u003cli\u003eUsher-Smith JA, Thompson MJ, Sharp SJ, Walter FM. Factors associated with the presence of diabetic ketoacidosis at diagnosis of diabetes in children and young adults: a systematic review. Bmj. 2011;343. \u003c/li\u003e\n\u003cli\u003eAlotaibi A, Aldoukhi A, Albdah B, Alonazi JA, Alseraya AS, Alrasheed N. Diabetic ketoacidosis treatment outcome and associated factors among adult patients admitted to the emergency department and medical wards at King Abdulaziz Medical City, Riyadh, Saudi Arabia. Cureus. 2020;12(8). \u003c/li\u003e\n\u003cli\u003eUsman A, Sulaiman SAS, Khan AH, Adnan AS. Profiles of diabetic ketoacidosis in multiethnic diabetic population of Malaysia. Tropical Journal of Pharmaceutical Research. 2015;14(1):179\u0026ndash;85. \u003c/li\u003e\n\u003cli\u003eOtieno CF, Kayima JK, Omonge EO, Oyoo GO. Diabetic ketoacidosis: risk factors, mechanisms and management strategies in sub-Saharan Africa: a review. East Afr Med J. 2005;82(12). \u003c/li\u003e\n\u003cli\u003eSherif FM. Clinical profile of Libyan patients admitted with diabetic ketoacidosis. 2024; \u003c/li\u003e\n\u003cli\u003eMahesh MG, ShIvaSwaMy RPr, ChandRa BS, Syed S. The study of different clinical pattern of diabetic ketoacidosis and common precipitating events and independent mortality factors. J Clin Diagn Res. 2017;11(4):OC42. \u003c/li\u003e\n\u003cli\u003eOtieno CF, Kayima JK, Mbugua PK, Amayo AA, Mcligeyo SO. Prognostic factors in patients hospitalised with diabetic ketoacidosis at Kenyatta National Hospital, Nairobi. East Afr Med J. 2010;87(2):67\u0026ndash;74. \u003c/li\u003e\n\u003cli\u003eMitiku Yigazu D, Lema M, Bekele F, Tesfaye Daka D, Samuel D, Addisu N. Diabetic ketoacidosis treatment outcomes and its associated factors among adult patients with diabetes mellitus admitted to public hospitals in Nekemte Town, Ethiopia: a cross-sectional study. Frontiers in Clinical Diabetes and Healthcare. 2024;5. \u003c/li\u003e\n\u003cli\u003eTaye GM, Bacha AJ, Taye FA, Bule MH, Tefera GM. Diabetic ketoacidosis management and treatment outcome at medical ward of Shashemene Referral Hospital, Ethiopia: a retrospective study. Clin Med Insights Endocrinol Diabetes. 2021;14:11795514211004956. \u003c/li\u003e\n\u003cli\u003eAbela AG, Magri CJ, Debono M, Calleja N, Vassallo J, Azzopardi J. An audit of the management of diabetic ketoacidosis at St Luke\u0026rsquo;s Hospital. 2008; \u003c/li\u003e\n\u003cli\u003eKassaye DA, Girsha WD, Guto GJ, Deybasso HA. Diabetic ketoacidosis treatment outcome and associated factors among adult patients admitted to medical wards of Adama Hospital Medical College, Oromia, Ethiopia. Am J Intern Med. 2018;6(2):34\u0026ndash;42. \u003c/li\u003e\n\u003cli\u003eDesse TA, Eshetie TC, Gudina EK. Predictors and treatment outcome of hyperglycemic emergencies at Jimma University Specialized Hospital, southwest Ethiopia. BMC Res Notes. 2015;8:1\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eAsfaw TP, Binega MG, Asmamaw MA, Molla TB. Treatment outcome and predictors of mortality among adult diabetic patients admitted with hyperglycemic crises at hiwot fana comprehensive specialized university hospital, eastern Ethiopia. East African Journal of Health and Biomedical Sciences. 2021;5(2):45\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eMekonnen GA, Gelaye KA, Gebreyohannes EA, Abegaz TM. Treatment outcomes of diabetic ketoacidosis among diabetes patients in Ethiopia. Hospital-based study. PLoS One. 2022;17(4):e0264626. \u003c/li\u003e\n\u003cli\u003eBishu KG, Jenkins C, Yebyo HG, Atsbha M, Wubayehu T, Gebregziabher M. Diabetes in Ethiopia: a systematic review of prevalence, risk factors, complications, and cost. Obes Med. 2019;15:100132. \u003c/li\u003e\n\u003cli\u003eAdem A, Demis T, Feleke Y. Trend of diabetic admissions in Tikur Anbessa and St. Paul\u0026rsquo;s University Teaching Hospitals from January 2005-December 2009, Addis Ababa, Ethiopia. Ethiop Med J. 2011;49(3):231\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eBedaso A, Oltaye Z, Geja E, Ayalew M. Diabetic ketoacidosis among adult patients with diabetes mellitus admitted to emergency unit of Hawassa university comprehensive specialized hospital. BMC Res Notes. 2019;12:1\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eDerse TK, Haile MT, Chamiso TM. Outcome of Diabetic Keto Acidosis Treatment and Associated Factors Among Adult Patients Admitted to Emergency and Medical Wards at St. Paul\u0026rsquo;s Hospital, Addis Ababa Ethiopia, 2023: A Cross-Sectional Study. Diabetes, Metabolic Syndrome and Obesity. 2023;3471\u0026ndash;80. \u003c/li\u003e\n\u003cli\u003eEdo AE. Clinical profile and outcomes of adult patients with hyperglycemic emergencies managed at a tertiary care hospital in Nigeria. Nigerian Medical Journal. 2012;53(3):121\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eKakusa M, Kamanga B, Ngalamika O, Nyirenda S. Comatose and noncomatose adult diabetic ketoacidosis patients at the University Teaching Hospital, Zambia: Clinical profiles, risk factors, and mortality outcomes. Indian J Endocrinol Metab. 2016;20(2):199\u0026ndash;205. \u003c/li\u003e\n\u003cli\u003eMbugua PK, Otieno CF, Kayima JK, Amayo AA, McLigeyo SO. Diabetic ketoacidosis: clinical presentation and precipitating factors at Kenyatta National Hospital, Nairobi. East Afr Med J. 2005;82(12). \u003c/li\u003e\n\u003cli\u003eNkoke C, Bain LE, Makoge C, Teuwafeu D, Mapina A, Nkouonlack C, et al. Profile and outcomes of patients admitted with hyperglycemic emergencies in the Buea Regional Hospital in Cameroon. Pan African medical journal. 2021;39(1). \u003c/li\u003e\n\u003cli\u003eThewjitcharoen Y, Plianpan P, Chotjirat A, Nakasatien S, Chotwanvirat P, Wanothayaroj E, et al. Clinical characteristics and outcomes of care in adult patients with diabetic ketoacidosis: a retrospective study from a tertiary diabetes center in Thailand. J Clin Transl Endocrinol. 2019;16:100188. \u003c/li\u003e\n\u003cli\u003eAssociation AD. Standards of medical care in diabetes\u0026mdash;2015 abridged for primary care providers. Clin Diabetes. 2015;33(2):97. \u003c/li\u003e\n\u003cli\u003eAssociation AD. Diabetes care in the hospital: standards of medical care in diabetes\u0026mdash;2020. Diabetes Care. 2020;43(Supplement_1):S193\u0026ndash;202. \u003c/li\u003e\n\u003cli\u003eYigazu DM, Lema M, Bekele F, Daka DT, Samuel D, Addisu N. Diabetic ketoacidosis treatment outcomes and its associated factors among adult patients with diabetes mellitus admitted to public hospitals in Nekemte Town, Ethiopia: A Cross-sectional study. Frontiers in Clinical Diabetes and Healthcare. 5:1446543. \u003c/li\u003e\n\u003cli\u003eHirobata T, Inaba H, Kaido Y, Kosugi D, Itoh S, Matsuoka T, et al. Serum ketone body measurement in patients with diabetic ketoacidosis. Diabetol Int. 2022;13(4):624\u0026ndash;30. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Diabetic keto-acidosis, poor treatment outcome, associated factors, hospital, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-7114400/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7114400/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDiabetic ketoacidosis emergencies are serious acute complications of diabetes mellitus, and their health and economic impacts have been increasing among adult diabetic patients. Despite the growing burden of emergencies from diabetic ketoacidosis among adults with diabetes, its outcome and predictors of treatment have not been well studied in Ethiopia.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo assess the prevalence of poor treatment outcome of diabetic ketoacidosis and associated factors among adult diabetic patients admitted to the Debre Markos comprehensive specialized hospital, northwest Ethiopia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA hospital-based cross-sectional study was conducted at Debre Markos comprehensive specialized hospital from April 8, 2025 to April 28, 2025. A total of 360 patients with diabetic DKA who were admitted from August 28, 2019 to September 30, 2024 participated in the study. A simple random sampling technique was used to select study participants. Data were extracted using a pre-tested data collection tool adapted from different literatures. The data were entered into epi-data version 4.6.0 and exported to SPSS version 26 for analysis. Both bivariable and multivariable binary logistic regression analysis were done. Statistical significance was declared at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 with an odds ratio of 95% confidence interval.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe prevalence of poor treatment outcomes was 15.5% (95%, CI: 11.5%, 19.3%). Factors, such as severe DKA (AOR: 1.482, 95% CI: 1.324, 4.872), the presence of comorbidities (AOR: 1.752, 95% CI: 1.215, 3.865), and underlying infections (95% CI: 1.362, 4.125), discontinuation of drugs (AOR: 2.115, 95% CI: 1.245, 3.865), treatment complications (AOR: 1.356, 95% CI: 1.253, 4.125), ketone levels\u0026thinsp;\u0026gt;\u0026thinsp;3 (AOR: 1.213, 95% CI: 1.052, 2.876), and hospital stays of less than five days (AOR: 1.29, 95% CI: 1.022, 3.254) were also significant predictors of poor outcomes in patients with DKA.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study found that a high number of patients with DKA in the Debre Markos comprehensive specialized hospital experienced poor treatment outcomes. Significant factors included severe DKA, comorbidities, infections, drug discontinuation, treatment complications, high ketone levels and short hospital stays. To improve treatment outcomes, early identification and proactive management of high-risk DKA patients, particularly those who present with severe illness, comorbidity conditions, or infections, shall be prioritized.\u003c/p\u003e","manuscriptTitle":"Prevalence of treatment outcomes and associated factors of diabetic ketoacidosis among adult diabetic patients admitted to Debre Markos comprehensive specialized hospital, Northwest Ethiopia: A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 05:56:06","doi":"10.21203/rs.3.rs-7114400/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-01T00:53:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-27T14:13:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-26T02:45:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269812143677886252865737366048097852822","date":"2025-07-18T12:52:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235765422407196346441273146340700004237","date":"2025-07-17T09:33:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T10:50:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-16T07:06:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-15T05:38:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2025-07-13T15:55:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4a2c5380-455e-494a-aaa7-e1e6f1ce666c","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:11:53+00:00","versionOfRecord":{"articleIdentity":"rs-7114400","link":"https://doi.org/10.1186/s40001-025-03593-1","journal":{"identity":"european-journal-of-medical-research","isVorOnly":false,"title":"European Journal of Medical Research"},"publishedOn":"2025-12-04 15:57:21","publishedOnDateReadable":"December 4th, 2025"},"versionCreatedAt":"2025-07-23 05:56:06","video":"","vorDoi":"10.1186/s40001-025-03593-1","vorDoiUrl":"https://doi.org/10.1186/s40001-025-03593-1","workflowStages":[]},"version":"v1","identity":"rs-7114400","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7114400","identity":"rs-7114400","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}