Predictors of 30- and 90-Day COPD Exacerbation Readmission: A Prospective Cohort Study.
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ABSTRACT:
SUBMITTER: Alqahtani JS
PROVIDER: S-EPMC8504869 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Rationale: Identifying patients hospitalized for acute exacerbations of COPD (AECOPD) who are at high risk for readmission is challenging. Traditional markers of disease severity such as pulmonary function have limited utility in predicting readmission. Handgrip strength, a component of the physical frailty phenotype, may be a simple tool to help predict readmission. Objective(s): To investigate if handgrip strength, a component of the physical frailty phenotype and surrogate for weakness, is a predictive biomarker of COPD readmission. Methods: This was a prospective, observational study of patients admitted to the inpatient general medicine unit at the University of Chicago Medicine, US. This study evaluated age, sex, ethnicity, degree of obstructive lung disease by spirometry (FEV1 percent predicted), and physical frailty phenotype (components include handgrip strength and walk speed). The primary outcome was all-cause hospital readmission within 30 days of discharge. Results: Of 381 eligible patients with AECOPD, 70 participants agreed to consent to participate in this study. Twelve participants (17%) were readmitted within 30 days of discharge. Weak grip at index hospitalization, defined as grip strength lower than previously established cut-points for sex and body mass index (BMI), was predictive of readmission (OR 11.2, 95% CI 1.3, 93.2, p = 0.03). Degree of airway obstruction (FEV1 percent predicted) did not predict readmission (OR 1.0, 95% CI 0.95, 1.1, p = 0.7). No non-frail patients were readmitted. Conclusions: At a single academic center weak grip strength was associated with increased 30-day readmission. Future studies should investigate whether geriatric measures can help risk-stratify patients for likelihood of readmission after admission for AECOPD.
| S-EPMC8058414 | biostudies-literature
Project description:Background Syncope accounts for 0.6% to 1.5% of hospitalizations in the United States. We sought to determine the causes and predictors of 30-day readmission in patients with syncope. Methods and Results We identified 323 250 encounters with a primary diagnosis of syncope/collapse in the 2013-2014 Nationwide Readmissions Database. We excluded patients younger than 18 years, those discharged in December, those who died during hospitalization, hospital transfers, and those whose length of stay was missing. We used multivariable logistic regression analysis to evaluate the association between baseline characteristics and 30-day readmission. A total of 282 311 syncope admissions were included. The median age was 72 years (interquartile range, 58-83), 53.9% were women, and 9.3% had 30-day readmission. The most common cause of 30-day readmissions was syncope/collapse, followed by cardiac, neurological, and infectious causes. Characteristics associated with 30-day readmissions were age 65 years and older (odds ratio [OR], 0.7; 95% confidence interval [ CI ], 0.6-0.7), female sex (OR, 0.9; 95% CI, 0.8-0.9), congestive heart failure (OR, 1.5; 95% CI, 1.2-1.9), atrial fibrillation/flutter (OR, 1.3; 95% CI, 1.3-1.4), diabetes mellitus (OR, 1.2; 95% CI, 1.2-1.3), coronary artery disease (OR, 1.2; 95% CI, 1.2-1.3), anemia (OR, 1.4; 95% CI, 1.4-1.5), chronic obstructive pulmonary disease (OR, 1.4; 95% CI, 1.3-1.4), home with home healthcare disposition (OR, 1.5; 95% CI, 1.5-1.6), leaving against medical advice (OR, 1.7; 95% CI, 1.6-1.9), length of stay of 3 to 5 days (OR, 1.5; 95% CI, 1.4-1.6) or >5 days (OR, 2; 95% CI, 1.8-2), and having private insurance (OR, 0.6; 95% CI, 0.6-0.7). Conclusions The 30-day readmission rate after syncope/collapse was 9.3%. We identified causes and risk factors associated with readmission. Future prospective studies are needed to derive risk-stratification models to reduce the high burden of readmissions.
| S-EPMC6222963 | biostudies-literature
Project description:OBJECTIVE:To investigate the longitudinal changes in principal readmission diagnoses within 30 days after hospitalization for acute exacerbation of chronic obstructive pulmonary disease (AECOPD). STUDY SETTING:Medicare claims data, 2010-2012. STUDY DESIGN:Retrospective cohort study. DATA COLLECTION METHODS:We identified AECOPD hospitalizations aged 65 years and above, and examined the principal 30-day readmission diagnoses (respiratory related, cardiac related, and other conditions). We also constructed Joinpoint regression models to test whether patients with each of the 3 major readmission conditions had a unique temporal pattern of readmission during the 30-day period. PRINCIPAL FINDINGS:Among 76,697 index hospitalizations with AECOPD, 14,090 (18.4%) were readmitted within 30 days. Respiratory-related conditions accounted for 55% of readmissions. The proportion of respiratory-related conditions as the readmission diagnosis decreased from postdischarge day 1 to day 8 (4.0% decrease), and then increased thereafter (13.2% increase; P=0.06). Cardiac-related conditions had a similar nonlinear trend with an inflection point at day 6 (P=0.02), with a subsequent downward trend from day 22 (P=0.01). By contrast, the other conditions increased from day 1 to day 6 (15.0% increase), and then significantly decreased (28.8% decrease; P=0.04). CONCLUSIONS:The proportions of principal discharge diagnosis of readmission changed significantly at around postdischarge day 7. Our findings advance research into identification of the underlying mechanisms and development of targeted interventions to prevent readmissions.
| S-EPMC6041171 | biostudies-literature
Project description:Stroke is one of the most common medical emergencies and the leading cause of preventable death and long-term disability worldwide. A prospective cohort study was conducted at the stroke unit of Jimma university medical center for four consecutive months (from March 10 to July 10, 2017). Of the total 116 study patients, 60 (51.7%) had an ischemic stroke. At 30-day follow-up, 81 (69.8%) patients were alive, 34 (29.3%) were died, and one patient (0.9%) was lost to follow-up. Elevated alanine aminotransferase (ALT) level (AHR: 3.77, 95% CI: 1.34-10.57), diagnosis of stroke clinically alone (AHR: 3.90, 95 CI: 1.49-10.26), brain edema (AHR: 4.28, 95% CI: 1.61-11.37), and National Institute of Health Stroke Scale (NIHSS) ≥ 13 during hospital arrival (AHR: 6.49, 95% CI: 1.90-22.22) were the independent predictors of 30-day mortality. At 60-day follow-up, 68 (58.6%) patients were alive, 46 (39.7%) were died, and 2 (1.7%) were lost to follow-up. Discharge against medical advice (AHR: 6.40, 95% CI: 2.31-17.73) and severe modified Rankin score/mRS (4-5) at discharge (AHR: 3.64, 95% CI: 1.01-13.16) were the independent predictors of 60-day mortality. The median (IQR) length of survival after hospital admission for patients died within 30 and 60 days were 4.65 (2.34-11.80) and 9.3 (3.93-33) days, respectively. Stroke significantly affects the morbidity and mortality in Ethiopia. There is a need to provide better care and future planning for stroke patients as an emergency diagnosis and treatment to minimize mortality and disability.
| S-EPMC7132118 | biostudies-literature
Project description:Reduction in 30-day readmission rate after chronic obstructive pulmonary disease (COPD)-related hospitalization is a national objective. However, little is known about trends in readmission rates in recent years, particularly in priority populations defined by the Agency for Healthcare Research and Quality (AHRQ)(e.g., the elderly, women, racial/ethnic minorities, low-income and rural populations, and populations with chronic illnesses).We conducted a retrospective cohort study using data from the State Inpatient Database of eight geographically-dispersed US states (Arkansas, California, Florida, Iowa, Nebraska, New York, Utah, and Washington) from 2006 through 2012. We identified all COPD-related hospitalizations by patients ?40 years old. The primary outcome was any-cause readmission within 30 days of discharge from the index hospitalization for COPD.From 2006 to 2012, a total of 845,465 hospitalizations at risk for 30-day readmissions were identified. Overall, 30-day readmission rate for COPD-related hospitalization decreased modestly from 20.0% in 2006 to 19.2% in 2012, an 0.8% absolute decrease (OR 0.991, 95%CI 0.989-0.995, Ptrend<0.001). This modest decline remained statistically significant after adjusting for patient demographics and comorbidities (adjusted OR 0.981, 95%CI 0.977-0.984, Ptrend<0.001). Similar to the overall population, the readmission rate over the 7-year period remained persistently high in most of AHRQ-defined priority populations.Our observations provide a benchmark for future investigation of the impact of Hospital Readmissions Reduction Program on readmissions after COPD hospitalization. Our findings encourage researchers and policymakers to develop effective strategies aimed at reducing readmissions among patients with COPD in an already-stressed healthcare system.
| S-EPMC5718159 | biostudies-literature
Project description:BackgroundThere is a growing understanding of the prevalence and impact of psychological disorders on COPD. However, the role of these disorders in early readmission is unclear.MethodsWe analyzed data from 5% fee-for-service Medicare beneficiaries diagnosed with COPD (International Classification of Diseases, Ninth Revision code, 491.xx, 492.xx, 493.xx, and 496.xx) between 2001 and 2011 who were hospitalized with a primary discharge diagnosis of COPD or a primary discharge diagnosis of respiratory failure (518.xx and 799.1) with secondary diagnosis of COPD. We hypothesized that such psychological disorders as depression, anxiety, psychosis, alcohol abuse, and drug abuse are independently associated with an increased risk of 30-day readmission in patients hospitalized for COPD.ResultsBetween 2001 and 2011, 135,498 hospitalizations occurred for COPD in 80,088 fee-for-service Medicare beneficiaries. Of these, 30,218 (22.30%) patients had one or more psychological disorders. In multivariate analyses, odds of 30-day readmission were higher in patients with COPD who had depression (OR, 1.34; 95% CI, 1.29-1.39), anxiety (OR, 1.43; 95% CI, 1.37-1.50), psychosis (OR, 1.18; 95% CI, 1.10-1.27), alcohol abuse (OR, 1.30; 95% CI, 1.15-1.47), and drug abuse (OR, 1.29; 95% CI, 1.11-1.50) compared with those who did not have these disorders. These psychological disorders increased amount of variation in 30-day readmission attributed to patient characteristics by 37%.ConclusionsPsychological disorders like depression, anxiety, psychosis, alcohol abuse, and drug abuse are independently associated with higher all-cause 30-day readmission rates for Medicare beneficiaries with COPD.
| S-EPMC4944783 | biostudies-literature
Project description:Chronic obstructive pulmonary disease (COPD) claimed 3.0 million lives in 2016 and ranked 3rd among the top 10 global causes of death. Moreover, once diagnosed and discharged from the hospital, the 30-day readmission risk in COPD patients is found to be the highest among all chronic diseases. The existing diagnosis methods, such as Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2019, Body-mass index, airflow Obstruction, Dyspnea, and Exercise (BODE) index, modified Medical Research Council (mMRC), COPD assessment test (CAT), 6-minute walking distance, which are adopted currently by physicians cannot predict the potential readmission of COPD patients, especially within the 30 days after discharge from the hospital. In this paper, a statistical model was proposed to predict the readmission risk of COPD patients within 30-days by monitoring their physical activity (PA) in daily living with accelerometer-based wrist-worn wearable devices. This proposed model was based on our previously reported PA models for activity index (AI) and regularity index (RI) and it introduced a new parameter, quality of activity (QoA), which incorporates previously proposed parameters, such as AI and RI, with other activity-based indices to predict the readmission risk. Data were collected from continuous PA monitoring of 16 COPD patients after hospital discharge as test subjects and readmission prediction criteria were proposed, with a 63% sensitivity and a 37.78% positive prediction rate. Compared to other clinical assessment, diagnosis, and prevention methods, the proposed model showed significant improvement in predicting the 30-day readmission risk.
| S-EPMC6982816 | biostudies-literature
Project description:ObjectivesAnalysis of frequency and reasons for planned and unplanned 30-day readmission in hospitalized pediatric otorhinolaryngology patients using German Diagnosis Related Group (G-DRG) system data.MethodsA retrospective population-based cohort study in Thuringia, Germany, was performed for the year 2015 with 2440 cases under 18 years (55.6% male) out of a total number of 15.271 inpatient cases. The majority of pediatric patients were from 2 to 5 years old (54.5%). The most frequent diagnoses were hyperplasia of adenoids or/and tonsils (26.6%). 36 cases (1.5%) experienced readmission within 30-days.Results30-day readmission was planned in 9 cases (25% of all readmission) and was unplanned in 27 cases (75%). The median interval between index and readmission treatment was 8 days. Postoperative bleeding after adenoidectomy, tonsillotomy/tonsillectomy or tracheostomy (33.4%) and infectious complications after surgery like acute otitis media, abscess formation or fever (36.2%) were the most frequent reasons for 30-day readmission. Compared to adults treated in 2015 in Thuringia, the readmission rate was higher in adult patients (8.9%) than in this pediatric cohort. In contrast to children, readmissions in adults were mainly planned (65.1%) with a different spectrum of underlying diseases and reasons for readmission.ConclusionThe 30-day readmission rate seemed to be lower for pediatric otolaryngology patients compared to adult patients. Unplanned readmissions dominated in pediatric patients, whereas planned readmissions dominated in adults.
| S-EPMC8454104 | biostudies-literature
Project description:Background: We conducted a retrospective cohort study of thirty-day readmission after abdominal aortic aneurysm (AAA) repair. Patients and methods: Inpatients (2009-2016) undergoing elective AAA repair were selected from the multicenter Cerner Health Facts® database using ICD-9 procedure codes. We identified characteristics associated with 30-day readmission with chi-square analysis and logistic regression. Results: 4,723 patients undergoing elective AAA procedures were identified; 3,101 endovascular aneurysm repairs (EVAR) and 1,622 open procedures. Readmission differed by procedure type (6.5 % EVAR vs. 9.3 % open, p =.0005). Multivariable logistic regression found that patients undergoing EVAR were less likely to be readmitted (OR 0.71, 95 % CI 0.54-0.92) than patients undergoing open repair. The following risk factors were associated with 30-day readmission following any AAA repair: surgical site infection during the index admission (OR 2.79, 95 % CI 1.25-6.22), age (OR 1.03, 95 % CI 1.01-1.05), receipt of bronchodilators (OR 1.34, 95 % CI 1.06-1.70) or steroids (OR 1.45, 95 % CI 1.04-2.02), serum potassium > 5.2 mEq/L (OR 1.89, 95 % CI 1.16-3.06), and higher Charlson co-morbidity scores (OR 1.12, 95 % CI 1.04-1.21). Subgroup analysis revealed that age (OR 1.02, 95 % CI 1.01-1.04), higher Charlson comorbidity scores (OR 1.20, 95 % CI 1.09-1.33), and receipt of post-operative bronchodilators (OR 1.39, 95 % CI 1.03-1.88) were risk factors for 30-day readmission following EVAR. After open procedures, readmission was associated with surgical site infection during the index admission (OR 2.91, 95 % CI 1.17-7.28), chronic heart failure (OR 2.18, 95 % CI 1.22-3.89), and receipt of post-operative steroids (OR 1.92, 95 % CI 1.24-2.96). The most common infections were pneumonia after open procedures and urinary tract infection after EVAR. Conclusions: The risk factor most associated with 30-day readmission after elective AAA repair was surgical site infection. Awareness of these risk factors and vulnerable groups may help identify high-risk patients who could benefit from increased surveillance programs to reduce readmission.
| S-EPMC6486413 | biostudies-literature
Project description:IntroductionThis study aimed to describe the rates and causes of unplanned readmissions within 30 days following carotid artery stenting (CAS) and to use artificial intelligence machine learning analysis for creating a prediction model for short-term readmissions. The prediction of unplanned readmissions after index CAS remains challenging. There is a need to leverage deep machine learning algorithms in order to develop robust prediction tools for early readmissions.MethodsPatients undergoing inpatient CAS during the year 2017 in the US Nationwide Readmission Database (NRD) were evaluated for the rates, predictors, and costs of unplanned 30-day readmission. Logistic regression, support vector machine (SVM), deep neural network (DNN), random forest, and decision tree models were evaluated to generate a robust prediction model.ResultsWe identified 16,745 patients who underwent CAS, of whom 7.4% were readmitted within 30 days. Depression [p < 0.001, OR 1.461 (95% CI 1.231-1.735)], heart failure [p < 0.001, OR 1.619 (95% CI 1.363-1.922)], cancer [p < 0.001, OR 1.631 (95% CI 1.286-2.068)], in-hospital bleeding [p = 0.039, OR 1.641 (95% CI 1.026-2.626)], and coagulation disorders [p = 0.007, OR 1.412 (95% CI 1.100-1.813)] were the strongest predictors of readmission. The artificial intelligence machine learning DNN prediction model has a C-statistic value of 0.79 (validation 0.73) in predicting the patients who might have all-cause unplanned readmission within 30 days of the index CAS discharge.ConclusionsMachine learning derived models may effectively identify high-risk patients for intervention strategies that may reduce unplanned readmissions post carotid artery stenting.Central illustrationFigure 2: ROC and AUPRC analysis of DNN prediction model with other classification models on 30-day readmission data for CAS subjects.
| S-EPMC8190015 | biostudies-literature