Mortality and Associated Factors in Critically Ill COVID-19 Patients: A Retrospective Cohort Study

Mortality and Associated Factors in Critically Ill COVID-19 Patients: A Retrospective Cohort 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 Mortality and Associated Factors in Critically Ill COVID-19 Patients: A Retrospective Cohort Study Hülya Kahraman Şah, Kamil Deveci, Ülkü Arslan, Naci Neccar, Onur Çetinkaya, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7362857/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Structured Abstract Background The COVID-19 pandemic has led to a substantial increase in intensive care unit (ICU) admissions worldwide, with high mortality rates among critically ill patients. Identifying mortality rates and associated factors is crucial for guiding clinical management and resource allocation. Methods This retrospective, single-center study included 410 adult patients with confirmed COVID-19 admitted to the ICU between March 2020 and March 2021 at a tertiary care hospital in Antalya, Türkiye. Demographic characteristics, comorbidities, clinical interventions, laboratory parameters, and outcomes were recorded. Survivors and non-survivors were compared using the Mann–Whitney U, Chi-square, and Fisher’s exact tests. Cox regression analysis was performed to identify independent predictors of mortality. Results The overall ICU mortality rate was 48.3%. Non-survivors were older (median age: 70 vs. 66 years, p < 0.001), had higher BMI (25.9 vs. 24.5 kg/m², p < 0.001), and longer ICU stays (6 vs. 4 days, p = 0.001). They more frequently required invasive mechanical ventilation (87.8% vs. 23.1%, p < 0.001), vasopressor therapy (82.7% vs. 26.9%, p < 0.001), and renal replacement therapy (19.8% vs. 7.5%, p < 0.001). Laboratory findings in non-survivors showed higher ferritin (680 vs. 412.6 ng/mL, p = 0.001), LDH (486 vs. 365 U/L, p < 0.001), fibrinogen (611.5 vs. 517 mg/dL, p = 0.023), NLR (15 vs. 11, p < 0.001), and lactate (1.7 vs. 1.4 mmol/L, p < 0.001), as well as lower PaO₂/FiO₂ ratio (104 vs. 164.8, p < 0.001). Multivariate Cox regression identified invasive mechanical ventilation (HR 5.15, 95% CI 3.25–8.15, p < 0.001), malignancy (HR 1.44, 95% CI 1.04–2.01, p = 0.031), and APACHE II score (HR 1.03, 95% CI 1.01–1.05, p = 0.001) as independent predictors of mortality. Conclusions ICU mortality among COVID-19 patients remains high. Advanced age, obesity, high APACHE II score, mechanical ventilation, vasopressor use, and certain comorbidities significantly increase mortality risk. Early identification of high-risk patients and targeted interventions may improve outcomes. COVID-19 intensive care unit mortality risk factors APACHE II mechanical ventilation comorbidity Background Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, China in December 2019 and rapidly spread worldwide, becoming a global pandemic (1, 2). According to the World Health Organization (WHO), as of March 2022, more than 450 million confirmed cases and over 6 million deaths have been reported globally. As of December 29, 2021, COVID–19 had caused 476,374,234 cases and 6,108,976 deaths worldwide (3). In Türkiye, the total number of cases was reported as 14,513,774, and the total number of deaths was 96,217 (4). The clinical spectrum of COVID-19 ranges from asymptomatic infection to severe pneumonia, acute respiratory distress syndrome (ARDS), multi-organ failure, and death. A significant proportion of critically ill patients require admission to intensive care units (ICUs), where mortality rates have been reported to vary between 30% and 80%, depending on disease severity, comorbidities, and available healthcare resources. Due to the rapid global spread of the COVID-19 virus and the resulting high case numbers, a significant proportion of patients required respiratory support and were classified as critically ill, creating an unprecedented demand on intensive care units (ICUs) worldwide (5, 6). This burden on ICU capacities globally has led to an increase in both the number of patients admitted to ICUs and the number of deaths occurring in ICUs due to COVID-19 (7). Several factors have been associated with poor prognosis in ICU patients with COVID-19, including advanced age, male sex, obesity, and comorbidities such as hypertension, diabetes, cardiovascular disease, and chronic lung disease. Additionally, higher severity scores such as the Acute Physiology and Chronic Health Evaluation II (APACHE II), invasive mechanical ventilation (IMV), vasopressor use, and acute kidney injury (AKI) have been linked to increased mortality. In Türkiye, ICU admission rates for COVID-19 have been substantial, yet data regarding mortality rates and prognostic factors in this population remain limited. Identifying these factors is critical for improving patient outcomes and optimizing resource allocation during pandemic surges. The aim of this study was to investigate the general characteristics, mortality rates, and factors associated with mortality in adult patients with COVID-19 admitted to the ICU in a tertiary hospital in Antalya, Türkiye. Methods Study design and setting This retrospective, single-center observational study was conducted at the Akdeniz University Faculty of Medicine Hospital, a tertiary care referral center in Antalya, Türkiye. The study period covered ICU admissions between March 1, 2020, and March 1, 2021. Participants A total of 410 adult patients (≥ 18 years old) with confirmed COVID-19 pneumonia were included. The diagnosis was established based on clinical presentation, radiological findings compatible with COVID-19 pneumonia on chest computed tomography (CT), and/or a positive reverse transcription–polymerase chain reaction (RT-PCR) test for SARS-CoV-2. Patients with incomplete medical records or ICU stays shorter than 24 hours were excluded. Data collection Data were obtained from electronic medical records and ICU follow-up charts. Variables collected included: Demographic characteristics: age, sex, body mass index (BMI), smoking status Comorbidities: hypertension, diabetes mellitus, ischemic heart disease, chronic lung disease, chronic kidney disease, rheumatologic disease, cerebrovascular accident, malignancy, organ transplantation history Clinical interventions: mechanical ventilation (invasive and non-invasive), vasopressor therapy, prone positioning, extracorporeal membrane oxygenation (ECMO), renal replacement therapy (RRT), tracheostomy, decannulation Laboratory parameters at ICU admission: complete blood count, lactate dehydrogenase (LDH), ferritin, fibrinogen, D-dimer, lactate, neutrophil-to-lymphocyte ratio (NLR), and PaO₂/FiO₂ ratio Outcomes: ICU length of stay, hospital length of stay, survival status Definitions Acute kidney injury (AKI): Defined according to Kidney Disease Improving Global Outcomes (KDIGO) criteria and staged accordingly. Body mass index (BMI): Calculated as weight in kilograms divided by the square of height in meters (kg/m²). Statistical analysis Statistical analysis was performed using SPSS version 15.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were expressed as median (interquartile range, IQR) and compared using the Mann–Whitney U test. Categorical variables were presented as frequencies and percentages, and compared using Chi-square or Fisher’s exact tests as appropriate. Cox proportional hazards regression analysis was performed to identify independent predictors of mortality. Variables with p < 0.05 in univariate analysis were entered into the multivariate model. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated. A p-value < 0.05 was considered statistically significant. Ethical approval The study was approved by the Akdeniz University Ethics Committee (Decision No: KAEK-282). As this was a retrospective study, the requirement for informed consent was waived.Results This study was conducted at Akdeniz University Faculty of Medicine Hospital and included 410 patients treated in the intensive care unit (ICU) for COVID-19 between March 11, 2020, and March 11, 2021. Of the 410 patients followed in our study, 212 (51.7%) survived, while 198 (48.3%) died. The mean hospital length of stay was 17.2 ± 17.3 days, with a median stay of 13 days (range: 1–156 days). When survival status was evaluated according to sex and smoking history, no statistically significant differences were found (p = 0.952 and p = 0.482, respectively). However, significant differences were observed for age, body mass index (BMI), total hospital stay, and COVID-19 PCR (polymerase chain reaction) results (all p < 0.001). Analysis of ICU length of stay also revealed statistically significant differences between survivors and non-survivors. No significant differences were found for comorbidities except for cerebrovascular accident (CVA), which was significantly more frequent among non-survivors (p = 0.001 and p = 0.029, respectively) (Table 1). When patients were evaluated according to survival status for the presence of co-infections, statistically significant differences were observed for having any co-infection, respiratory tract infection, urinary tract infection, catheter-tip infection, and positive blood culture (p < 0.001, p < 0.001, p = 0.002, p = 0.028, and p < 0.001, respectively). Regarding oxygen therapy, statistically significant differences were found for receiving any form of oxygen therapy, use of invasive mechanical ventilation (IMV) or non-invasive mechanical ventilation (NIMV), and PaO₂/FiO₂ ratio (all p < 0.001). However, there were no significant differences for extracorporeal membrane oxygenation (ECMO) use or mechanical ventilation duration (p = 0.071 and p = 0.255, respectively). Statistically significant differences were also found in prone positioning, tracheostomy, and decannulation procedures (p = 0.045, p = 0.047, and p = 0.031, respectively). Evaluation of vasopressor and renal replacement therapy (RRT) use revealed statistically significant differences between survivors and non-survivors (both p < 0.001). Significant differences were also observed for acute kidney injury (AKI) presence and AKI staging (p < 0.001), while pneumothorax showed no significant difference between groups (p = 0.242). When laboratory parameters were compared between survivors and non-survivors, ferritin, LDH, fibrinogen, neutrophil-to-lymphocyte ratio (NLR), and lactate levels were significantly different (p = 0.001, p < 0.001, p = 0.023, p < 0.001, and p < 0.001, respectively), whereas no significant difference was observed for D-dimer levels (p = 0.065) (Table 2). In the univariate Cox regression analysis of COVID-19 patients treated in the ICU, the variable with the greatest impact on hazard ratio (mortality risk) was the use of invasive mechanical ventilation (IMV) (HR: 6.47, p < 0.001). Other factors affecting the hazard ratio were, in order of magnitude: vasopressor therapy (HR: 4.80, p 25 kg/m² (HR: 1.57, p = 0.002), presence of co-infection (HR: 1.54, p = 0.003), age >65 years (HR: 1.48, p = 0.010), use of non-invasive mechanical ventilation (NIMV) (HR: 1.45, p = 0.012), lactate level (HR: 1.09, p = 0.002), APACHE II score (HR: 1.06, p < 0.001), and PaO₂/FiO₂ ratio (HR: 0.997, p = 0.001). In the multivariate Cox regression analysis, the variable with the greatest impact on hazard ratio was again the use of IMV (HR: 5.15, p < 0.001). Other significant factors in the multivariate model were the presence of malignancy (HR: 1.44, p = 0.031) and APACHE II score (HR: 1.03, p = 0.001). Thus, in our multivariate Cox regression analysis, COVID-19 patients on IMV had a 5.15-fold higher risk of death, those with malignancy had a 1.44-fold higher risk, and each one-point increase in APACHE II score increased mortality risk by 1.03 times (Table 3). Discussion In our study, 410 patients treated in the intensive care unit (ICU) due to COVID-19 were analyzed. A total of 48.3% of our patients died while in the ICU. The mean ICU length of stay was 17 days. A meta-analysis conducted in June 2020, which evaluated 24 studies on ICU mortality, reported an overall mortality rate of 41.6% (8). Although ICU–COVID-19 mortality rates vary across countries in the literature, COVID-19 continues to present with high mortality in the ICU setting (9,10). It has been suggested that differences in ICU admission criteria between countries may account for these variations. However, comparing the early pandemic period with the present, ICU mortality rates have not changed significantly, likely because only critically ill patients are admitted to the ICU at all stages of the pandemic. In our study, non-survivors more frequently received vasopressors, invasive mechanical ventilation (IMV), non-invasive mechanical ventilation (NIMV), and high-flow oxygen therapy, and prone positioning was also used more frequently in this group. Notably, NIMV use increased mortality risk by 1.45 times, vasopressor therapy by 4.8 times, and IMV by 6.47 times. Additionally, the PaO₂/FiO₂ ratio was significantly lower in non-survivors. Extracorporeal membrane oxygenation (ECMO) use was not associated with mortality. A study from Mexico reported that IMV use was significantly less frequent in survivors, and multivariate Cox regression showed that IMV increased the risk of death by 3.31 times (11). In an American study, PaO₂/FiO₂ ratios were higher among survivors, while vasopressor and renal replacement therapy use was lower and statistically significant; ECMO use, as in our study, was not significant (12). In Sweden, an analysis of all ICU COVID-19 patients admitted up to May 2020 found that IMV use and prone positioning were significantly more common among non-survivors, while PaO₂/FiO₂ ratios and high-flow oxygen use were higher in survivors; NIMV showed no significant difference (13). COVID-19 mainly presents with pneumonia and ARDS-like hypoxemic respiratory failure, which is a primary cause of mortality and morbidity. Therefore, respiratory support forms the cornerstone of ICU care, but treatment algorithms vary by patient and country. Since IMV, NIMV, ECMO use, low PaO₂/FiO₂ ratios, and vasopressor therapy are applied to already critically ill patients, our results are consistent with expectations. There was a statistically significant difference in APACHE II scores between survivors and non-survivors, with higher scores in the latter. In our Cox regression model, each one-point increase in the APACHE II score increased mortality risk by 1.03 times; IMV was associated with a 5.15-fold higher risk of death, and malignancy with a 1.44-fold higher risk. Similarly, a study from Wuhan demonstrated that the APACHE II score was an important predictor of mortality in both univariate and multivariate Cox regression analyses (14). In our study, mortality frequency did not differ by sex; however, older age and higher BMI were observed in non-survivors. The Cox regression model showed that age >65 years increased mortality risk by 1.48 times, and BMI >25 kg/m² increased risk by 1.57 times. An Italian multicenter study across 72 ICUs found higher mortality in older patients, particularly those aged ≥63 years (15). Ata et al. also reported that sex did not influence ICU mortality (16). In a Chicago-based study, obesity increased mortality risk by 1.7 times (17). Older age and elevated BMI are well-known risk factors for many diseases and are especially detrimental in the presence of comorbidities; our findings reinforce that this holds true for COVID-19. In our study, survivors had longer hospital stays overall, whereas non-survivors had significantly longer ICU stays. Khalid et al. reported longer hospital and ICU stays among non-survivors (18). We believe that earlier ICU admission of critically ill patients in our cohort may have influenced these results, which can be considered a success of healthcare delivery. Smoking did not affect mortality in our study, consistent with findings from a Czech study (19). However, some publications report increased mortality with smoking (20). The literature shows heterogeneous results regarding the relationship between smoking and COVID-19 severity, mortality, and morbidity. We found no statistically significant differences in mortality based on the presence of diabetes, hypertension, ischemic heart disease, chronic lung disease, chronic kidney disease, rheumatologic disease, or organ transplantation. However, cerebrovascular accident (CVA) was significantly more common among non-survivors. Mutair et al. similarly reported no significant association between most comorbidities and survival in ICU COVID-19 patients (21). While some studies indicate higher mortality in organ transplant recipients with severe COVID-19, results vary (22). The literature is mixed on whether chronic diseases and comorbidities influence mortality (23–25). In our study, the lack of patients with isolated single comorbidities may have influenced these findings. Co-infections were more common among non-survivors, and further analysis showed a 1.54-fold increased mortality risk in patients with co-infections. Respiratory and urinary tract infections were more frequent among non-survivors, and positive blood or catheter-tip cultures were also more common. A Spanish study reported that co-infections were rare on ICU admission but that ICU-acquired infections were more frequent, and any co-infection source was associated with higher mortality (26). Our results align with the literature on co-infections. Tracheostomy was more common among non-survivors, whereas decannulation occurred more frequently among survivors. The literature is divided on tracheostomy and decannulation outcomes. In general, only one-third of tracheostomized patients are decannulated, and mortality in this group is around 13.1% (27). Despite guideline-based recommendations, clinician experience plays a key role, likely explaining variability in results. Nasal oxygen therapy was more frequent among survivors; a study from India reported higher venturi mask and nasal oxygen use among survivors (28). Acute kidney injury (AKI), particularly stage 3, was more common in non-survivors. Compared to patients without AKI, mortality risk increased 1.72-fold in stage 1, 1.79-fold in stage 2, and 2.4-fold in stage 3 AKI. Renal replacement therapy was also more frequent among non-survivors. A study from Saudi Arabia likewise showed higher mortality among ICU COVID-19 patients with AKI (18). Multiple studies in the literature have shown an association between AKI and mortality (29). The pathophysiology of AKI in COVID-19 is thought to involve direct viral effects, local and systemic inflammatory responses, endothelial injury, microemboli, sepsis, and hypoxia (30). The coexistence of these factors in critically ill ICU patients may explain the high AKI-related mortality in our cohort. Ferritin, LDH, neutrophil-to-lymphocyte ratio (NLR), fibrinogen, and lactate levels were higher in non-survivors. Although D-dimer levels were also higher, the difference was not statistically significant. Coagulation factors were higher in survivors. In the Cox regression model, each unit increase in lactate increased mortality risk by 1.09 times. A study from Mexico City similarly found significant differences between survivors and non-survivors in LDH, ferritin, D-dimer, NLR, fibrinogen, and lactate, with lower median values in survivors (31). Increases in acute phase reactants are expected in severe disease. Lactate is an important blood gas parameter, rising before detectable changes in vital signs. NLR may also be useful in predicting mortality, as supported by multiple studies in the literature (32). Abbreviations AKI Acute Kidney Injury APACHE II Acute Physiology and Chronic Health Evaluation II BMI Body Mass Index CI Confidence Interval CVA Cerebrovascular Accident ECMO Extracorporeal Membrane Oxygenation HR Hazard Ratio ICU Intensive Care Unit IMV Invasive Mechanical Ventilation IQR Interquartile Range LDH Lactate Dehydrogenase NIMV Non-invasive Mechanical Ventilation NLR Neutrophil-to-Lymphocyte Ratio PaO₂/FiO₂ ratio Arterial Oxygen Partial Pressure to Fraction of Inspired Oxygen Ratio PCR Polymerase Chain Reaction RRT Renal Replacement Therapy SD Standard Deviation WHO World Health Organization Mortality and Associated Factors in Critically Ill COVID-19 Patients A Retrospective Cohort Study Declarations Ethics approval and consent to participate This study was approved by the Akdeniz University Ethics Committee (Research Code: KAEK-282; approval date: April 5, 2023). The committee determined there were no ethical objections to conducting the study. Informed consent was waived due to the retrospective nature of the study. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding No specific funding was received for this study. Authors’ contributions All authors contributed to study conception, design, data acquisition, statistical analysis, and interpretation. All authors read and approved the final manuscript. Acknowledgements We thank the ICU staff at Akdeniz University Faculty of Medicine Hospital for their dedication and service during the COVID-19 pandemic. References World Health Organization. Coronavirus disease (COVID-19) pandemic. Available from: https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov. Accessed 20 March 2022. 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COVID-19 Adult Patient Treatment Guideline. Available from: https://covid19.saglik.gov.tr/Eklenti/39061/0/covid-19rehberieriskinhastatedavisipdf.pdf. Accessed 20 March 2022. National Institutes of Health. COVID-19 treatment guidelines. Available from: https://www.covid19treatmentguidelines.nih.gov/. Accessed 20 March 2022. Tables Table 1 Evaluation of some descriptive characteristics and comorbidities of COVID-19 patients in the ICU, Antalya, 2022. Characteristics Total Survived Deceased p-value Gender, n (%) 0.952 Female 134 (32.7) 69 (32.5) 65 (32.8) Male 276 (67.3) 143 (67.5) 133 (67.2) Age (years), median (IQR) 67 (58–76) 66 (55.3–74) 70 (60–78) < 0.001 BMI, n = 403 25 (23–27.7) 24.5 (22.5–27) 25.9 (24–29) < 0.001 ICU length of stay (days) 5 (3–10) 4 (3–7) 6 (3–12.3) 0.001 Hospital length of stay (days) 13 (7–20.3) 14 (9–23.8) 10 (5–17) < 0.001 Smoking status, n = 317 0.482 Non-smoker 189 (59.6) 92 (56.4) 97 (63.0) Smoker 80 (25.2) 45 (27.6) 35 (22.7) Ex-smoker 48 (15.1) 26 (16.0) 22 (14.3) PCR positive, n (%) 215 (52.4) 91 (42.9) 124 (62.6) < 0.001 CT positive, n (%) 410 (100) 212 (100) 198 (100) – Comorbidities, n (%) Diabetes Mellitus 164 (40.0) 86 (40.6) 78 (39.4) 0.809 Hypertension 208 (50.7) 104 (49.1) 104 (52.5) 0.483 Ischemic heart disease 163 (39.8) 85 (40.1) 78 (39.4) 0.885 Chronic lung disease 100 (24.4) 51 (24.1) 49 (24.7) 0.871 Chronic kidney disease 63 (15.4) 36 (17.0) 27 (13.6) 0.348 Rheumatological disease 19 (4.6) 10 (4.7) 9 (4.5) 0.934 Cerebrovascular accident 42 (10.2) 15 (7.1) 27 (13.6) 0.029 Malignancy, n = 409 97 (23.7) 46 (21.8) 51 (25.8) 0.347 Organ transplant 15 (3.7) 5 (2.4) 10 (5.1) 0.147 Table 2 Evaluation of co-infections, laboratory parameters, and selected clinical characteristics of COVID-19 patients in the ICU, Antalya, 2022. Variable Total Survived Deceased p-value Co-infection, n (%) 181 (44.1) 61 (28.8) 120 (60.6) < 0.001 Blood culture positive, n = 347 39 (11.2) 9 (5.1) 30 (17.8) < 0.001 Respiratory infection, n = 360 136 (37.8) 39 (22.2) 97 (52.7) < 0.001 Urinary infection, n = 387 75 (19.4) 27 (13.4) 48 (25.9) 0.002 Catheter tip infection, n = 329 11 (3.3) 2 (1.2) 9 (5.6) 0.028 Treatment ECMO, n = 409 3 (0.7) 0 (0.0) 3 (1.5) 0.071 Vasopressor, n = 409 220 (53.8) 57 (26.9) 163 (82.7) < 0.001 IMV, n = 409 222 (54.3) 49 (23.1) 173 (87.8) < 0.001 MV duration (days), n = 227 5 (2–10) 4 (2–11) 6 (2–10) 0.255 NIMV, n = 409 113 (27.6) 38 (17.9) 75 (38.1) < 0.001 High-flow oxygen, n = 409 37 (9.0) 13 (6.1) 24 (12.2) 0.033 Any oxygen therapy, n = 409 347 (84.8) 195 (92.0) 152 (77.2) < 0.001 Prone positioning, n = 409 114 (27.9) 50 (23.6) 64 (32.5) 0.045 Tracheostomy, n = 409 27 (6.6) 9 (4.2) 18 (9.1) 0.047 Decannulation, n = 409 6 (1.5) 6 (2.8) 0 (0.0) 0.031 Other AKI status, n = 409 < 0.001 No AKI 225 (55.4) 150 (71.8) 75 (38.1) Stage 1 AKI 32 (7.9) 16 (7.7) 16 (8.1) Stage 2 AKI 56 (13.8) 23 (11.0) 33 (16.8) Stage 3 AKI 93 (22.9) 20 (9.6) 73 (37.1) RRT, n = 409 55 (13.4) 16 (7.5) 39 (19.8) < 0.001 Pneumothorax, n = 409 16 (3.9) 6 (2.8) 10 (5.1) 0.242 APACHE II score, n = 409 16 (11–22) 13 (9–17) 19 (14–25) < 0.001 Laboratory results D-dimer, n = 397 2.4 (1.1–5.3) 2.3 (1.1–4.3) 2.9 (1.1–6.8) 0.065 Ferritin, n = 386 540.1 (208.1–1283.1) 412.6 (136–1169) 680 (343–1347) 0.001 LDH, n = 372 404.5 (288.3–605.8) 365 (281–535) 486 (314.5–692) < 0.001 NLR, n = 407 12.7 (6.8–22.3) 11 (6–19) 15 (8.3–24.9) < 0.001 Fibrinogen, n = 260 582.5 (420.3–707.8) 517 (383.8–676.8) 611.5 (442.5–727) 0.023 PaO₂/FiO₂ ratio, n = 392 131.7 (88–211.1) 164.8 (108–253.3) 104 (68.8–181.6) < 0.001 Lactate, n = 393 1.5 (1.1–2.3) 1.4 (1–2) 1.7 (1.2–2.7) < 0.001 Table 3 Cox regression analysis of factors affecting mortality in COVID-19 patients in the ICU, Antalya, 2022. Variable Univariate HR (95% CI) p-value Multivariate HR (95% CI) p-value Male gender (ref: female) 0.90 (0.67–1.21) 0.479 0.89 (0.66–1.21) 0.474 Age ≥ 65 (ref: 25 1.57 (1.17–2.10) 0.002 – – BMI < 18.5 0.80 (0.32–1.98) 0.625 – – PCR positive 1.20 (0.90–1.61) 0.207 – – APACHE II score 1.06 (1.05–1.08) < 0.001 1.03 (1.01–1.05) 0.001 Malignancy 1.28 (0.93–1.76) 0.136 1.44 (1.04–2.01) 0.031 Co-infection 1.54 (1.16–2.06) 0.003 – – PaO₂/FiO₂ ratio 0.997 (0.996–0.999) 0.001 0.999 (0.997–1.000) 0.052 Lactate 1.09 (1.03–1.15) 0.002 – – Vasopressor use 4.80 (3.32–6.96) < 0.001 – – AKI Stage 1 1.72 (1.00–2.96) 0.049 – – AKI Stage 2 1.79 (1.19–2.70) 0.005 – – AKI Stage 3 2.40 (1.74–3.32) < 0.001 – – IMV 6.47 (4.22–9.92) < 0.001 5.15 (3.25–8.15) < 0.001 NIMV 1.45 (1.08–1.93) 0.012 – – Additional Declarations No competing interests reported. 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According to the World Health Organization (WHO), as of March 2022, more than 450\u0026nbsp;million confirmed cases and over 6\u0026nbsp;million deaths have been reported globally. As of December 29, 2021, COVID\u0026ndash;19 had caused 476,374,234 cases and 6,108,976 deaths worldwide (3). In T\u0026uuml;rkiye, the total number of cases was reported as 14,513,774, and the total number of deaths was 96,217 (4).\u003c/p\u003e\u003cp\u003eThe clinical spectrum of COVID-19 ranges from asymptomatic infection to severe pneumonia, acute respiratory distress syndrome (ARDS), multi-organ failure, and death. A significant proportion of critically ill patients require admission to intensive care units (ICUs), where mortality rates have been reported to vary between 30% and 80%, depending on disease severity, comorbidities, and available healthcare resources.\u003c/p\u003e\u003cp\u003eDue to the rapid global spread of the COVID-19 virus and the resulting high case numbers, a significant proportion of patients required respiratory support and were classified as critically ill, creating an unprecedented demand on intensive care units (ICUs) worldwide (5, 6). This burden on ICU capacities globally has led to an increase in both the number of patients admitted to ICUs and the number of deaths occurring in ICUs due to COVID-19 (7).\u003c/p\u003e\u003cp\u003eSeveral factors have been associated with poor prognosis in ICU patients with COVID-19, including advanced age, male sex, obesity, and comorbidities such as hypertension, diabetes, cardiovascular disease, and chronic lung disease. Additionally, higher severity scores such as the Acute Physiology and Chronic Health Evaluation II (APACHE II), invasive mechanical ventilation (IMV), vasopressor use, and acute kidney injury (AKI) have been linked to increased mortality.\u003c/p\u003e\u003cp\u003eIn T\u0026uuml;rkiye, ICU admission rates for COVID-19 have been substantial, yet data regarding mortality rates and prognostic factors in this population remain limited. Identifying these factors is critical for improving patient outcomes and optimizing resource allocation during pandemic surges.\u003c/p\u003e\u003cp\u003eThe aim of this study was to investigate the general characteristics, mortality rates, and factors associated with mortality in adult patients with COVID-19 admitted to the ICU in a tertiary hospital in Antalya, T\u0026uuml;rkiye.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design and setting\u003c/p\u003e\n\u003cp\u003eThis retrospective, single-center observational study was conducted at the Akdeniz University Faculty of Medicine Hospital, a tertiary care referral center in Antalya, T\u0026uuml;rkiye. The study period covered ICU admissions between March 1, 2020, and March 1, 2021.\u003c/p\u003e\n\u003cp\u003eParticipants\u003c/p\u003e\n\u003cp\u003eA total of 410 adult patients (\u0026ge;\u0026thinsp;18 years old) with confirmed COVID-19 pneumonia were included. The diagnosis was established based on clinical presentation, radiological findings compatible with COVID-19 pneumonia on chest computed tomography (CT), and/or a positive reverse transcription\u0026ndash;polymerase chain reaction (RT-PCR) test for SARS-CoV-2. Patients with incomplete medical records or ICU stays shorter than 24 hours were excluded.\u003c/p\u003e\n\u003cp\u003eData collection\u003c/p\u003e\n\u003cp\u003eData were obtained from electronic medical records and ICU follow-up charts. Variables collected included:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eDemographic characteristics: age, sex, body mass index (BMI), smoking status\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eComorbidities: hypertension, diabetes mellitus, ischemic heart disease, chronic lung disease, chronic kidney disease, rheumatologic disease, cerebrovascular accident, malignancy, organ transplantation history\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eClinical interventions: mechanical ventilation (invasive and non-invasive), vasopressor therapy, prone positioning, extracorporeal membrane oxygenation (ECMO), renal replacement therapy (RRT), tracheostomy, decannulation\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLaboratory parameters at ICU admission: complete blood count, lactate dehydrogenase (LDH), ferritin, fibrinogen, D-dimer, lactate, neutrophil-to-lymphocyte ratio (NLR), and PaO₂/FiO₂ ratio\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eOutcomes: ICU length of stay, hospital length of stay, survival status\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDefinitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcute kidney injury (AKI): Defined according to Kidney Disease Improving Global Outcomes (KDIGO) criteria and staged accordingly.\u003c/p\u003e\n\u003cp\u003eBody mass index (BMI): Calculated as weight in kilograms divided by the square of height in meters (kg/m\u0026sup2;).\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eStatistical analysis was performed using SPSS version 15.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were expressed as median (interquartile range, IQR) and compared using the Mann\u0026ndash;Whitney U test. Categorical variables were presented as frequencies and percentages, and compared using Chi-square or Fisher\u0026rsquo;s exact tests as appropriate. Cox proportional hazards regression analysis was performed to identify independent predictors of mortality. Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analysis were entered into the multivariate model. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The study was approved by the Akdeniz University Ethics Committee (Decision No: KAEK-282). As this was a retrospective study, the requirement for informed consent was waived.Results\u003c/p\u003e\n\u003cp\u003eThis study was conducted at Akdeniz University Faculty of Medicine Hospital and included 410 patients treated in the intensive care unit (ICU) for COVID-19 between March 11, 2020, and March 11, 2021. Of the 410 patients followed in our study, 212 (51.7%) survived, while 198 (48.3%) died. The mean hospital length of stay was 17.2 \u0026plusmn; 17.3 days, with a median stay of 13 days (range: 1\u0026ndash;156 days).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;When survival status was evaluated according to sex and smoking history, no statistically significant differences were found (p = 0.952 and p = 0.482, respectively). However, significant differences were observed for age, body mass index (BMI), total hospital stay, and COVID-19 PCR (polymerase chain reaction) results (all p \u0026lt; 0.001). Analysis of ICU length of stay also revealed statistically significant differences between survivors and non-survivors. No significant differences were found for comorbidities except for cerebrovascular accident (CVA), which was significantly more frequent among non-survivors (p = 0.001 and p = 0.029, respectively) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;When patients were evaluated according to survival status for the presence of co-infections, statistically significant differences were observed for having any co-infection, respiratory tract infection, urinary tract infection, catheter-tip infection, and positive blood culture (p \u0026lt; 0.001, p \u0026lt; 0.001, p = 0.002, p = 0.028, and p \u0026lt; 0.001, respectively).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Regarding oxygen therapy, statistically significant differences were found for receiving any form of oxygen therapy, use of invasive mechanical ventilation (IMV) or non-invasive mechanical ventilation (NIMV), and PaO₂/FiO₂ ratio (all p \u0026lt; 0.001). However, there were no significant differences for extracorporeal membrane oxygenation (ECMO) use or mechanical ventilation duration (p = 0.071 and p = 0.255, respectively). Statistically significant differences were also found in prone positioning, tracheostomy, and decannulation procedures (p = 0.045, p = 0.047, and p = 0.031, respectively).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Evaluation of vasopressor and renal replacement therapy (RRT) use revealed statistically significant differences between survivors and non-survivors (both p \u0026lt; 0.001). Significant differences were also observed for acute kidney injury (AKI) presence and AKI staging (p \u0026lt; 0.001), while pneumothorax showed no significant difference between groups (p = 0.242).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;When laboratory parameters were compared between survivors and non-survivors, ferritin, LDH, fibrinogen, neutrophil-to-lymphocyte ratio (NLR), and lactate levels were significantly different (p = 0.001, p \u0026lt; 0.001, p = 0.023, p \u0026lt; 0.001, and p \u0026lt; 0.001, respectively), whereas no significant difference was observed for D-dimer levels (p = 0.065) (Table 2).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In the univariate Cox regression analysis of COVID-19 patients treated in the ICU, the variable with the greatest impact on hazard ratio (mortality risk) was the use of invasive mechanical ventilation (IMV) (HR: 6.47, p \u0026lt; 0.001). Other factors affecting the hazard ratio were, in order of magnitude: vasopressor therapy (HR: 4.80, p \u0026lt; 0.001), BMI \u0026gt;25 kg/m\u0026sup2; (HR: 1.57, p = 0.002), presence of co-infection (HR: 1.54, p = 0.003), age \u0026gt;65 years (HR: 1.48, p = 0.010), use of non-invasive mechanical ventilation (NIMV) (HR: 1.45, p = 0.012), lactate level (HR: 1.09, p = 0.002), APACHE II score (HR: 1.06, p \u0026lt; 0.001), and PaO₂/FiO₂ ratio (HR: 0.997, p = 0.001).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In the multivariate Cox regression analysis, the variable with the greatest impact on hazard ratio was again the use of IMV (HR: 5.15, p \u0026lt; 0.001). Other significant factors in the multivariate model were the presence of malignancy (HR: 1.44, p = 0.031) and APACHE II score (HR: 1.03, p = 0.001). Thus, in our multivariate Cox regression analysis, COVID-19 patients on IMV had a 5.15-fold higher risk of death, those with malignancy had a 1.44-fold higher risk, and each one-point increase in APACHE II score increased mortality risk by 1.03 times (Table 3).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, 410 patients treated in the intensive care unit (ICU) due to COVID-19 were analyzed. A total of 48.3% of our patients died while in the ICU. The mean ICU length of stay was 17 days. A meta-analysis conducted in June 2020, which evaluated 24 studies on ICU mortality, reported an overall mortality rate of 41.6% (8). Although ICU–COVID-19 mortality rates vary across countries in the literature, COVID-19 continues to present with high mortality in the ICU setting (9,10). It has been suggested that differences in ICU admission criteria between countries may account for these variations. However, comparing the early pandemic period with the present, ICU mortality rates have not changed significantly, likely because only critically ill patients are admitted to the ICU at all stages of the pandemic.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In our study, non-survivors more frequently received vasopressors, invasive mechanical ventilation (IMV), non-invasive mechanical ventilation (NIMV), and high-flow oxygen therapy, and prone positioning was also used more frequently in this group. Notably, NIMV use increased mortality risk by 1.45 times, vasopressor therapy by 4.8 times, and IMV by 6.47 times. Additionally, the PaO₂/FiO₂ ratio was significantly lower in non-survivors. Extracorporeal membrane oxygenation (ECMO) use was not associated with mortality. A study from Mexico reported that IMV use was significantly less frequent in survivors, and multivariate Cox regression showed that IMV increased the risk of death by 3.31 times (11). In an American study, PaO₂/FiO₂ ratios were higher among survivors, while vasopressor and renal replacement therapy use was lower and statistically significant; ECMO use, as in our study, was not significant (12). In Sweden, an analysis of all ICU COVID-19 patients admitted up to May 2020 found that IMV use and prone positioning were significantly more common among non-survivors, while PaO₂/FiO₂ ratios and high-flow oxygen use were higher in survivors; NIMV showed no significant difference (13). COVID-19 mainly presents with pneumonia and ARDS-like hypoxemic respiratory failure, which is a primary cause of mortality and morbidity. Therefore, respiratory support forms the cornerstone of ICU care, but treatment algorithms vary by patient and country. Since IMV, NIMV, ECMO use, low PaO₂/FiO₂ ratios, and vasopressor therapy are applied to already critically ill patients, our results are consistent with expectations.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;There was a statistically significant difference in APACHE II scores between survivors and non-survivors, with higher scores in the latter. In our Cox regression model, each one-point increase in the APACHE II score increased mortality risk by 1.03 times; IMV was associated with a 5.15-fold higher risk of death, and malignancy with a 1.44-fold higher risk. Similarly, a study from Wuhan demonstrated that the APACHE II score was an important predictor of mortality in both univariate and multivariate Cox regression analyses (14).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In our study, mortality frequency did not differ by sex; however, older age and higher BMI were observed in non-survivors. The Cox regression model showed that age \u0026gt;65 years increased mortality risk by 1.48 times, and BMI \u0026gt;25 kg/m² increased risk by 1.57 times. An Italian multicenter study across 72 ICUs found higher mortality in older patients, particularly those aged ≥63 years (15). Ata et al. also reported that sex did not influence ICU mortality (16). In a Chicago-based study, obesity increased mortality risk by 1.7 times (17). Older age and elevated BMI are well-known risk factors for many diseases and are especially detrimental in the presence of comorbidities; our findings reinforce that this holds true for COVID-19.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In our study, survivors had longer hospital stays overall, whereas non-survivors had significantly longer ICU stays. Khalid et al. reported longer hospital and ICU stays among non-survivors (18). We believe that earlier ICU admission of critically ill patients in our cohort may have influenced these results, which can be considered a success of healthcare delivery.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Smoking did not affect mortality in our study, consistent with findings from a Czech study (19). However, some publications report increased mortality with smoking (20). The literature shows heterogeneous results regarding the relationship between smoking and COVID-19 severity, mortality, and morbidity.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;We found no statistically significant differences in mortality based on the presence of diabetes, hypertension, ischemic heart disease, chronic lung disease, chronic kidney disease, rheumatologic disease, or organ transplantation. However, cerebrovascular accident (CVA) was significantly more common among non-survivors. Mutair et al. similarly reported no significant association between most comorbidities and survival in ICU COVID-19 patients (21). While some studies indicate higher mortality in organ transplant recipients with severe COVID-19, results vary (22). The literature is mixed on whether chronic diseases and comorbidities influence mortality (23–25). In our study, the lack of patients with isolated single comorbidities may have influenced these findings.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Co-infections were more common among non-survivors, and further analysis showed a 1.54-fold increased mortality risk in patients with co-infections. Respiratory and urinary tract infections were more frequent among non-survivors, and positive blood or catheter-tip cultures were also more common. A Spanish study reported that co-infections were rare on ICU admission but that ICU-acquired infections were more frequent, and any co-infection source was associated with higher mortality (26). Our results align with the literature on co-infections.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Tracheostomy was more common among non-survivors, whereas decannulation occurred more frequently among survivors. The literature is divided on tracheostomy and decannulation outcomes. In general, only one-third of tracheostomized patients are decannulated, and mortality in this group is around 13.1% (27). Despite guideline-based recommendations, clinician experience plays a key role, likely explaining variability in results. Nasal oxygen therapy was more frequent among survivors; a study from India reported higher venturi mask and nasal oxygen use among survivors (28).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Acute kidney injury (AKI), particularly stage 3, was more common in non-survivors. Compared to patients without AKI, mortality risk increased 1.72-fold in stage 1, 1.79-fold in stage 2, and 2.4-fold in stage 3 AKI. Renal replacement therapy was also more frequent among non-survivors. A study from Saudi Arabia\u0026nbsp;likewise showed higher mortality among ICU COVID-19 patients with AKI (18). Multiple studies in the literature have shown an association between AKI and mortality (29). The pathophysiology of AKI in COVID-19 is thought to involve direct viral effects, local and systemic inflammatory responses, endothelial injury, microemboli, sepsis, and hypoxia (30). The coexistence of these factors in critically ill ICU patients may explain the high AKI-related mortality in our cohort.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eFerritin, LDH, neutrophil-to-lymphocyte ratio (NLR), fibrinogen, and lactate levels were higher in non-survivors. Although D-dimer levels were also higher, the difference was not statistically significant. Coagulation factors were higher in survivors. In the Cox regression model, each unit increase in lactate increased mortality risk by 1.09 times. A study from Mexico City similarly found significant differences between survivors and non-survivors in LDH, ferritin, D-dimer, NLR, fibrinogen, and lactate, with lower median values in survivors (31). Increases in acute phase reactants are expected in severe disease. Lactate is an important blood gas parameter, rising before detectable changes in vital signs. NLR may also be useful in predicting mortality, as supported by multiple studies in the literature (32).\u003c/p\u003e\n"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAKI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute Kidney Injury\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAPACHE II\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute Physiology and Chronic Health Evaluation II\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody Mass Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eCVA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCerebrovascular Accident\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eECMO\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eExtracorporeal Membrane Oxygenation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHazard Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eICU\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIntensive Care Unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eIMV\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInvasive Mechanical Ventilation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eIQR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterquartile Range\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eLDH\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLactate Dehydrogenase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eNIMV\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNon-invasive Mechanical Ventilation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eNLR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNeutrophil-to-Lymphocyte Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePaO₂/FiO₂ ratio\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eArterial Oxygen Partial Pressure to Fraction of Inspired Oxygen Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePCR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePolymerase Chain Reaction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eRRT\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRenal Replacement Therapy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eWHO\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWorld Health Organization\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eMortality and Associated Factors in Critically Ill COVID-19 Patients\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e\u003cb\u003eA Retrospective Cohort Study\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis study was approved by the Akdeniz University Ethics Committee (Research Code: KAEK-282; approval date: April 5, 2023). The committee determined there were no ethical objections to conducting the study. Informed consent was waived due to the retrospective nature of the study.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eNo specific funding was received for this study.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eAll authors contributed to study conception, design, data acquisition, statistical analysis, and interpretation. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eWe thank the ICU staff at Akdeniz University Faculty of Medicine Hospital for their dedication and service during the COVID-19 pandemic.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Coronavirus disease (COVID-19) pandemic. Available from: https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov. Accessed 20 March 2022.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Coronavirus disease (COVID-19). Available from: https://www.who.int/health-topics/coronavirus. Accessed 20 March 2022.\u003c/li\u003e\n\u003cli\u003eRepublic of T\u0026uuml;rkiye Ministry of Health. COVID-19 Information Platform. Available from: https://covid19.saglik.gov.tr/. Accessed 20 March 2022.\u003c/li\u003e\n\u003cli\u003eWu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a report of 72,314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323(13):1239\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eGrasselli G, Zangrillo A, Zanella A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy. JAMA. 2020;323(16):1574\u0026ndash;81.\u003c/li\u003e\n\u003cli\u003eYang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475\u0026ndash;81.\u003c/li\u003e\n\u003cli\u003eHuang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497\u0026ndash;506.\u003c/li\u003e\n\u003cli\u003eArentz M, Yim E, Klaff L, et al. Characteristics and outcomes of 21 critically ill patients with COVID-19 in Washington State. JAMA. 2020;323(16):1612\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eZhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eRichardson S, Hirsch JS, Narasimhan M, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA. 2020;323(20):2052\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eBhatraju PK, Ghassemieh BJ, Nichols M, et al. Covid-19 in critically ill patients in the Seattle region \u0026mdash; case series. N Engl J Med. 2020;382(21):2012\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eWang Y, Lu X, Li Y, et al. Clinical course and outcomes of 344 intensive care patients with COVID-19. Am J Respir Crit Care Med. 2020;201(11):1430\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003ePhua J, Weng L, Ling L, et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations. Lancet Respir Med. 2020;8(5):506\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eKnaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: A severity of disease classification system. Crit Care Med. 1985;13(10):818\u0026ndash;29.\u003c/li\u003e\n\u003cli\u003eYang X, Cai S, Luo Y, et al. Clinical characteristics of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: A single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475\u0026ndash;81.\u003c/li\u003e\n\u003cli\u003eFan E, Brodie D, Slutsky AS. Acute respiratory distress syndrome: advances in diagnosis and treatment. JAMA. 2018;319(7):698\u0026ndash;710.\u003c/li\u003e\n\u003cli\u003eBellani G, Laffey JG, Pham T, et al. Epidemiology, patterns of care, and mortality for patients with acute respiratory distress syndrome in intensive care units in 50 countries. JAMA. 2016;315(8):788\u0026ndash;800.\u003c/li\u003e\n\u003cli\u003eBrochard L, Slutsky A, Pesenti A. Mechanical ventilation to minimize progression of lung injury in acute respiratory failure. Am J Respir Crit Care Med. 2017;195(4):438\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eAlhazzani W, M\u0026oslash;ller MH, Arabi YM, et al. Surviving Sepsis Campaign: guidelines on the management of critically ill adults with coronavirus disease 2019 (COVID-19). Intensive Care Med. 2020;46(5):854\u0026ndash;87.\u003c/li\u003e\n\u003cli\u003eGuan WJ, Ni ZY, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003eMehra MR, Desai SS, Kuy S, Henry TD, Patel AN. Cardiovascular disease, drug therapy, and mortality in Covid-19. N Engl J Med. 2020;382(25):e102.\u003c/li\u003e\n\u003cli\u003eKuderer NM, Choueiri TK, Shah DP, et al. Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study. Lancet. 2020;395(10241):1907\u0026ndash;18.\u003c/li\u003e\n\u003cli\u003eGuan WJ, Liang WH, Zhao Y, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J. 2020;55(5):2000547.\u003c/li\u003e\n\u003cli\u003eTang N, Li D, Wang X, Sun Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost. 2020;18(4):844\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eZhang L, Yan X, Fan Q, et al. D‐dimer levels on admission to predict in-hospital mortality in patients with Covid-19. J Thromb Haemost. 2020;18(6):1324\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eHan H, Ma Q, Li C, et al. Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors. Emerg Microbes Infect. 2020;9(1):1123\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eChen G, Wu D, Guo W, et al. Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest. 2020;130(5):2620\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eChen Y, Li L. SARS-CoV-2: virus dynamics and host response. Lancet Infect Dis. 2020;20(5):515\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eZhou Y, Fu B, Zheng X, et al. Aberrant pathogenic GM-CSF+ T cells and inflammatory CD14+CD16+ monocytes in severe pulmonary syndrome patients of a new coronavirus. Proc Natl Acad Sci USA. 2020;117(17):10917\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Clinical management of COVID-19: interim guidance. Available from: https://www.who.int/publications/i/item/clinical-management-of-covid-19. Accessed 20 March 2022.\u003c/li\u003e\n\u003cli\u003eRepublic of T\u0026uuml;rkiye Ministry of Health. COVID-19 Adult Patient Treatment Guideline. Available from: https://covid19.saglik.gov.tr/Eklenti/39061/0/covid-19rehberieriskinhastatedavisipdf.pdf. Accessed 20 March 2022.\u003c/li\u003e\n\u003cli\u003eNational Institutes of Health. COVID-19 treatment guidelines. Available from: https://www.covid19treatmentguidelines.nih.gov/. Accessed 20 March 2022.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eEvaluation of some descriptive characteristics and comorbidities of COVID-19 patients in the ICU, Antalya, 2022.\u003c/div\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eCharacteristics\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eTotal\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eSurvived\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eDeceased\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ep-value\u003c/div\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eGender, n (%)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.952\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eFemale\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e134 (32.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e69 (32.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e65 (32.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eMale\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e276 (67.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e143 (67.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e133 (67.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eAge (years), median (IQR)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e67 (58\u0026ndash;76)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e66 (55.3\u0026ndash;74)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e70 (60\u0026ndash;78)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eBMI, n\u0026thinsp;=\u0026thinsp;403\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e25 (23\u0026ndash;27.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e24.5 (22.5\u0026ndash;27)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e25.9 (24\u0026ndash;29)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eICU length of stay (days)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e5 (3\u0026ndash;10)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e4 (3\u0026ndash;7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e6 (3\u0026ndash;12.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eHospital length of stay (days)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e13 (7\u0026ndash;20.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e14 (9\u0026ndash;23.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e10 (5\u0026ndash;17)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eSmoking status, n\u0026thinsp;=\u0026thinsp;317\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.482\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eNon-smoker\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e189 (59.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e92 (56.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e97 (63.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eSmoker\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e80 (25.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e45 (27.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e35 (22.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eEx-smoker\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e48 (15.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e26 (16.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e22 (14.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ePCR positive, n (%)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e215 (52.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e91 (42.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e124 (62.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eCT positive, n (%)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e410 (100)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e212 (100)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e198 (100)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eComorbidities, n (%)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eDiabetes Mellitus\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e164 (40.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e86 (40.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e78 (39.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.809\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eHypertension\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e208 (50.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e104 (49.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e104 (52.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.483\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eIschemic heart disease\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e163 (39.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e85 (40.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e78 (39.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.885\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eChronic lung disease\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e100 (24.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e51 (24.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e49 (24.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.871\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eChronic kidney disease\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e63 (15.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e36 (17.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e27 (13.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.348\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eRheumatological disease\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e19 (4.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e10 (4.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e9 (4.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.934\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eCerebrovascular accident\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e42 (10.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e15 (7.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e27 (13.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.029\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eMalignancy, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e97 (23.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e46 (21.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e51 (25.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.347\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eOrgan transplant\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e15 (3.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e5 (2.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e10 (5.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.147\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eEvaluation of co-infections, laboratory parameters, and selected clinical characteristics of COVID-19 patients in the ICU, Antalya, 2022.\u003c/div\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eVariable\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eTotal\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eSurvived\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eDeceased\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ep-value\u003c/div\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eCo-infection, n (%)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e181 (44.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e61 (28.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e120 (60.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eBlood culture positive, n\u0026thinsp;=\u0026thinsp;347\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e39 (11.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e9 (5.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e30 (17.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eRespiratory infection, n\u0026thinsp;=\u0026thinsp;360\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e136 (37.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e39 (22.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e97 (52.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eUrinary infection, n\u0026thinsp;=\u0026thinsp;387\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e75 (19.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e27 (13.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e48 (25.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.002\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eCatheter tip infection, n\u0026thinsp;=\u0026thinsp;329\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e11 (3.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e2 (1.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e9 (5.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.028\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eTreatment\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eECMO, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e3 (0.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0 (0.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e3 (1.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.071\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eVasopressor, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e220 (53.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e57 (26.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e163 (82.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eIMV, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e222 (54.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e49 (23.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e173 (87.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eMV duration (days), n\u0026thinsp;=\u0026thinsp;227\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e5 (2\u0026ndash;10)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e4 (2\u0026ndash;11)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e6 (2\u0026ndash;10)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.255\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eNIMV, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e113 (27.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e38 (17.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e75 (38.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eHigh-flow oxygen, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e37 (9.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e13 (6.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e24 (12.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.033\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eAny oxygen therapy, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e347 (84.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e195 (92.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e152 (77.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eProne positioning, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e114 (27.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e50 (23.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e64 (32.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.045\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eTracheostomy, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e27 (6.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e9 (4.2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e18 (9.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.047\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eDecannulation, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e6 (1.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e6 (2.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0 (0.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.031\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eOther\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eAKI status, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eNo AKI\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e225 (55.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e150 (71.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e75 (38.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eStage 1 AKI\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e32 (7.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e16 (7.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e16 (8.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eStage 2 AKI\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e56 (13.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e23 (11.0)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e33 (16.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eStage 3 AKI\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e93 (22.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e20 (9.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e73 (37.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eRRT, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e55 (13.4)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e16 (7.5)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e39 (19.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ePneumothorax, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e16 (3.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e6 (2.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e10 (5.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.242\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eAPACHE II score, n\u0026thinsp;=\u0026thinsp;409\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e16 (11\u0026ndash;22)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e13 (9\u0026ndash;17)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e19 (14\u0026ndash;25)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eLaboratory results\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eD-dimer, n\u0026thinsp;=\u0026thinsp;397\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e2.4 (1.1\u0026ndash;5.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e2.3 (1.1\u0026ndash;4.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e2.9 (1.1\u0026ndash;6.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.065\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eFerritin, n\u0026thinsp;=\u0026thinsp;386\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e540.1 (208.1\u0026ndash;1283.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e412.6 (136\u0026ndash;1169)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e680 (343\u0026ndash;1347)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eLDH, n\u0026thinsp;=\u0026thinsp;372\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e404.5 (288.3\u0026ndash;605.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e365 (281\u0026ndash;535)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e486 (314.5\u0026ndash;692)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eNLR, n\u0026thinsp;=\u0026thinsp;407\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e12.7 (6.8\u0026ndash;22.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e11 (6\u0026ndash;19)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e15 (8.3\u0026ndash;24.9)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eFibrinogen, n\u0026thinsp;=\u0026thinsp;260\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e582.5 (420.3\u0026ndash;707.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e517 (383.8\u0026ndash;676.8)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e611.5 (442.5\u0026ndash;727)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.023\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ePaO₂/FiO₂ ratio, n\u0026thinsp;=\u0026thinsp;392\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e131.7 (88\u0026ndash;211.1)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e164.8 (108\u0026ndash;253.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e104 (68.8\u0026ndash;181.6)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eLactate, n\u0026thinsp;=\u0026thinsp;393\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.5 (1.1\u0026ndash;2.3)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.4 (1\u0026ndash;2)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.7 (1.2\u0026ndash;2.7)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eCox regression analysis of factors affecting mortality in COVID-19 patients in the ICU, Antalya, 2022.\u003c/div\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eVariable\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eUnivariate HR (95% CI)\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ep-value\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eMultivariate HR (95% CI)\u003c/div\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ep-value\u003c/div\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eMale gender (ref: female)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.90 (0.67\u0026ndash;1.21)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.479\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.89 (0.66\u0026ndash;1.21)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.474\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;65 (ref: \u0026lt;65)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.48 (1.10\u0026ndash;2.00)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.010\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.25 (0.92\u0026ndash;1.70)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.154\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eBMI\u0026thinsp;\u0026gt;\u0026thinsp;25\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.57 (1.17\u0026ndash;2.10)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.002\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.80 (0.32\u0026ndash;1.98)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.625\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ePCR positive\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.20 (0.90\u0026ndash;1.61)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.207\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eAPACHE II score\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.06 (1.05\u0026ndash;1.08)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.03 (1.01\u0026ndash;1.05)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eMalignancy\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.28 (0.93\u0026ndash;1.76)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.136\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.44 (1.04\u0026ndash;2.01)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.031\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eCo-infection\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.54 (1.16\u0026ndash;2.06)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.003\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003ePaO₂/FiO₂ ratio\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.997 (0.996\u0026ndash;0.999)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.001\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.999 (0.997\u0026ndash;1.000)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.052\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003eLactate\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e1.09 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(1.08\u0026ndash;1.93)\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e0.012\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cdiv class=\"SimplePara\"\u003e\u0026ndash;\u003c/div\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, intensive care unit, mortality, risk factors, APACHE II, mechanical ventilation, comorbidity","lastPublishedDoi":"10.21203/rs.3.rs-7362857/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7362857/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eStructured Abstract\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBackground\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic has led to a substantial increase in intensive care unit (ICU) admissions worldwide, with high mortality rates among critically ill patients. Identifying mortality rates and associated factors is crucial for guiding clinical management and resource allocation.\u003c/p\u003e\u003cp\u003eMethods\u003c/p\u003e\u003cp\u003e This retrospective, single-center study included 410 adult patients with confirmed COVID-19 admitted to the ICU between March 2020 and March 2021 at a tertiary care hospital in Antalya, T\u0026uuml;rkiye. Demographic characteristics, comorbidities, clinical interventions, laboratory parameters, and outcomes were recorded. Survivors and non-survivors were compared using the Mann\u0026ndash;Whitney U, Chi-square, and Fisher\u0026rsquo;s exact tests. Cox regression analysis was performed to identify independent predictors of mortality.\u003c/p\u003e\u003cp\u003eResults\u003c/p\u003e\u003cp\u003eThe overall ICU mortality rate was 48.3%. Non-survivors were older (median age: 70 vs. 66 years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had higher BMI (25.9 vs. 24.5 kg/m\u0026sup2;, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and longer ICU stays (6 vs. 4 days, p\u0026thinsp;=\u0026thinsp;0.001). They more frequently required invasive mechanical ventilation (87.8% vs. 23.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), vasopressor therapy (82.7% vs. 26.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and renal replacement therapy (19.8% vs. 7.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Laboratory findings in non-survivors showed higher ferritin (680 vs. 412.6 ng/mL, p\u0026thinsp;=\u0026thinsp;0.001), LDH (486 vs. 365 U/L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), fibrinogen (611.5 vs. 517 mg/dL, p\u0026thinsp;=\u0026thinsp;0.023), NLR (15 vs. 11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and lactate (1.7 vs. 1.4 mmol/L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as lower PaO₂/FiO₂ ratio (104 vs. 164.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multivariate Cox regression identified invasive mechanical ventilation (HR 5.15, 95% CI 3.25\u0026ndash;8.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), malignancy (HR 1.44, 95% CI 1.04\u0026ndash;2.01, p\u0026thinsp;=\u0026thinsp;0.031), and APACHE II score (HR 1.03, 95% CI 1.01\u0026ndash;1.05, p\u0026thinsp;=\u0026thinsp;0.001) as independent predictors of mortality.\u003c/p\u003e\u003cp\u003eConclusions\u003c/p\u003e\u003cp\u003eICU mortality among COVID-19 patients remains high. Advanced age, obesity, high APACHE II score, mechanical ventilation, vasopressor use, and certain comorbidities significantly increase mortality risk. Early identification of high-risk patients and targeted interventions may improve outcomes.\u003c/p\u003e","manuscriptTitle":"Mortality and Associated Factors in Critically Ill COVID-19 Patients: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 16:50:33","doi":"10.21203/rs.3.rs-7362857/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e6bc1a0-f1aa-4900-bf3e-49ba3218df3b","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-07T08:39:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 16:50:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7362857","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7362857","identity":"rs-7362857","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}