Frequency, risk factors, and outcomes of hospital readmissions of COVID-19 patients.
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ABSTRACT:
SUBMITTER: Ramos-Martinez A
PROVIDER: S-EPMC8253752 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:To determine the rate of unplanned PICU readmissions, examine the characteristics of index admissions associated with readmission, and compare outcomes of readmissions versus index admissions.Retrospective cohort analysis.Ninety North American PICUs that participated in the Virtual Pediatric Intensive Care Unit Systems.One hundred five thousand four hundred thirty-seven admissions between July 2009 and March 2011.None.Unplanned PICU readmission within 48 hours of index discharge was the primary outcome. Summary statistics, bivariate analyses, and mixed-effects logistic regression model with random effects for each hospital were performed.There were 1,161 readmissions (1.2%). The readmission rate varied among PICUs (0-3.3%), and acute respiratory (56%), infectious (35%), neurological (28%), and cardiovascular (20%) diagnoses were often present on readmission. Readmission risk increased in patients with two or more complex chronic conditions (adjusted odds ratio, 1.72; p < 0.001), unscheduled index admission (adjusted odds ratio, 1.37; p < 0.001), and transfer to an intermediate unit (adjusted odds ratio, 1.29; p = 0.004, compared with ward). Trauma patients had a decreased risk of readmission (adjusted odds ratio, 0.67; p = 0.003). Gender, race, insurance, age more than 6 months, perioperative status, and nighttime transfer were not associated with readmission. Compared with index admissions, readmissions had longer median PICU length of stay (3.1 vs 1.7 d, p < 0.001) and higher mortality (4% vs 2.5%, p = 0.002).Unplanned PICU readmissions were relatively uncommon, but were associated with worse outcomes. Several patient and admission characteristics were associated with readmission. These data help identify high-risk patient groups and inform risk-adjustment for standardized readmission rates.
| S-EPMC4327890 | biostudies-literature
Project description:Background/objectiveThe primary objective was to quantify the role of the number of Centers of Disease Control and Prevention (CDC) risk factors on in-hospital mortality. The secondary objective was to assess the associated hospital length of stay (LOS), intensive care unit (ICU) bed utilization, and ICU LOS with the number of CDC risk factors.MethodsA retrospective cohort study consisting of all hospitalizations with a confirmed COVID-19 diagnosis discharged between March 15, 2020 and April 30, 2020 was conducted. Data was obtained from 276 acute care hospitals across the United States. Cohorts were identified based upon the number of the CDC COVID-19 risk factors. Multivariable regression modeling was performed to assess outcomes and utilization. The odds ratio (OR) and incidence rate ratio (IRR) were reported.ResultsCompared with patients with no CDC risk factors, patients with risk factors were significantly more likely to die during the hospitalization: One risk factor (OR 2.08, 95% CI, 1.60-2.70; P < 0.001), two risk factors (OR 2.63, 95% CI, 2.00-3.47; P < 0.001), and three or more risk factors (OR 3.49, 95% CI, 2.53-4.80; P < 0.001). The presence of CDC risk factors was associated with increased ICU utilization, longer ICU LOS, and longer hospital LOS compared to those with no risk factors. Patients with hypertension (OR 0.77, 95% CI, 0.70-0.86; P < 0.001) and those administered statins were less likely to die (OR 0.54, 95% CI, 0.49-0.60; P < 0.001).ConclusionsQuantifying the role of CDC risk factors upon admission may improve risk stratification and identification of patients who may require closer monitoring and more intensive treatment.
| S-EPMC7539762 | biostudies-literature
Project description:BackgroundUnderstanding the implications of disease-specific factors beyond baseline patient characteristics for coronavirus disease 2019 (COVID-19) may allow for identification of indicators for safe hospital discharge.ObjectiveAssess whether disease-specific factors are associated with adverse events post-discharge using a data-driven approach.DesignRetrospective cohort study.SettingFifteen medical centers within Kaiser Permanente Southern California.ParticipantsAdult patients (n=3508) discharged alive following hospitalization for COVID-19 between 05/01/2020 and 09/30/2020.InterventionsNone.Main measuresAdverse events defined as all-cause readmission or mortality within 14 days of discharge. Least absolute shrinkage and selection operator (LASSO) was used for variable selection and logistic regression was performed to estimate odds ratio (OR) and 95% confidence interval (CI).Key resultsFour variables including age, Elixhauser index, treatment with remdesivir, and symptom duration at discharge were selected by LASSO. Treatment with remdesivir was inversely associated with adverse events (OR: 0.46 [95%CI: 0.36-0.61]), while symptom duration ≤ 10 days was associated with adverse events (OR: 2.27 [95%CI: 1.79-2.87]) in addition to age (OR: 1.02 [95%CI: 1.01-1.03]) and Elixhauser index (OR: 1.15 [95%CI: 1.11-1.20]). A significant interaction between remdesivir and symptom duration was further observed (p=0.01). The association of remdesivir was stronger among those with symptom duration ≤10 days vs >10 days at discharge (OR: 0.30 [95%CI: 0.19-0.47] vs 0.62 [95%CI: 0.44-0.87]), while the association of symptom duration ≤ 10 days at discharge was weaker among those treated with remdesivir vs those not treated (OR: 1.31 [95%CI: 0.79-2.17] vs 2.71 [95%CI 2.05-3.59]).ConclusionsDisease-specific factors including treatment with remdesivir, symptom duration, and their interplay may help guide clinical decision making at time of discharge.
| S-EPMC9473458 | biostudies-literature
Project description:Preventing communicable diseases requires understanding the spread, epidemiology, clinical features, progression, and prognosis of the disease. Early identification of risk factors and clinical outcomes might help in identifying critically ill patients, providing appropriate treatment, and preventing mortality. We conducted a prospective study in patients with flu-like symptoms referred to the imaging department of a tertiary hospital in Iran between March 3, 2020, and April 8, 2020. Patients with COVID-19 were followed up after two months to check their health condition. The categorical data between groups were analyzed by Fisher's exact test and continuous data by Wilcoxon rank-sum test. Three hundred and nineteen patients (mean age 45.48 ± 18.50 years, 177 women) were enrolled. Fever, dyspnea, weakness, shivering, C-reactive protein, fatigue, dry cough, anorexia, anosmia, ageusia, dizziness, sweating, and age were the most important symptoms of COVID-19 infection. Traveling in the past 3 months, asthma, taking corticosteroids, liver disease, rheumatological disease, cough with sputum, eczema, conjunctivitis, tobacco use, and chest pain did not show any relationship with COVID-19. To the best of our knowledge, a number of factors associated with mortality due to COVID-19 have been investigated for the first time in this study. Our results might be helpful in early prediction and risk reduction of mortality in patients infected with COVID-19.
| S-EPMC7753243 | biostudies-literature
Project description:OBJECTIVE:To synthesise evidence on risk factors associated with paediatric unplanned hospital readmissions (UHRs). DESIGN:Systematic review. DATA SOURCE:CINAHL, EMBASE (Ovid) and MEDLINE from 2000 to 2017. ELIGIBILITY CRITERIA:Studies published in English with full-text access and focused on paediatric All-cause, Surgical procedure and General medical condition related UHRs were included. DATA EXTRACTION AND SYNTHESIS:Characteristics of the included studies, examined variables and the statistically significant risk factors were extracted. Two reviewers independently assessed study quality based on six domains of potential bias. Pooling of extracted risk factors was not permitted due to heterogeneity of the included studies. Data were synthesised using content analysis and presented in narrative form. RESULTS:Thirty-six significant risk factors were extracted from the 44 included studies and presented under three health condition groupings. For All-cause UHRs, ethnicity, comorbidity and type of health insurance were the most frequently cited factors. For Surgical procedure related UHRs, specific surgical procedures, comorbidity, length of stay (LOS), age, the American Society of Anaesthesiologists class, postoperative complications, duration of procedure, type of health insurance and illness severity were cited more frequently. The four most cited risk factors associated with General medical condition related UHRs were comorbidity, age, health service usage prior to the index admission and LOS. CONCLUSIONS:This systematic review acknowledges the complexity of readmission risk prediction in paediatric populations. This review identified four risk factors across all three health condition groupings, namely comorbidity; public health insurance; longer LOS and patients<12 months or between 13-18 years. The identification of risk factors, however, depended on the variables examined by each of the included studies. Consideration should be taken into account when generalising reported risk factors to other institutions. This review highlights the need to develop a standardised set of measures to capture key hospital discharge variables that predict unplanned readmission among paediatric patients.
| S-EPMC6352831 | biostudies-other
Project description:As of December 2020, there were over 450,000 confirmed coronavirus disease 2019 (COVID-19) cases in New York City (NYC) with approximately 25,000 deaths. Previous literature identified advanced age, higher severity of illness, elevated inflammatory biomarkers, acute organ dysfunction, comorbidities, and presentation from long-term care facility as risk factors for mortality in patients from Wuhan, China, and the United States. Additional studies conducted in NYC are warranted to confirm these findings. The objective of this study was to assess the risk factors for in-hospital mortality in patients with confirmed COVID-19 infections. This was a retrospective case-control study at The Brooklyn Hospital Center, a 464-bed community teaching hospital. Adult patients with a confirmed COVID-19 infection and who received at least 24 h of COVID-19 therapy were included. Univariate and multivariate logistic regression analyses were conducted to identify the risk factors for in-hospital mortality. Two-hundred and eighty four patients were included, of whom 95 (33.5%) were nonsurvivors and 189 (66.5%) patients were survivors. Multivariate analysis showed higher in-hospital mortality with advanced age (odds ratio [OR] 6.476; 95% confidence interval [CI], 1.827-22.953), presentation from long-term care facility (OR 4.259; 95% CI 1.481-12.250), elevated total bilirubin (OR 4.947; 95% CI 1.048-23.350), vasopressor initiation (OR 36.262; 95% CI 5.319-247.216), and development of renal failure (OR 36.261; 95% CI 2.667-493.046). Risk factors associated with mortality for patients with COVID-19 in a community teaching hospital included advanced age, vasopressor initiation, development of renal failure, elevated total bilirubin, and presentation from long-term care facility.
| S-EPMC8014291 | biostudies-literature
Project description:To determine the frequency, mortality, cost, and risk factors associated with readmission after index hospitalization with severe sepsis.Observational cohort study of Healthcare Cost and Utilization Project data.All nonfederal hospitals in three U.S. states.Severe sepsis survivors (n = 43,452) in the first two quarters of 2011.None.We measured readmission rates and the associated cost and mortality of readmissions in severe sepsis survivors. We used multivariable logistic regression to identify patient and hospitalization characteristics associated with readmission. Of 43,452 sepsis survivors, 26% required readmission within 30 days and 48% within 180 days. The cumulative mortality rate of sepsis survivors attributed to readmissions was 8%, and the estimated cost was over $1.1 billion. Among survivors, 25% required multiple readmissions within 180 days and accounted for 77% of all readmissions. Age younger than 80 years (odds ratio, 1.14; 95% CI, 1.08-1.21), black race (odds ratio, 1.18; 95% CI, 1.10-1.26), and Medicare or Medicaid payor status (odds ratio, 1.21; 95% CI, 1.13-1.30; odds ratio, 1.34; 95% CI, 1.23-1.46, respectively) were associated with greater odds of 30-day readmission while female gender was associated with reduced odds (odds ratio, 0.92; 95% CI, 0.87-0.96). Comorbidities including malignancy (odds ratio, 1.34; 95% CI, 1.24-1.45), collagen vascular disease (odds ratio, 1.30; 95% CI, 1.15-1.46), chronic kidney disease (odds ratio, 1.24; 95% CI, 1.18-1.31), liver disease (odds ratio, 1.22; 95% CI, 1.11-1.34), congestive heart failure (odds ratio, 1.14; 95% CI, 1.08-1.19), lung disease (odds ratio, 1.12; 95% CI, 1.06-1.18), and diabetes (odds ratio, 1.12; 95% CI, 1.07-1.17) were associated with greater odds of 30-day readmission. Index hospitalization characteristics including longer length of stay, discharge to a care facility, higher hospital annual severe sepsis case volume, and higher hospital sepsis mortality rate were also positively associated with readmission rates.The 30-day and 180-day readmissions are common in sepsis survivors with significant resultant cost and mortality. Patient sociodemographics and comorbidities as well as index hospitalization characteristics are associated with 30-day readmission rates.
| S-EPMC4479267 | biostudies-literature
Project description:BackgroundThe surge of coronavirus 2019 (COVID-19) hospitalizations in New York City required rapid discharges to maintain hospital capacity.ObjectiveTo determine whether lenient provisional discharge guidelines with remote monitoring after discharge resulted in safe discharges home for patients hospitalized with COVID-19 illness.DesignRetrospective case series SETTING: Tertiary care medical center PATIENTS: Consecutive adult patients hospitalized with COVID-19 illness between March 26, 2020, and April 8, 2020, with a subset discharged home INTERVENTIONS: COVID-19 Discharge Care Program consisting of lenient provisional inpatient discharge criteria and option for daily telephone monitoring for up to 14 days after discharge MEASUREMENTS: Fourteen-day emergency department (ED) visits and hospital readmissions RESULTS: Among 812 patients with COVID-19 illness hospitalized during the study time period, 15.5% died prior to discharge, 24.1% remained hospitalized, 10.0% were discharged to another facility, and 50.4% were discharged home. Characteristics of the 409 patients discharged home were mean (SD) age 57.3 (16.6) years; 245 (59.9%) male; 27 (6.6%) with temperature ≥ 100.4 °F; and 154 (37.7%) with oxygen saturation < 95% on day of discharge. Over 14 days of follow-up, 45 patients (11.0%) returned to the ED, of whom 31 patients (7.6%) were readmitted. Compared to patients not referred, patients referred for remote monitoring had fewer ED visits (8.3% vs 14.1%; OR 0.60, 95% CI 0.31-1.15, p = 0.12) and readmissions (6.9% vs 8.3%; OR 1.15, 95% CI 0.52-2.52, p = 0.73).LimitationsSingle-center study; assignment to remote monitoring was not randomized.ConclusionsDuring the COVID-19 surge in New York City, lenient discharge criteria in conjunction with remote monitoring after discharge were associated with a rate of early readmissions after COVID-related hospitalizations that was comparable to the rate of readmissions after other reasons for hospitalization before the COVID pandemic.
| S-EPMC7808120 | biostudies-literature
Project description: Not available
| S-EPMC8007946 | biostudies-literature
Project description:BackgroundSince February 2020, over 2.5 million Texans have been diagnosed with COVID-19, and 20% are young adults at risk for SARS-CoV-2 exposure at work, academic, and social settings. This study investigated demographic and clinical risk factors for severe disease and readmission among young adults 18-29 years old, who were diagnosed at a hospital encounter in Houston, Texas, USA.Methods and findingsA retrospective registry-based chart review was conducted investigating demographic and clinical risk factors for severe COVID-19 among patients aged 18-29 with positive SARS-CoV-2 tests within a large metropolitan healthcare system in Houston, Texas, USA. In the cohort of 1,853 young adult patients diagnosed with COVID-19 infection at a hospital encounter, including 226 pregnant women, 1,438 (78%) scored 0 on the Charlson Comorbidity Index, and 833 (45%) were obese (≥30 kg/m2). Within 30 days of their diagnostic encounter, 316 (17%) patients were diagnosed with pneumonia, 148 (8%) received other severe disease diagnoses, and 268 (14%) returned to the hospital after being discharged home. In multivariable logistic regression analyses, increasing age (adjusted odds ratio [aOR] 1.1, 95% confidence interval [CI] 1.1-1.2, p<0.001), male gender (aOR 1.8, 95% CI 1.2-2.7, p = 0.002), Hispanic ethnicity (aOR 1.9, 95% CI 1.2-3.1, p = 0.01), obesity (3.1, 95% CI 1.9-5.1, p<0.001), asthma history (aOR 2.3, 95% CI 1.3-4.0, p = 0.003), congestive heart failure (aOR 6.0, 95% CI 1.5-25.1, p = 0.01), cerebrovascular disease (aOR 4.9, 95% CI 1.7-14.7, p = 0.004), and diabetes (aOR 3.4, 95% CI 1.9-6.2, p<0.001) were predictive of severe disease diagnoses within 30 days. Non-Hispanic Black race (aOR 1.6, 95% CI 1.0-2.4, p = 0.04), obesity (aOR 1.7, 95% CI 1.0-2.9, p = 0.046), asthma history (aOR 1.7, 95% CI 1.0-2.7, p = 0.03), myocardial infarction history (aOR 6.2, 95% CI 1.7-23.3, p = 0.01), and household exposure (aOR 1.5, 95% CI 1.1-2.2, p = 0.02) were predictive of 30-day readmission.ConclusionsThis investigation demonstrated the significant risk of severe disease and readmission among young adult populations, especially marginalized communities and people with comorbidities, including obesity, asthma, cardiovascular disease, and diabetes. Health authorities must emphasize COVID-19 awareness and prevention in young adults and continue investigating risk factors for severe disease, readmission and long-term sequalae.
| S-EPMC8323903 | biostudies-literature