Thirty‑Day Readmission Rates and Outcomes after hospitalization for Ischemic Colitis. A National Analysis

Thirty‑Day Readmission Rates and Outcomes after hospitalization for Ischemic Colitis. 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A National Analysis Sharon I. Narvaez, John P. Martinez, Jami Kinnucan, Steven Keilin, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4503996/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 Background/Aim Limited data exists on 30-day readmission rates, readmission causes and predictors following Ischemic Colitis (IC). The aim is to identify etiologies for the above using a national database. Methods A retrospective cohort study using the 2019 National Readmission Database (NRD) of adult patients with an index admission (IA) for IC from January to November and were readmitted within 30 days of discharge was performed. The primary outcome was readmission of any cause. Secondary outcomes were mortality and resource utilization associated with readmission. Independent risk factors for all-cause readmission were identified using Cox regression analysis. Results A total of 6,853 IC patients were identified. Readmission within 30 days occurred in 762 (11%). The primary readmission cause was sepsis. A total of 325 patients died during the IA and additional 30 patients died within 30 days of discharge. Independent predictors of readmission were discharge to short term hospital, a Charlson comorbidity index score ≥ 2 and admission at large size hospital. Having private insurance and undergoing colonoscopy were associated with lower readmission odds. Economic burden of readmission was $12 million in total costs and $51.4 million in total charges. Conclusion Among admitted IC patients, 30-day readmission rate was 11% with half of those secondary to sepsis. Undergoing colonoscopy during the IA is associated with 34% less risk of readmission and disposition to other facilities appears associated with increased early readmission risk. Prospective evaluation to confirm these findings along with development of optimal care strategies to reduce readmission post IC episodes are needed. Ischemic Colitis 30-day Readmission Common Causes of Readmission Predictors of readmission Introduction Ischemic colitis (IC) is the primary etiology from intestinal ischemia, with a prevalence that significantly increases with advancing age [ 1 ]. Its occurrence varies between 4.5 to 44 per 100,000 person-years [ 2 ]. It constitutes a meaningful proportion of hospital admissions, seen in approximately 1 in 2000 individuals admitted to hospitals [ 2 ]. IC consists of a range of clinical syndromes attributed to vascular occlusive or non-occlusive pathologies marked by inadequacies in colonic blood perfusion [ 3 ]. This damage can extend from a mild inflammation process to full thickness necrosis. The gold standard for diagnosing IC includes colonoscopy and histopathological biopsy [ 4 ]. Most patients exhibit favorable response to conservative medical treatment; however, surgical intervention becomes necessary in approximately one of every five patients [ 4 ]. Management of IC patients continues to pose a considerable challenge to healthcare systems. Unfortunately, there is a lack of studies addressing the challenges of this gastrointestinal (GI) disorder. A major obstacle is disparities between patients with this condition and the lack of research in this area. Studies of other gastrointestinal diseases have revealed that patients with worse outcomes, early readmissions, and higher mortality are more commonly seen with certain kind of health insurance, which may be related to access of medical care [ 5 – 6 ]. IC prognosis can vary depending on several factors, including disease location, presence of other medical conditions, and whether surgical intervention is needed [ 5 ]. It is important that the overall mortality rate associated with this condition is approximately 22% [ 5 ]. However, it is essential to emphasize that the severity of the disease and the likelihood of a fatal outcome tend to be higher when IC occurs on the right side of the colon [ 2 ]. Risk factors include a patient's medical history, including a prior cerebrovascular disease, abdominal surgical interventions, hyperlipidemia, and malignancies [ 7 ]. These comorbidities, acting as independent risk factors, exert notable influence on the duration of hospitalization, varying from one week to two weeks [ 7 ]. Timely and accurately identifying IC is critical in mitigating length of stay (LOS) and diminishing the likelihood of readmission. The 30-day readmission rate has garnered heightened attention from healthcare administrators and medical professionals due to its significance in assessing hospital effectiveness and its correlation with elevated healthcare expenditures [ 7 – 8 ]. It is worth noting that Medicare bears a substantial financial burden, with an estimated annual expenditure of tens of billions attributable to readmissions [ 7 – 8 ]. The aim of the current investigation is to identify 30-day readmission rate, readmission causes, and predictors of readmission in ischemic colitis. Methods A retrospective cohort study using the 2019 National Readmission Database (NRD) of adult patients that had an index admission (IA) for IC from the month of January to November and were readmitted within 30-days of discharge was performed. International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10CM/PCS) codes were utilized to identify diagnosis and procedures. Admitting hospital for IA and readmission was categorized by ownership control, bed capacity, academic standing, urban/rural location, and geographic region. Next, a 20% probability sample of every hospital in each collection was gathered. For every patient listed in the NRD database, a unique ID was assigned. This ID was useful to identify all patient admissions made inside the data set between January and November 2019. The additional data included all of the ICD-10CM/PCS codes. Study Outcomes The primary outcome was the 30-day hospital readmission rate from any cause. Secondary outcomes were mortality, resource utilization (length of stay (LOS), total hospitalization costs and charges) associated with readmission. Additionally, the top ten reasons for readmission was identified during the study period. Definitions of Variables Patient demographics along with data of interest was obtained from the NRD. Information obtained included age (years), gender, primary payer (Medicare, medicated, private, uninsured), residence (large metropolitan areas with a population of at least one million, small metropolitan areas with a population of less than one million, micropolitan areas (nonurban residual), and not metropolitan or micropolitan), hospital size (small, medium, and large) based on bed count, and teaching status. ICD10-CM/PCS codes were used to acquire primary diagnosis, comorbidities, and procedures performed during IA along with readmission. Sundararajan's adaptation of the modified Deyo's Charlson Comorbidity Index (CCI) was employed to evaluate the comorbidity burden [ 9 ]. Cox regression analysis was used to find independent risk factors for readmission. Hospital-specific cost-charge ratios based on inpatient all-payer costs are provided by the NRD. The hospital accounting reports provides the Centers for Medicare and Medicaid Services with this cost data. Total hospital costs were determined by multiplying the total hospital charges by the associated cost-to-charge ratio. Statistical Analysis STATA, version 16 (StataCorp, College Station, TX) was used to perform the statistical analysis. To get estimates for the total population of hospitalized patients with IC in the US, weighting of patient-level observations was used. The primary and secondary outcomes' unadjusted odds ratios were determined by univariate Cox regression analysis. Multivariable Cox regression analysis was then employed to correct for potential confounders in the results. All confounders that were significantly associated with the outcome on univariable analysis with a cutoff P value of 0.20 were included in the multivariable regression models. Fisher exact test was used to compare proportions, and Student t-test was used to compare continuous variables. Every P-value was two-sided, and the statistical significance threshold was set at 0.05. Results General Characteristics A total of 6,853 patients with diagnosis of IC were identified in 2019. The mean age was 70.0 years of age, 26.3% of patients were female, Medicare was the most common health insurance, 22.7% of patients were from the lowest quartile of income, more than half of the patients resided in large metropolitan areas with at least 1 million residents, 30.3% of patients had a CCI score of ≥ 3, 15.2% of patients had obesity and more than a quarter of the patients had type 2 diabetes mellitus as a comorbidity. In addition, 8.8% and 3.1% of patients had registered malnutrition and alcohol use disorder (AUD), respectively. More than 68% of the patients were treated at urban-teaching hospitals. Table 1 illustrates the items above as well as provides further detail about the IA group with IC. Table 1 Patient characteristics (N = 6,853) Variable N (%) Female 1,802 (26.3) Age in years (Mean) 70.0 (69.6–70.5) Disposition of patient Discharged to home or self-care 4,612 (67.3) Short-term hospital 21 (0.3) Skilled nursing facility/intermediate care 877 (12.8) Home health care 973 (14.2) Against medical advice 48 (0.7) Died 322 (4.7) Insurance provider Medicare 4,996 (72.9) Medicaid 418 (6.1) Private 1,343 (19.6) Uninsured 96 (1.4) Median Income in patient zip code $ 1–42,999 1,556 (22.7) $ 43,000–53,999 1,843 (26.9) $ 54,000–70,999 1,946 (28.4) $ ≥71,000 1,508 (22.0) Patient residence Large metropolitan area with at least 1 million residents 3,543 (51.7) Small metropolitan areas with less than 1 million residents 2,666 (38.9) Micropolitan areas 500 (7.3) Not metropolitan or micropolitan (nonurban residual) 144 (2.1) Charlson Comorbidity Index Score (%) 0 1,974 (28.8) 1 1,652 (24.1) 2 1,151 (16.8) ≥ 3 2,076 (30.3) Hospital Bed size (%) Small 1,597 (23.3) Medium 2,090 (30.5) Large 3,166 (46.2) In-hospital procedures (%) Colonoscopy 2,960 (43.2) Time Colonoscopy (Mean) 2.1 (1.9–2.2) Colectomy 583 (8.5) Time Colectomy (Mean) 2.1 (1.6–2.6) Parenteral nutrition 171 (2.5) In-hospital complications (%) Mechanical ventilation 89 (1.3) Shock 254 (3.7) Transfer to Rehab (%) 34 (0.5) Other Comorbidities (%) Alcohol use disorder 212 (3.1) Tobacco use disorder 47 (0.7) Cannabis use disorder 75 (1.1) Malnutrition 603 (8.8) Obesity 1,042 (15.2) BMI < 30 459 (6.7) BMI ≥ 30 850 (12.4) Type 2 diabetes 1,830 (26.7) Vit D deficiency 117 (1.7) Vit B12 deficiency 41 (0.6) Teaching Status (%) Teaching 4,701 (68.6) Urban hospital (%) Urban 5,338 (77.9) Health-care related usage (%) LOS (days), mean 5.7 (5.5–5.9) Charges ( $ ), mean 65,118.0 (60,770.1–69,465.9) Cost ( $ ), mean 16,321.2 (15,428.4–17,214.1) Thirty-Day All‑Cause Hospital Readmission A total of 762 patients (11.0%) were readmitted in 30 days after hospital discharge. The primary cause for readmission was sepsis (32.5%) followed by vascular disorder of the intestine (14.2%) and acute kidney injury (4.9%). Table 2 contains a list of the top ten readmission diagnoses after IA for IC. Table 2 Top ten causes of readmission Diagnosis n (%) ICD 10 CM code Sepsis 453 (59.3) A419 Vascular disorder of intestine 312 (40.9) K559 Acute kidney failure 188 (24.7) N179 Enterocolitis due to Clostridium difficile 176 (23.1) A0472 Gastrointestinal hemorrhage 161 (21.2) K922 Chronic vascular disorders of intestine 156 (20.5) K551 Noninfective gastroenteritis and colitis 155 (20.3) K529 Unspecified intestinal obstruction 100 (13.1) K56609 Pneumonia 99 (13.0) J189 Hypertensive heart disease with heart failure 97 (12.7) I110 In‑Hospital and 30‑Day Mortality Rates Among Index Admission A total of 325 patients died during the IA for IC with an additional 30 patients that died within 30 days of discharge. The respective mortality rates for IA and readmission were 4.7% and 4.0%; however, it was not statistically significant (P = 0.79). Readmitted Patients Versus Index Admission Patients Readmitted patients were older (71.0 years vs. 70.0 years; P = < 0.01) with an increased proportion of females (32.0% vs. 25.5%; P = < 0.01). Readmitted patients were more likely to have Medicare as primary health insurance 79.9% vs. 71.9%; P = < 0.01), to be from the lowest quartile of income (27.7% vs. 22.1%; P 0.02), have a CCI score ≥ 3 (17.8% vs. 11.6%; P = < 0.01), underlying type 2 DM (37.0% vs. 25.5%; P = < 0.01), malnutrition (13.4% vs. 8.2%; P = < 0.01) and secondary diagnosis of AUD (4.8% vs. 2.8%; P = 0.04). There was no difference in the proportion of patients admitted at teaching hospitals (72.6% vs. 68.1% P = 0.08) or proportion of patients with underlying obesity between groups (13.8% vs. 15.3%; P = 0.47). Readmitted patients with CCI ≥ 3 had increased morbidity compared to CCI of < 3 (46.2% vs. 28.4%; P = < 0.01). Furthermore, readmitted patients were less likely to have an inpatient colonoscopy (32.3% vs. 44.6%; P = < 0.01), but most likely to have parenteral nutrition support (5.3% vs. 2.1%; P = < 0.01) and colectomy (17.5% vs. 7.3%; P = < 0.01). There was no difference in having tobacco, cannabis or opioid use disorders between both groups. The results are summarized in Table 3 . Table 3 General characteristics of index admission vs. readmitted patients after index admission for ischemic colitis Variable Index Admission Readmitted P value Female (N = 1,802) % (460) 25.5 (577) 32.0 < 0.01 Age in years (mean) 70.0 71.0 < 0.01 Disposition (%) Home 70.2 44.4 Short-term hospital 0.2 0.7 Against medical advice 11.1 26.7 Discharged to another institution 12.6 26.9 Home Health Care 0.6 0 Insurance provider (%) Medicare 71.9 79.9 < 0.01 Medicaid 5.9 7.8 Private 20.7 10.9 Uninsured 1.5 1.4 Charlson Comorbidity Index Score (%) 0 30.4 15.0 < 0.01 1 24.9 17.7 2 16.3 21.1 ≥ 3 28.4 46.2 Median Income in patient zip code (%) $ 1–42,999 22.1 27.7 0.02 $ 43,000–53,999 26.7 29.3 $ 54,000–70,999 28.8 24.4 $ ≥71,000 22.4 18.6 Patient residence (%) Large metropolitan area with at least 1 million residents 51.4 54.0 0.84 Small metropolitan areas with less than 1 million residents 39.2 37.2 Micropolitan areas 7.4 6.7 Not metropolitan or micropolitan (nonurban residual) 2.0 2.1 Hospital Procedures (%) Parenteral nutrition 2.1 5.3 < 0.01 Colonoscopy 44.6 32.3 < 0.01 Colectomy 7.3 17.5 < 0.01 In-hospital complications (%) Mechanical ventilation 1.2 2.2 0.08 Shock 3.6 5.0 0.19 Other comorbidities (%) Alcohol use disorder 2.8 4.8 0.04 Tobacco use disorder 0.7 0.2 0.12 Cannabis use disorder 1.1 1.4 0.53 Opioid use disorder 1.7 1.3 0.46 Type 2 DM 25.5 37.0 < 0.01 Obesity 15.3 13.8 0.47 BMI < 30 6.6 7.0 0.77 BMI ≥ 30 12.5 11.5 0.61 Malnutrition 8.2 13.4 < 0.01 Vit D deficiency 1.6 2.9 0.08 Vit B12 deficiency 0.6 0.8 0.68 Hospital Size (%) Small 23.9 18.5 0.07 Medium 30.5 30.4 Large 45.6 51.1 Teaching status (%) Teaching 68.1 72.6 0.08 Urban hospital (%) Urban 77.5 81.3 0.08 Health-care related usage LOS (days), mean 5.7 6.4 < 0.01 Charges ( $ ), mean 65,118.0 67,423.4 < 0.01 Cost ( $ ), mean 16,321.2 15,786.1 < 0.01 Mortality rate (%) Mortality 325 (4.7%) 30 (4%) 0.79 Morbidity Among Readmitted Patients Versus Index Admission Patients The percentage of patients who experienced respiratory failure and needed mechanical ventilation (2.2% vs. 1.2%; P = 0.08) and those who experienced shock of any kind (5.0% vs. 3.6%; P = 0.19) did not differ between readmitted patients and IA patients. Health Care Burden of Readmission The hospital LOS for readmitted patients was 6.4 (6.2–6.6) days which was longer than the index admission (5.7 days [5.5–5.9]; P = < 0.01). The mean hospital costs of readmission were $ 15,786 which was lower than those of the index admissions $ 16,32; P < 0.01. The mean hospitalization charges for readmission were $ 67,423 which was higher than the index admission $ 65,118; P < 0.01. The total economic burden of readmission was $ 12 million in total costs and $ 51.4 million in total charges. Independent Predictors of Readmission Using univariate Cox regression analysis, the degree of association between readmission and various variables, such as patient, hospital, comorbidities, and treatment-level, was examined separately. Table 4 displays the final Cox multivariate regression analysis, which only included variables with P ≤ 0.20. Independent predictors of readmission were patients discharged to short term hospital (aHR:4.54, P = 0.02), skilled nursing facility (aHR:1.98, P = < 0.01), and home health care (aHR:2.08, P = < 0.01), a Charlson comorbidity index score ≥ 2 (aHR:1.63, P = 0.02) and being admitted at large size hospital (aHR:1.37, P = 0.04). Having private insurance as primary payer (aHR:0.59, P = < 0.01) and undergoing to colonoscopy at IA (aHR:0.66, P = < 0.01) were associated with lower odds of readmission. Table 4 Independent Predictors of 30-days readmission using Cox multivariate regression analysis Variable Hazard ratio (95% confidence interval) P value Female 0.92 (0.72–1.18) 0.53 Age 0.98 (0.97–1.01) 0.08 Disposition of patient - Discharged to home or self-care - Short-term hospital - Skilled nursing facility/intermediate care - Home health care - Against medical advice Reference 4.54 (1.19–17.30) 1.98 (1.40–2.81) 2.08 (1.55–2.79) 2.37 (0.96–5.81) Reference 0.02 < 0.01 < 0.01 0.06 Insurance Provider Medicare Medicaid Private Uninsured Reference 1.20 (0.77–1.88) 0.59 (0.41–0.87) 0.74 (0.30-1.182) Reference 0.42 < 0.01 0.51 Median Income in patient zip code $ 1–42,999 $ 43,000–53,999 $ 54,000–70,999 $ ≥71,000 Reference 0.90 (0.68–1.21) 1.63 (1.07–2.49) 1.79 (1.24–2.59) Reference 0.46 0.22 < 0.01 Patient residence - Large metropolitan area with at least 1 million residents - Small metropolitan areas with less than 1 million residents - Micropolitan areas - Not metropolitan or micropolitan (nonurban residual) Reference 0.91 (0.68–1.21) 0.82 (0.61–1.10) 0.78 (0.57–1.08) Reference 0.51 0.18 0.14 Charlson Comorbidity Index Score 0 1 2 ≥ 3 Reference 1.15 (0.78–1.69) 1.63 (1.07–2.48) 1.79 (1.24–2.59) Reference 0.46 0.02 < 0.01 In-hospital procedures Colonoscopy Colectomy Parenteral nutrition 0.66 (0.53–0.83) 1.29 (0.89–1.88) 1.02 (0.58–1.82) < 0.01 0.17 0.92 Other Comorbidities Obesity Type 2 DM Alcohol use disorder History of tobacco use Opioid use disorder Vitamin D deficiency Malnutrition 0.79 (0.58–1.09) 1.22 (0.96–1.55) 1.37 (0.78–2.40) 0.20 (0.26–1.55) 0.48 (0.19–1.16) 1.82 (0.94–3.53) 0.85 (0.59–1.23) 0.15 0.09 0.25 0.12 0.10 0.07 0.40 Hospital bed size Small Medium Large Reference 1.26 (0.89–1.79) 1.37 (1.01–1.88) Reference 0.18 0.04 In-hospital Complications Shock Mechanical ventilation 1.05 (0.62–1.79) 0.95 (0.48–1.86) 0.85 0.88 Teaching hospital 1.08 (0.83–1.41) 0.54 Discussion Limited data exists on 30-day readmission rates, readmission causes and predictors following IC. Using a national database, the current investigation underscored the need for targeted interventions to reduce the burden of 30-day readmissions among IC patients. Colonoscopy during the initial admission emerges as a promising strategy to achieve this goal, with a substantial decrease in readmission risk observed in our analysis. However, further research is warranted to explain how colonoscopy influences readmission risk along with identifying optimal timing and patient selection criteria for this procedure. Additionally, our study highlights the impact of patient disposition in early readmission rates. Healthcare systems should carefully consider the impact of discharge decisions and explore strategies to ensure that patients receive appropriate post-discharge care to mitigate the risk of readmission. IC is a condition whose incidence rises significantly with age, necessitating a high degree of clinical suspicion for accurate diagnosis [ 10 ]. Studies have determined that the median age at the time of diagnosis for IC is around 71 years, with a female predominance. [ 10 – 11 ]. In our study, we observed comparable findings regarding age but not gender. The mean age at diagnosis was 70.0 years, and females constituted 26.3% of the patient population. On 30 days readmission this mean increased by 1 year of age. As individuals grow older, their susceptibility to IC increases, along with elevated mortality and morbidity rates. Several factors have been identified that increase the likelihood of developing IC, including arrhythmias, irritable bowel syndrome, prior surgical procedures, and even chronic constipation [ 10 ]. Moreover, certain predictive factors can anticipate a patient's likelihood of readmission after discharge for IC. These include shorter hospital stays, transfer to nursing care facilities or home healthcare, a CCI score of 2 or higher, and admission to larger hospitals. Of note, investigators assessing readmission rates in inflammatory bowel disease (IBD) patients revealed comparable results with our study, indicating that patients discharged to nursing facilities and home healthcare demonstrated higher readmission rates [ 6 ]. The high readmission rate among patients in those facilities could signify greater disease severity, as these services often admit more acutely affected individuals. Furthermore, our research reveals that individuals whose primary payer is private insurance and those who undergo colonoscopy experience lower chances of readmission. This phenomenon may highlight social disparities, particularly affecting low-income and disabled populations predominantly covered by Medicaid [ 6 ]. Studies in other colonic disorders have shown that Medicaid-insured individuals belonging to historically disadvantaged racial groups are less likely to receive surgical treatment for severe cases of IBD and face prolonged wait times for essential procedures [ 6 ]. Consequently, this situation likely leads to diminished quality of life and increased mortality rates, potentially explaining what was observed presently in IC patients. Following a patient's discharge with an admission index for IC, our study revealed that sepsis predominantly contributed to their readmissions. In cases of severe ischemia, there is a potential for tissue necrosis to develop [ 13 ]. This increases the likelihood of critical complications, including perforation and infection that can lead to sepsis. The timely administration of intravenous fluids and a broad-spectrum antibiotic regimen targeting aerobic and anaerobic pathogens can effectively mitigate the risk of developing sepsis [ 2 ]. If this complication is not addressed appropriately, often necessitates immediate surgical intervention. The choice of surgical intervention depends on the severity and duration of ischemia, with more extensive bowel resection being necessary in some instances [ 2 ]. To determine the appropriate extent of bowel resection, preoperative imaging or endoscopy is crucial in assessing the extent of the disease [ 2 ]. It is notable that ischemia typically affects the mucosa or submucosa, and the serosa may appear normal, making it an unreliable indicator of the actual extent of the disease [ 2 ]. In cases of severe ischemic colitis, surgical intervention may significantly elevate the risk of early readmission. Further studies dedicated to exploring this issue specifically in the context of ischemic colitis are needed for a more comprehensive understanding. The present study reveals a notable correlation between an extended LOS and an increased rate of 30-day readmissions, which subsequently impacts prognosis and mortality. In fact, most IC-related deaths occur within the initial 90 days following diagnosis, highlighting the importance of close monitoring during this period [ 5 ]. This observation aligns with our findings, as we found a considerable death rate during their initial hospitalization and within 30 days post-discharge. Some studies estimate mortality rate for IC around 10% in patient with recent history of cardiovascular surgery and severe mucosal changes seen in urgent colonoscopies, although this rate can surge to 55% in cases necessitating surgical intervention [ 14 ]. However, our study reported lower rates with a mortality rate of 4.7% for initial admissions and 4.0% during readmission. Patients with mild to moderate IC demonstrated better prognosis and lower mortality rates. Furthermore, other studies have suggested that colonoscopy staging can be a valuable predictor of mortality [ 14 ]. Our research highlights the significance of colonoscopy in reducing readmissions, as it aids in measuring the severity of IC and subsequently guides treatment strategies to provide optimal outcomes. The economic impact of 30-day readmissions for all diseases is significant for hospitals and health systems with an estimated cost in the tens of billions and Medicare beneficiaries bearing a significant portion of this burden [ 15 ]. In current investigation, IC was not the exception, impacting the total economic burden with $ 12 million in total costs and $ 51.4 million in total charges. Hospital acquired infections are well known for their impact in health care cost and research in other colonic disorders have consistently identified flares and infection as the leading cause of 30-day readmissions, as in the case of IBD [ 16 ]. In our study, sepsis emerged as the predominant factor contributing to 30-day readmission for IC. Limited research has addressed factors linked to a heightened risk of readmission for patients with IC. In contrast, numerous studies have identified various factors associated with increased readmission rates in patients with IBD. These factors surround an extended LOS, hypertension, the requirement for parenteral nutrition upon discharge, inadequate pain control management, and the presence of 2 or more comorbidities [ 16 ]. Identifying high-risk patients necessitating closer inpatient monitoring and intensifying outpatient follow-up post-discharge could significantly reduce 30-day readmissions and alleviate the economic strain of IC [ 2 – 15 ]. Therefore, our study provides important information on the most frequent causes of readmission post an index episode of IC which may provide impetus to address these factors resulting in better overall outcomes. There are advantages and disadvantages to any retrospective study that must be considered. Our study's inherent qualities and its sizable nationally representative sample are its main advantages. This is the largest study that we are aware of that examines IC readmissions over a 30-day span. Second, the NRD database uses each patient's unique ID number to identify all of their admissions as well as readmissions between hospitals in various states, eliminating duplicate records. Our study has some limitations. First, causality cannot be ascertained from the retrospective description of this data; only association can. Based on this, there is a possibility that patients with initially severe and complicated disease are more likely to be hemodynamically unstable precluding them from undergoing colonoscopy. This situation may lead to colonoscopy performance in patients with relatively mild disease, and those milder patients may naturally have lower readmission rates. Secondly, the data interval used for analysis is restricted to 2019 data. Third, the database may contain underrepresented diagnoses and comorbidities due to the reliance on ICD-10CM/PCS coding, which is prone to error. Generalizing findings is hampered by the inconsistent coding between hospitals and providers in various hospital systems, but this is lessened when we take into account the vast and varied number of patients that were part of the study. Lasty, due to the nature of the database it is technically difficult to perform a propensity score matching which would add even more validity to the results; however, the Cox multivariate regression analysis used in our study is a common statistical tool used in this type of database assessment to adjusts for confounders. Conclusion In conclusion, managing IC patients remains a complex challenge, but this investigation provides valuable insights into potential interventions and factors contributing to 30-day readmissions. Addressing these issues can enhance the quality of care for IC patients and alleviate the strain on healthcare resources. Future research should focus on prospective studies to validate these findings and guide the development of evidence-based interventions to minimize readmission post an episode of IC. Declarations Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by L.M.N, P.P.A and S.I.N. Data curation: J.K and S.K. The first draft of the manuscript was written by L.M.N and J.P.M, and all authors commented on further versions of the manuscript. Writing - review and editing: K.J.V, J.K and S.I.N. Supervision: S.K and K.J.V. All authors read and approved the final manuscript. Conflict of interest All authors have no conflict of interest to disclose for this manuscript. Acknowledgment of grant support and disclosure of financial arrangements We certify that no financial and grant support has been received for this research. Ethics Approval and Consent to Participate Given the deidentified nature of the National Readmission Database (NRD), the analysis was exempt from the Institutional Review Board (IRB) approval. Consent for publication Not applicable. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Compliance with Ethical Standards Conflict of interest All authors have no conflict of interest to disclose for this manuscript. References Theodoropoulou, Αngeliki, and Ioannis E Κoutroubakis. “Ischemic colitis: Clinical practice in diagnosis and treatment.” World Journal of Gastroenterology , vol. 14, no. 48, 2008, p. 7302, https://doi.org/10.3748/wjg.14.7302. 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D., et al. “The epidemiology of Ischaemic Colitis.” Alimentary Pharmacology & Therapeutics , vol. 19, no. 7, 2004, pp. 729–738, https://doi.org/10.1111/j.1365 2036.2004.01903.x. Yadav, Siddhant, et al. “A population-based study of incidence, risk factors, clinical spectrum, and outcomes of ischemic colitis.” Clinical Gastroenterology and Hepatology ,vol. 13, no. 4, 2015, https://doi.org/10.1016/j.cgh.2014.07.061. Poojary, Priti, et al. “Predictors of hospital readmissions for ulcerative colitis in the United States.” Inflammatory Bowel Diseases , 2017, p. 1, https://doi.org/10.1097/mib.0000000000001041. Professional, Cleveland Clinic medical. “Ischemic Colitis: Symptoms & Treatment.” Cleveland Clinic , 7 Sept. 2023, my.clevelandclinic.org/health/diseases/24513-ischemic-colitis?view=print. Lozano Maya, M., et al. “Usefulness of colonoscopy in ischemic colitis.” Revista Española de Enfermedades Digestivas , vol. 102, no. 8, 2010,https://doi.org/10.4321/s1130-01082010000800004. Fallon, Caroline. “Cost of Hospital Readmissions: What the Statistics Tell Us.” Blog , Cureatr Inc., 13 June 2023, blog.cureatr.com/cost-of-hospital-readmissions-what-thestatistics-tell-us. Nguyen, Nghia H., et al. “Rate of risk factors for and interventions to reduce hospital readmission in patients with inflammatory bowel diseases.” Clinical Gastroenterology and Hepatology , vol. 18, no. 9, 2020, https://doi.org/10.1016/j.cgh.2019.08.042. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4503996","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313313587,"identity":"94fa7a25-22d4-47c8-a52c-a4dceeec2b75","order_by":0,"name":"Sharon I. Narvaez","email":"","orcid":"","institution":"Emory School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sharon","middleName":"I.","lastName":"Narvaez","suffix":""},{"id":313313588,"identity":"20870560-9d83-4aed-b232-c4ba6f0218e8","order_by":1,"name":"John P. Martinez","email":"","orcid":"","institution":"Emory School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"P.","lastName":"Martinez","suffix":""},{"id":313313589,"identity":"214bb9f6-d64e-4fca-8718-e0464581ba1e","order_by":2,"name":"Jami Kinnucan","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Jami","middleName":"","lastName":"Kinnucan","suffix":""},{"id":313313590,"identity":"cea13160-992b-4786-84c3-53bdfe7b2e81","order_by":3,"name":"Steven Keilin","email":"","orcid":"","institution":"Emory School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Steven","middleName":"","lastName":"Keilin","suffix":""},{"id":313313591,"identity":"77c69a16-b0b5-4a61-8577-6cb8d30ff74d","order_by":4,"name":"Kenneth J. Vega","email":"","orcid":"","institution":"Augusta University","correspondingAuthor":false,"prefix":"","firstName":"Kenneth","middleName":"J.","lastName":"Vega","suffix":""},{"id":313313592,"identity":"3c94c498-36eb-4806-9a3f-a526cf0a8db0","order_by":5,"name":"Pedro Palacios Argueta","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Pedro","middleName":"Palacios","lastName":"Argueta","suffix":""},{"id":313313593,"identity":"01fc3aa0-c296-473f-9ecb-0092f2bda671","order_by":6,"name":"Luis M. Nieto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACPgbGBiAlAcTMB2CCBni1sMG08DCwJRCrBQp4GHjgKglokUhu/sC4w0LOnr3n46MbFfcSG9ibt0ng15LYJsF4RsKYh+fsZuOcM8WJDTzHyghqYWBsk0jskcjdJp3blpDYIJFjRkgL0GFtEvU9EjnPf4O1yL8hqKVBAqglgUcih40ZYgsPAS08D9tA3jHsOXPMWDrnTIJxG09asQU+Lfzs6Y8/fGyrk2dvb374OaciQbaf/fDGG/i0gEECEtuxjaBydGBPso5RMApGwSgY9gAAxOFAsyVDQ6oAAAAASUVORK5CYII=","orcid":"","institution":"Emory School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Luis","middleName":"M.","lastName":"Nieto","suffix":""}],"badges":[],"createdAt":"2024-05-30 15:21:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4503996/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4503996/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58872238,"identity":"98457290-60b3-4cc4-ae30-e33e9db28eca","added_by":"auto","created_at":"2024-06-22 20:01:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1020258,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503996/v1/ad259a30-78d0-4fa9-a2d8-33479bf8940f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Thirty‑Day Readmission Rates and Outcomes after hospitalization for Ischemic Colitis. A National Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIschemic colitis (IC) is the primary etiology from intestinal ischemia, with a prevalence that significantly increases with advancing age [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Its occurrence varies between 4.5 to 44 per 100,000 person-years [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It constitutes a meaningful proportion of hospital admissions, seen in approximately 1 in 2000 individuals admitted to hospitals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. IC consists of a range of clinical syndromes attributed to vascular occlusive or non-occlusive pathologies marked by inadequacies in colonic blood perfusion [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This damage can extend from a mild inflammation process to full thickness necrosis. The gold standard for diagnosing IC includes colonoscopy and histopathological biopsy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Most patients exhibit favorable response to conservative medical treatment; however, surgical intervention becomes necessary in approximately one of every five patients [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Management of IC patients continues to pose a considerable challenge to healthcare systems. Unfortunately, there is a lack of studies addressing the challenges of this gastrointestinal (GI) disorder. A major obstacle is disparities between patients with this condition and the lack of research in this area. Studies of other gastrointestinal diseases have revealed that patients with worse outcomes, early readmissions, and higher mortality are more commonly seen with certain kind of health insurance, which may be related to access of medical care [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIC prognosis can vary depending on several factors, including disease location, presence of other medical conditions, and whether surgical intervention is needed [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. It is important that the overall mortality rate associated with this condition is approximately 22% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, it is essential to emphasize that the severity of the disease and the likelihood of a fatal outcome tend to be higher when IC occurs on the right side of the colon [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Risk factors include a patient's medical history, including a prior cerebrovascular disease, abdominal surgical interventions, hyperlipidemia, and malignancies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These comorbidities, acting as independent risk factors, exert notable influence on the duration of hospitalization, varying from one week to two weeks [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Timely and accurately identifying IC is critical in mitigating length of stay (LOS) and diminishing the likelihood of readmission. The 30-day readmission rate has garnered heightened attention from healthcare administrators and medical professionals due to its significance in assessing hospital effectiveness and its correlation with elevated healthcare expenditures [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. It is worth noting that Medicare bears a substantial financial burden, with an estimated annual expenditure of tens of billions attributable to readmissions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The aim of the current investigation is to identify 30-day readmission rate, readmission causes, and predictors of readmission in ischemic colitis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA retrospective cohort study using the 2019 National Readmission Database (NRD) of adult patients that had an index admission (IA) for IC from the month of January to November and were readmitted within 30-days of discharge was performed. International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10CM/PCS) codes were utilized to identify diagnosis and procedures. Admitting hospital for IA and readmission was categorized by ownership control, bed capacity, academic standing, urban/rural location, and geographic region. Next, a 20% probability sample of every hospital in each collection was gathered. For every patient listed in the NRD database, a unique ID was assigned. This ID was useful to identify all patient admissions made inside the data set between January and November 2019. The additional data included all of the ICD-10CM/PCS codes.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Outcomes\u003c/h2\u003e \u003cp\u003eThe primary outcome was the 30-day hospital readmission rate from any cause. Secondary outcomes were mortality, resource utilization (length of stay (LOS), total hospitalization costs and charges) associated with readmission. Additionally, the top ten reasons for readmission was identified during the study period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDefinitions of Variables\u003c/h2\u003e \u003cp\u003ePatient demographics along with data of interest was obtained from the NRD. Information obtained included age (years), gender, primary payer (Medicare, medicated, private, uninsured), residence (large metropolitan areas with a population of at least one million, small metropolitan areas with a population of less than one million, micropolitan areas (nonurban residual), and not metropolitan or micropolitan), hospital size (small, medium, and large) based on bed count, and teaching status. ICD10-CM/PCS codes were used to acquire primary diagnosis, comorbidities, and procedures performed during IA along with readmission. Sundararajan's adaptation of the modified Deyo's Charlson Comorbidity Index (CCI) was employed to evaluate the comorbidity burden [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Cox regression analysis was used to find independent risk factors for readmission. Hospital-specific cost-charge ratios based on inpatient all-payer costs are provided by the NRD. The hospital accounting reports provides the Centers for Medicare and Medicaid Services with this cost data. Total hospital costs were determined by multiplying the total hospital charges by the associated cost-to-charge ratio.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eSTATA, version 16 (StataCorp, College Station, TX) was used to perform the statistical analysis. To get estimates for the total population of hospitalized patients with IC in the US, weighting of patient-level observations was used. The primary and secondary outcomes' unadjusted odds ratios were determined by univariate Cox regression analysis. Multivariable Cox regression analysis was then employed to correct for potential confounders in the results. All confounders that were significantly associated with the outcome on univariable analysis with a cutoff P value of 0.20 were included in the multivariable regression models. Fisher exact test was used to compare proportions, and Student t-test was used to compare continuous variables. Every P-value was two-sided, and the statistical significance threshold was set at 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eGeneral Characteristics\u003c/h2\u003e \u003cp\u003eA total of 6,853 patients with diagnosis of IC were identified in 2019. The mean age was 70.0 years of age, 26.3% of patients were female, Medicare was the most common health insurance, 22.7% of patients were from the lowest quartile of income, more than half of the patients resided in large metropolitan areas with at least 1\u0026nbsp;million residents, 30.3% of patients had a CCI score of \u0026ge;\u0026thinsp;3, 15.2% of patients had obesity and more than a quarter of the patients had type 2 diabetes mellitus as a comorbidity. In addition, 8.8% and 3.1% of patients had registered malnutrition and alcohol use disorder (AUD), respectively. More than 68% of the patients were treated at urban-teaching hospitals. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the items above as well as provides further detail about the IA group with IC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient characteristics (N\u0026thinsp;=\u0026thinsp;6,853)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,802 (26.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years (Mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.0 (69.6\u0026ndash;70.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisposition of patient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDischarged to home or self-care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,612 (67.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShort-term hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (0.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkilled nursing facility/intermediate care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e877 (12.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome health care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e973 (14.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgainst medical advice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e322 (4.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsurance provider\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,996 (72.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e418 (6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,343 (19.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUninsured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Income in patient zip code\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e1\u0026ndash;42,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,556 (22.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e43,000\u0026ndash;53,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,843 (26.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e54,000\u0026ndash;70,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,946 (28.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e\u0026ge;71,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,508 (22.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge metropolitan area with at least 1\u0026nbsp;million residents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,543 (51.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall metropolitan areas with less than 1\u0026nbsp;million residents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,666 (38.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicropolitan areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500 (7.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot metropolitan or micropolitan (nonurban residual)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharlson Comorbidity Index Score (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,974 (28.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,652 (24.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,151 (16.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,076 (30.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Bed size (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,597 (23.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,090 (30.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,166 (46.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-hospital procedures (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColonoscopy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,960 (43.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime Colonoscopy (Mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1 (1.9\u0026ndash;2.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e583 (8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime Colectomy (Mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1 (1.6\u0026ndash;2.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParenteral nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 (2.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-hospital complications (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e254 (3.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTransfer to Rehab (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther Comorbidities (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e212 (3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannabis use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalnutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e603 (8.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,042 (15.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e459 (6.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e850 (12.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,830 (26.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVit D deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVit B12 deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTeaching Status (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,701 (68.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrban hospital (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,338 (77.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth-care related usage (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS (days), mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7 (5.5\u0026ndash;5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharges (\u003cspan\u003e$\u003c/span\u003e), mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65,118.0 (60,770.1\u0026ndash;69,465.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost (\u003cspan\u003e$\u003c/span\u003e), mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,321.2 (15,428.4\u0026ndash;17,214.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eThirty-Day All‑Cause Hospital Readmission\u003c/h2\u003e \u003cp\u003eA total of 762 patients (11.0%) were readmitted in 30 days after hospital discharge. The primary cause for readmission was sepsis (32.5%) followed by vascular disorder of the intestine (14.2%) and acute kidney injury (4.9%). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e contains a list of the top ten readmission diagnoses after IA for IC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop ten causes of readmission\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICD 10 CM code\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e453 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular disorder of intestine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312 (40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK559\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute kidney failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188 (24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN179\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterocolitis due to Clostridium difficile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA0472\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic vascular disorders of intestine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e156 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK551\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNoninfective gastroenteritis and colitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e155 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK529\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnspecified intestinal obstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK56609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJ189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertensive heart disease with heart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eIn‑Hospital and 30‑Day Mortality Rates Among Index Admission\u003c/h2\u003e \u003cp\u003eA total of 325 patients died during the IA for IC with an additional 30 patients that died within 30 days of discharge. The respective mortality rates for IA and readmission were 4.7% and 4.0%; however, it was not statistically significant (P\u0026thinsp;=\u0026thinsp;0.79).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eReadmitted Patients Versus Index Admission Patients\u003c/h2\u003e \u003cp\u003eReadmitted patients were older (71.0 years vs. 70.0 years; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with an increased proportion of females (32.0% vs. 25.5%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Readmitted patients were more likely to have Medicare as primary health insurance 79.9% vs. 71.9%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01), to be from the lowest quartile of income (27.7% vs. 22.1%; P 0.02), have a CCI score\u0026thinsp;\u0026ge;\u0026thinsp;3 (17.8% vs. 11.6%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01), underlying type 2 DM (37.0% vs. 25.5%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01), malnutrition (13.4% vs. 8.2%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and secondary diagnosis of AUD (4.8% vs. 2.8%; P\u0026thinsp;=\u0026thinsp;0.04). There was no difference in the proportion of patients admitted at teaching hospitals (72.6% vs. 68.1% P\u0026thinsp;=\u0026thinsp;0.08) or proportion of patients with underlying obesity between groups (13.8% vs. 15.3%; P\u0026thinsp;=\u0026thinsp;0.47). Readmitted patients with CCI\u0026thinsp;\u0026ge;\u0026thinsp;3 had increased morbidity compared to CCI of \u0026lt;\u0026thinsp;3 (46.2% vs. 28.4%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Furthermore, readmitted patients were less likely to have an inpatient colonoscopy (32.3% vs. 44.6%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01), but most likely to have parenteral nutrition support (5.3% vs. 2.1%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and colectomy (17.5% vs. 7.3%; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01). There was no difference in having tobacco, cannabis or opioid use disorders between both groups. The results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e General characteristics of index admission vs. readmitted patients after index admission for ischemic colitis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndex Admission\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReadmitted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (N\u0026thinsp;=\u0026thinsp;1,802) %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(460) 25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(577) 32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years (mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisposition (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShort-term hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgainst medical advice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDischarged to another institution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome Health Care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsurance provider (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUninsured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharlson Comorbidity Index Score (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Income in patient zip code (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e1\u0026ndash;42,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e43,000\u0026ndash;53,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e54,000\u0026ndash;70,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e\u0026ge;71,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient residence (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge metropolitan area with at least 1\u0026nbsp;million residents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall metropolitan areas with less than 1\u0026nbsp;million residents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicropolitan areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot metropolitan or micropolitan (nonurban residual)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Procedures (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParenteral nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColonoscopy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-hospital complications (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther comorbidities (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannabis use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOpioid use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType 2 DM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalnutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVit D deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVit B12 deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Size (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTeaching status (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrban hospital (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth-care related usage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS (days), mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharges (\u003cspan\u003e$\u003c/span\u003e), mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65,118.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67,423.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost (\u003cspan\u003e$\u003c/span\u003e), mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,321.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,786.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality rate (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e325 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMorbidity Among Readmitted Patients Versus Index Admission Patients\u003c/h2\u003e \u003cp\u003eThe percentage of patients who experienced respiratory failure and needed mechanical ventilation (2.2% vs. 1.2%; P\u0026thinsp;=\u0026thinsp;0.08) and those who experienced shock of any kind (5.0% vs. 3.6%; P\u0026thinsp;=\u0026thinsp;0.19) did not differ between readmitted patients and IA patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHealth Care Burden of Readmission\u003c/h2\u003e \u003cp\u003eThe hospital LOS for readmitted patients was 6.4 (6.2\u0026ndash;6.6) days which was longer than the index admission (5.7 days [5.5\u0026ndash;5.9]; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The mean hospital costs of readmission were \u003cspan\u003e$\u003c/span\u003e15,786 which was lower than those of the index admissions \u003cspan\u003e$\u003c/span\u003e16,32; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The mean hospitalization charges for readmission were \u003cspan\u003e$\u003c/span\u003e67,423 which was higher than the index admission \u003cspan\u003e$\u003c/span\u003e65,118; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The total economic burden of readmission was \u003cspan\u003e$\u003c/span\u003e12\u0026nbsp;million in total costs and \u003cspan\u003e$\u003c/span\u003e51.4\u0026nbsp;million in total charges.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eIndependent Predictors of Readmission\u003c/h2\u003e \u003cp\u003eUsing univariate Cox regression analysis, the degree of association between readmission and various variables, such as patient, hospital, comorbidities, and treatment-level, was examined separately. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e displays the final Cox multivariate regression analysis, which only included variables with P\u0026thinsp;\u0026le;\u0026thinsp;0.20. Independent predictors of readmission were patients discharged to short term hospital (aHR:4.54, P\u0026thinsp;=\u0026thinsp;0.02), skilled nursing facility (aHR:1.98, P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and home health care (aHR:2.08, P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01), a Charlson comorbidity index score\u0026thinsp;\u0026ge;\u0026thinsp;2 (aHR:1.63, P\u0026thinsp;=\u0026thinsp;0.02) and being admitted at large size hospital (aHR:1.37, P\u0026thinsp;=\u0026thinsp;0.04). Having private insurance as primary payer (aHR:0.59, P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and undergoing to colonoscopy at IA (aHR:0.66, P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were associated with lower odds of readmission.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIndependent Predictors of 30-days readmission using Cox multivariate regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHazard ratio (95% confidence interval)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92 (0.72\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.98 (0.97\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisposition of patient\u003c/b\u003e\u003c/p\u003e \u003cp\u003e- Discharged to home or self-care\u003c/p\u003e \u003cp\u003e- Short-term hospital\u003c/p\u003e \u003cp\u003e- Skilled nursing facility/intermediate care\u003c/p\u003e \u003cp\u003e- Home health care\u003c/p\u003e \u003cp\u003e- Against medical advice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e4.54 (1.19\u0026ndash;17.30)\u003c/p\u003e \u003cp\u003e1.98 (1.40\u0026ndash;2.81)\u003c/p\u003e \u003cp\u003e2.08 (1.55\u0026ndash;2.79)\u003c/p\u003e \u003cp\u003e2.37 (0.96\u0026ndash;5.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsurance Provider\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003cp\u003eUninsured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.20 (0.77\u0026ndash;1.88)\u003c/p\u003e \u003cp\u003e0.59 (0.41\u0026ndash;0.87)\u003c/p\u003e \u003cp\u003e0.74 (0.30-1.182)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.42\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Income in patient zip code\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e1\u0026ndash;42,999\u003c/p\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e43,000\u0026ndash;53,999\u003c/p\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e54,000\u0026ndash;70,999\u003c/p\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e\u0026ge;71,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.90 (0.68\u0026ndash;1.21)\u003c/p\u003e \u003cp\u003e1.63 (1.07\u0026ndash;2.49)\u003c/p\u003e \u003cp\u003e1.79 (1.24\u0026ndash;2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.46\u003c/p\u003e \u003cp\u003e0.22\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient residence\u003c/b\u003e\u003c/p\u003e \u003cp\u003e- Large metropolitan area with at least 1\u0026nbsp;million residents\u003c/p\u003e \u003cp\u003e- Small metropolitan areas with less than 1\u0026nbsp;million residents\u003c/p\u003e\u003cp\u003e- Micropolitan areas\u003c/p\u003e\u003cp\u003e- Not metropolitan or micropolitan (nonurban residual)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.91 (0.68\u0026ndash;1.21)\u003c/p\u003e \u003cp\u003e0.82 (0.61\u0026ndash;1.10)\u003c/p\u003e \u003cp\u003e0.78 (0.57\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.51\u003c/p\u003e \u003cp\u003e0.18\u003c/p\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharlson Comorbidity Index Score\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.15 (0.78\u0026ndash;1.69)\u003c/p\u003e \u003cp\u003e1.63 (1.07\u0026ndash;2.48)\u003c/p\u003e \u003cp\u003e1.79 (1.24\u0026ndash;2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.46\u003c/p\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-hospital procedures\u003c/b\u003e\u003c/p\u003e \u003cp\u003eColonoscopy\u003c/p\u003e \u003cp\u003eColectomy\u003c/p\u003e \u003cp\u003eParenteral nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.66 (0.53\u0026ndash;0.83)\u003c/p\u003e \u003cp\u003e1.29 (0.89\u0026ndash;1.88)\u003c/p\u003e \u003cp\u003e1.02 (0.58\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003cp\u003e0.17\u003c/p\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther Comorbidities\u003c/b\u003e\u003c/p\u003e \u003cp\u003eObesity\u003c/p\u003e \u003cp\u003eType 2 DM\u003c/p\u003e \u003cp\u003eAlcohol use disorder\u003c/p\u003e \u003cp\u003eHistory of tobacco use\u003c/p\u003e \u003cp\u003eOpioid use disorder\u003c/p\u003e \u003cp\u003eVitamin D deficiency\u003c/p\u003e \u003cp\u003eMalnutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.79 (0.58\u0026ndash;1.09)\u003c/p\u003e \u003cp\u003e1.22 (0.96\u0026ndash;1.55)\u003c/p\u003e \u003cp\u003e1.37 (0.78\u0026ndash;2.40)\u003c/p\u003e \u003cp\u003e0.20 (0.26\u0026ndash;1.55)\u003c/p\u003e \u003cp\u003e0.48 (0.19\u0026ndash;1.16)\u003c/p\u003e \u003cp\u003e1.82 (0.94\u0026ndash;3.53)\u003c/p\u003e \u003cp\u003e0.85 (0.59\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003cp\u003e0.09\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003cp\u003e0.12\u003c/p\u003e \u003cp\u003e0.10\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital bed size\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSmall\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.26 (0.89\u0026ndash;1.79)\u003c/p\u003e \u003cp\u003e1.37 (1.01\u0026ndash;1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.18\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-hospital Complications\u003c/b\u003e\u003c/p\u003e \u003cp\u003eShock\u003c/p\u003e \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05 (0.62\u0026ndash;1.79)\u003c/p\u003e \u003cp\u003e0.95 (0.48\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTeaching hospital\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.08 (0.83\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLimited data exists on 30-day readmission rates, readmission causes and predictors following IC. Using a national database, the current investigation underscored the need for targeted interventions to reduce the burden of 30-day readmissions among IC patients. Colonoscopy during the initial admission emerges as a promising strategy to achieve this goal, with a substantial decrease in readmission risk observed in our analysis. However, further research is warranted to explain how colonoscopy influences readmission risk along with identifying optimal timing and patient selection criteria for this procedure. Additionally, our study highlights the impact of patient disposition in early readmission rates. Healthcare systems should carefully consider the impact of discharge decisions and explore strategies to ensure that patients receive appropriate post-discharge care to mitigate the risk of readmission.\u003c/p\u003e \u003cp\u003eIC is a condition whose incidence rises significantly with age, necessitating a high degree of clinical suspicion for accurate diagnosis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Studies have determined that the median age at the time of diagnosis for IC is around 71 years, with a female predominance. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In our study, we observed comparable findings regarding age but not gender. The mean age at diagnosis was 70.0 years, and females constituted 26.3% of the patient population. On 30 days readmission this mean increased by 1 year of age. As individuals grow older, their susceptibility to IC increases, along with elevated mortality and morbidity rates. Several factors have been identified that increase the likelihood of developing IC, including arrhythmias, irritable bowel syndrome, prior surgical procedures, and even chronic constipation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Moreover, certain predictive factors can anticipate a patient's likelihood of readmission after discharge for IC. These include shorter hospital stays, transfer to nursing care facilities or home healthcare, a CCI score of 2 or higher, and admission to larger hospitals. Of note, investigators assessing readmission rates in inflammatory bowel disease (IBD) patients revealed comparable results with our study, indicating that patients discharged to nursing facilities and home healthcare demonstrated higher readmission rates [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The high readmission rate among patients in those facilities could signify greater disease severity, as these services often admit more acutely affected individuals. Furthermore, our research reveals that individuals whose primary payer is private insurance and those who undergo colonoscopy experience lower chances of readmission. This phenomenon may highlight social disparities, particularly affecting low-income and disabled populations predominantly covered by Medicaid [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Studies in other colonic disorders have shown that Medicaid-insured individuals belonging to historically disadvantaged racial groups are less likely to receive surgical treatment for severe cases of IBD and face prolonged wait times for essential procedures [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Consequently, this situation likely leads to diminished quality of life and increased mortality rates, potentially explaining what was observed presently in IC patients.\u003c/p\u003e \u003cp\u003eFollowing a patient's discharge with an admission index for IC, our study revealed that sepsis predominantly contributed to their readmissions. In cases of severe ischemia, there is a potential for tissue necrosis to develop [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This increases the likelihood of critical complications, including perforation and infection that can lead to sepsis. The timely administration of intravenous fluids and a broad-spectrum antibiotic regimen targeting aerobic and anaerobic pathogens can effectively mitigate the risk of developing sepsis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. If this complication is not addressed appropriately, often necessitates immediate surgical intervention. The choice of surgical intervention depends on the severity and duration of ischemia, with more extensive bowel resection being necessary in some instances [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. To determine the appropriate extent of bowel resection, preoperative imaging or endoscopy is crucial in assessing the extent of the disease [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is notable that ischemia typically affects the mucosa or submucosa, and the serosa may appear normal, making it an unreliable indicator of the actual extent of the disease [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In cases of severe ischemic colitis, surgical intervention may significantly elevate the risk of early readmission. Further studies dedicated to exploring this issue specifically in the context of ischemic colitis are needed for a more comprehensive understanding.\u003c/p\u003e \u003cp\u003eThe present study reveals a notable correlation between an extended LOS and an increased rate of 30-day readmissions, which subsequently impacts prognosis and mortality. In fact, most IC-related deaths occur within the initial 90 days following diagnosis, highlighting the importance of close monitoring during this period [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This observation aligns with our findings, as we found a considerable death rate during their initial hospitalization and within 30 days post-discharge. Some studies estimate mortality rate for IC around 10% in patient with recent history of cardiovascular surgery and severe mucosal changes seen in urgent colonoscopies, although this rate can surge to 55% in cases necessitating surgical intervention [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, our study reported lower rates with a mortality rate of 4.7% for initial admissions and 4.0% during readmission. Patients with mild to moderate IC demonstrated better prognosis and lower mortality rates. Furthermore, other studies have suggested that colonoscopy staging can be a valuable predictor of mortality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our research highlights the significance of colonoscopy in reducing readmissions, as it aids in measuring the severity of IC and subsequently guides treatment strategies to provide optimal outcomes.\u003c/p\u003e \u003cp\u003eThe economic impact of 30-day readmissions for all diseases is significant for hospitals and health systems with an estimated cost in the tens of billions and Medicare beneficiaries bearing a significant portion of this burden [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In current investigation, IC was not the exception, impacting the total economic burden with \u003cspan\u003e$\u003c/span\u003e12\u0026nbsp;million in total costs and \u003cspan\u003e$\u003c/span\u003e51.4\u0026nbsp;million in total charges. Hospital acquired infections are well known for their impact in health care cost and research in other colonic disorders have consistently identified flares and infection as the leading cause of 30-day readmissions, as in the case of IBD [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In our study, sepsis emerged as the predominant factor contributing to 30-day readmission for IC. Limited research has addressed factors linked to a heightened risk of readmission for patients with IC. In contrast, numerous studies have identified various factors associated with increased readmission rates in patients with IBD. These factors surround an extended LOS, hypertension, the requirement for parenteral nutrition upon discharge, inadequate pain control management, and the presence of 2 or more comorbidities [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Identifying high-risk patients necessitating closer inpatient monitoring and intensifying outpatient follow-up post-discharge could significantly reduce 30-day readmissions and alleviate the economic strain of IC [\u003cspan additionalcitationids=\"CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, our study provides important information on the most frequent causes of readmission post an index episode of IC which may provide impetus to address these factors resulting in better overall outcomes.\u003c/p\u003e \u003cp\u003eThere are advantages and disadvantages to any retrospective study that must be considered. Our study's inherent qualities and its sizable nationally representative sample are its main advantages. This is the largest study that we are aware of that examines IC readmissions over a 30-day span. Second, the NRD database uses each patient's unique ID number to identify all of their admissions as well as readmissions between hospitals in various states, eliminating duplicate records. Our study has some limitations. First, causality cannot be ascertained from the retrospective description of this data; only association can. Based on this, there is a possibility that patients with initially severe and complicated disease are more likely to be hemodynamically unstable precluding them from undergoing colonoscopy. This situation may lead to colonoscopy performance in patients with relatively mild disease, and those milder patients may naturally have lower readmission rates. Secondly, the data interval used for analysis is restricted to 2019 data. Third, the database may contain underrepresented diagnoses and comorbidities due to the reliance on ICD-10CM/PCS coding, which is prone to error. Generalizing findings is hampered by the inconsistent coding between hospitals and providers in various hospital systems, but this is lessened when we take into account the vast and varied number of patients that were part of the study. Lasty, due to the nature of the database it is technically difficult to perform a propensity score matching which would add even more validity to the results; however, the Cox multivariate regression analysis used in our study is a common statistical tool used in this type of database assessment to adjusts for confounders.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, managing IC patients remains a complex challenge, but this investigation provides valuable insights into potential interventions and factors contributing to 30-day readmissions. Addressing these issues can enhance the quality of care for IC patients and alleviate the strain on healthcare resources. Future research should focus on prospective studies to validate these findings and guide the development of evidence-based interventions to minimize readmission post an episode of IC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by L.M.N, P.P.A and S.I.N. Data curation: J.K and S.K. The first draft of the manuscript was written by L.M.N and J.P.M, and all authors commented on further versions of the manuscript. Writing - review and editing: K.J.V, J.K and S.I.N. Supervision: S.K and K.J.V. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have no conflict of interest to disclose for this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment of grant support\u003c/strong\u003e \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003edisclosure of financial arrangements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe certify that no financial and grant support has been received for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the deidentified nature of the National Readmission Database (NRD), the analysis was exempt from the Institutional Review Board (IRB) approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eAll authors have no conflict of interest to disclose for this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eTheodoropoulou, \u0026Alpha;ngeliki, and Ioannis E \u0026Kappa;outroubakis. \u0026ldquo;Ischemic colitis: Clinical practice in diagnosis and treatment.\u0026rdquo; \u003cem\u003eWorld Journal of Gastroenterology\u003c/em\u003e, vol. 14, no. 48, 2008, p. 7302, https://doi.org/10.3748/wjg.14.7302.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWashington, Christopher, and Joseph Carmichael. \u0026ldquo;Management of ischemic colitis.\u0026rdquo;\u0026nbsp;\u003cem\u003eClinics in Colon and Rectal Surgery\u003c/em\u003e, vol. 25, no. 04, 2012, pp. 228\u0026ndash;235, https://doi.org/10.1055/s-0032-1329534.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eXu, YuShuang, et al. \u0026ldquo;Diagnostic methods and drug therapies in patients with ischemic colitis.\u0026rdquo;\u0026nbsp;\u003cem\u003eInternational Journal of Colorectal Disease\u003c/em\u003e, vol. 36, no. 1, 2020, pp. 47\u0026ndash;56, https://doi.org/10.1007/s00384-020-03739-z.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHernandez III, Luis, and James FitzGerald. \u0026ldquo;Ischemic colitis.\u0026rdquo;\u0026nbsp;\u003cem\u003eClinics in Colon and Rectal Surgery\u003c/em\u003e, vol. 28, no. 02, 2015, pp. 093\u0026ndash;098, https://doi.org/10.1055/s-0035 1549099.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePeixoto, Armando, et al. \u0026ldquo;Predictive factors of short‐term mortality in ischaemic colitis and development of a new prognostic scoring model of in‐hospital mortality.\u0026rdquo;\u0026nbsp;\u003cem\u003eUnited European Gastroenterology Journal\u003c/em\u003e, vol. 5, no. 3, 2017, pp. 432\u0026ndash;439, https://doi.org/10.1177/2050640616658219.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eShah, Shamita, et al. \u0026ldquo;Racial and ethnic disparities in patients with inflammatory bowel disease: An online survey.\u0026rdquo;\u0026nbsp;\u003cem\u003eInflammatory Bowel Diseases\u003c/em\u003e, 2023, https://doi.org/10.1093/ibd/izad194.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMouchtouris, Nikolaos, et al. \u0026ldquo;Predictors of 30-day hospital readmission after mechanical thrombectomy for acute ischemic stroke.\u0026rdquo;\u0026nbsp;\u003cem\u003eJournal of Neurosurgery\u003c/em\u003e, vol. 134, no. 5, 2021, pp. 1500\u0026ndash;1504, https://doi.org/10.3171/2020.2.jns193249.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHuang, Haosu, et al. \u0026ldquo;Factors influencing hospital stay duration for patients with mild ischemic colitis: A retrospective study.\u0026rdquo;\u0026nbsp;\u003cem\u003eEuropean Journal of Medical Research\u003c/em\u003e, vol. 27, no. 1, 2022, https://doi.org/10.1186/s40001-022-00665-4.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSundararajan V, Quan H, Halfon P, Fushimi K, Luthi JC, Burnand B, et al. Cross-national comparative performance of three versions of the ICD-10 Charlson index. Med Care. 2007;45(12):1210-5.\u003c/li\u003e\n \u003cli\u003eHiggins, P. D., et al. \u0026ldquo;The epidemiology of Ischaemic Colitis.\u0026rdquo;\u0026nbsp;\u003cem\u003eAlimentary Pharmacology \u0026amp;amp; Therapeutics\u003c/em\u003e, vol. 19, no. 7, 2004, pp. 729\u0026ndash;738, https://doi.org/10.1111/j.1365 2036.2004.01903.x.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eYadav, Siddhant, et al. \u0026ldquo;A population-based study of incidence, risk factors, clinical spectrum, and outcomes of ischemic colitis.\u0026rdquo;\u0026nbsp;\u003cem\u003eClinical Gastroenterology and Hepatology\u003c/em\u003e,vol. 13, no. 4, 2015, https://doi.org/10.1016/j.cgh.2014.07.061.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePoojary, Priti, et al. \u0026ldquo;Predictors of hospital readmissions for ulcerative colitis in the United States.\u0026rdquo;\u0026nbsp;\u003cem\u003eInflammatory Bowel Diseases\u003c/em\u003e, 2017, p. 1, https://doi.org/10.1097/mib.0000000000001041.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eProfessional, Cleveland Clinic medical. \u0026ldquo;Ischemic Colitis: Symptoms \u0026amp; Treatment.\u0026rdquo;\u0026nbsp;\u003cem\u003eCleveland Clinic\u003c/em\u003e, 7 Sept. 2023, my.clevelandclinic.org/health/diseases/24513-ischemic-colitis?view=print.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLozano Maya, M., et al. \u0026ldquo;Usefulness of colonoscopy in ischemic colitis.\u0026rdquo;\u0026nbsp;\u003cem\u003eRevista Espa\u0026ntilde;ola de Enfermedades Digestivas\u003c/em\u003e, vol. 102, no. 8, 2010,https://doi.org/10.4321/s1130-01082010000800004.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFallon, Caroline. \u0026ldquo;Cost of Hospital Readmissions: What the Statistics Tell Us.\u0026rdquo; \u003cem\u003eBlog\u003c/em\u003e, Cureatr Inc., 13 June 2023, blog.cureatr.com/cost-of-hospital-readmissions-what-thestatistics-tell-us.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNguyen, Nghia H., et al. \u0026ldquo;Rate of risk factors for and interventions to reduce hospital readmission in patients with inflammatory bowel diseases.\u0026rdquo; \u003cem\u003eClinical Gastroenterology and Hepatology\u003c/em\u003e, vol. 18, no. 9, 2020, https://doi.org/10.1016/j.cgh.2019.08.042.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\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":"Ischemic Colitis, 30-day Readmission, Common Causes of Readmission, Predictors of readmission","lastPublishedDoi":"10.21203/rs.3.rs-4503996/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4503996/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Aim\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLimited data exists on 30-day readmission rates, readmission causes and predictors following Ischemic Colitis (IC). The aim is to identify etiologies for the above using a national database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective cohort study using the 2019 National Readmission Database (NRD) of adult patients with an index admission (IA) for IC from January to November and were readmitted within 30 days of discharge was performed. The primary outcome was readmission of any cause. Secondary outcomes were mortality and resource utilization associated with readmission. Independent risk factors for all-cause readmission were identified using Cox regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 6,853 IC patients were identified. Readmission within 30 days occurred in 762 (11%). The primary readmission cause was sepsis. A total of 325 patients died during the IA and additional 30 patients died within 30 days of discharge. Independent predictors of readmission were discharge to short term hospital, a Charlson comorbidity index score ≥ 2 and admission at large size hospital. Having private insurance and undergoing colonoscopy were associated with lower readmission odds. Economic burden of readmission was $12\u0026nbsp;million in total costs and $51.4\u0026nbsp;million in total charges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong admitted IC patients, 30-day readmission rate was 11% with half of those secondary to sepsis. Undergoing colonoscopy during the IA is associated with 34% less risk of readmission and disposition to other facilities appears associated with increased early readmission risk. Prospective evaluation to confirm these findings along with development of optimal care strategies to reduce readmission post IC episodes are needed.\u003c/p\u003e","manuscriptTitle":"Thirty‑Day Readmission Rates and Outcomes after hospitalization for Ischemic Colitis. A National Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-13 05:41:26","doi":"10.21203/rs.3.rs-4503996/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":"95377962-8c3e-47ed-958a-d6b928781ee7","owner":[],"postedDate":"June 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-22T19:53:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-13 05:41:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4503996","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4503996","identity":"rs-4503996","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}