Risk factors for readmission following inpatient management of COVID-19 in a low-prevalence setting.
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ABSTRACT:
SUBMITTER: Drewett GP
PROVIDER: S-EPMC8206980 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo characterize the functional impairments of a cohort of patients undergoing inpatient rehabilitation after surviving severe COVID-19 illness, in order to better understand the ongoing needs of this patient population.MethodsThis study consisted of a retrospective chart review of consecutive patients hospitalized for COVID-19 and admitted to a regional inpatient rehabilitation hospital from April 29th to May 22nd, 2020. Patient demographics, clinical characteristics and complications from acute hospitalization were examined. Measures of fall risk (Berg Balance Scale), endurance (6 Minute Walk Test), gait speed (10 Meter Walk Test), mobility (transfer and ambulation independence), cognition, speech and swallowing (American Speech and Hearing Association National Outcomes Measurement System Functional Communication Measures) were assessed at rehabilitation admission and discharge.ResultsThe study population included 29 patients and was 70% male, 58.6% white and with a mean age of 59.5. The mean length of acute hospitalization was 32.2 days with a mean of 18.7 days intubated. Patients spent a mean of 16.7 days in inpatient rehabilitation and 90% were discharged home. Patients demonstrated significant improvement from admission to discharge in measures of fall risk, endurance, gait speed, mobility, cognition, speech and swallowing, (p< 0.05). At discharge, a significant portion of the population continued to deficits in cognition (attention 37%; memory 28%; problem solving 28%), balance (55%) and gait speed (97%).ConclusionPatients admitted to inpatient rehabilitation after hospitalization with COVID-19 demonstrated deficits in mobility, cognition, speech and swallowing at admission and improved significantly in all of these domains by discharge. However, a significant number of patients exhibited residual deficits at discharge highlighting the post-acute care needs of this patient population.
| S-EPMC8011729 | biostudies-literature
Project description:ObjectiveCOVID-19 has been introduced by the World Health Organization as a health emergency worldwide. Up to 9% of the patients with COVID-19 may be readmitted by 2 months after discharge. This study aimed to estimate the readmission rate and identify main risk factors for readmission in these patients. In this prospective study, 416 discharged COVID patients followed up with a minimum 1 month and the readmission rate was recorded. Evaluated characteristics included time of readmission, age and sex, main symptoms of disease, result of computed tomography scan, reverse transcription polymerase chain reaction test and treatment modalities.ResultsRegarding readmission, 51 patients of 416 discharged patients, was readmitted during the study period. The rate of readmission for 30 and 60 days after discharge was 7.6% and 8.1%, respectively. The median age of the readmitted patients was 67 years (IQR: 53-78). About 65% of readmitted patients had underlying disease. The most significant factor in readmission rate was related to the site of lung involvement (OR > 4). Age over 60 years, underlying disease especially diabetes (OR = 3.43), high creatinine level (≥ to 1.2 mg/dl) (OR = 2.15) were the most important predictors of readmission.
| S-EPMC8474946 | biostudies-literature
Project description:ObjectivesReadmission to acute care from the inpatient rehabilitation facility (IRF) setting is potentially preventable and an important target of quality improvement and cost savings. The objective of this study was to develop a risk calculator to predict 30-day all-cause readmissions from the IRF setting.DesignRetrospective database analysis using the Uniform Data System for Medical Rehabilitation (UDSMR) from 2015 through 2019.Setting and participantsIn total, 956 US inpatient rehabilitation facilities and 1,849,768 IRF discharges comprising patients from 14 impairment groups.MethodsLogistic regression models were developed to calculate risk-standardized 30-day all-cause hospital readmission rates for patients admitted to an IRF. Models for each impairment group were assessed using 12 common clinical and demographic variables and all but 4 models included various special variables. Models were assessed for discrimination (c-statistics), calibration (calibration plots), and internal validation (bootstrapping). A readmission risk scoring system was created for each impairment group population and was graphically validated.ResultsThe mean age of the cohort was 68.7 (15.2) years, 50.7% were women, and 78.3% were Caucasian. Medicare was the primary payer for 73.1% of the study population. The final models for each impairment group included between 4 and 13 total predictor variables. Model c-statistics ranged from 0.65 to 0.70. There was good calibration represented for most models up to a readmission risk of 30%. Internal validation of the models using bootstrap samples revealed little bias. Point systems for determining risk of 30-day readmission were developed for each impairment group.Conclusions and implicationsMultivariable risk factor algorithms based upon administrative data were developed to assess 30-day readmission risk for patients admitted from IRF. This report represents the development of a readmission risk calculator for the IRF setting, which could be instrumental in identifying high risk populations for readmission and targeting resources towards a diverse group of IRF impairment groups.
| S-EPMC9926973 | biostudies-literature
Project description:Though mechanical ventilation (MV) is used to treat patients with severe coronavirus disease 2019 (COVID-19), little is known about the long-term health implications of this treatment. Our objective was to determine the association between MV for treatment of COVID-19 and likelihood of hospital readmission, all-cause mortality, and reason for readmission. This study was a longitudinal observational design with electronic health record (EHR) data collected between 3/1/2020 and 1/31/2021. Participants included 17,652 patients hospitalized for COVID-19 during this period who were followed through 6/30/2021. The primary outcome was readmission to inpatient care following discharge. Secondary outcomes included all-cause mortality and reason for readmission. Rates of readmission and mortality were compared between ventilated and non-ventilated patients using Cox proportional hazards regression models. Differences in reasons for readmission by MV status were compared using multinomial logistic regression. Patient characteristics and measures of illness severity were balanced between those who were mechanically ventilated and those who were not utilizing 1-to-1 propensity score matching. The sample had a median age of 63 and was 47.1% female. There were 1,131 (6.4%) patients who required MV during their initial hospitalization. Rates (32.1% versus 9.9%) and hazard of readmission were greater for patients requiring MV in the propensity score-matched samples [hazard ratio (95% confidence interval) = 3.34 (2.72-4.10)]. Rates (15.3% versus 3.4%) and hazard [hazard ratio (95% confidence interval) = 3.12 (2.32-4.20)] of all-cause mortality were also associated with MV status. Ventilated patients were more likely to be readmitted for reasons which were classified as COVID-19, infectious diseases, and respiratory diagnoses compared to non-ventilated patients. Mechanical ventilation is a necessary treatment for severely ill patients. However, it may be associated with adverse outcomes including hospital readmission and death. More intense post-discharge monitoring may be warranted to decrease this associational finding.
| S-EPMC9821470 | biostudies-literature
Project description:Purpose: To investigate molecular mechanisms of SARS-CoV-2-induced mucin expression and synthesis and test candidate countermeasures. Methods: Bulk RNA-seq was performed on well-differentiated human bronchial epithelial (HBE) cell culture lysates with/without SARS-CoV-2 inoculation. Results: SARS-CoV-2-infected HBE cultures exhibited peak titers 3 days post inoculation, whereas induction of MUC5B/MUC5AC peaked 7-14 days post inoculation. Conclusions: SARS-CoV-2-infection to HBE culture causes mucus goblet cell metaplasia and increased expression of MUC5B-dominated mucin overproduction.
2022-08-03 | GSE210223 | GEO
Project description:Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
2022-02-01 | E-MTAB-10129 | biostudies-arrayexpress
Project description:Determine patient and hospital-level risk factors associated with 30-day readmission for patients undergoing inpatient otolaryngologic surgery.Retrospective cohort study.We analyzed the State Inpatient Database (SID) from California for patients who underwent otolaryngologic surgery between 2008 and 2010. Readmission rates, readmission diagnoses, and patient- and hospital-level risk factors for 30-day readmission were determined. Hierarchical logistic regression modeling was performed to identify procedure-, patient-, and hospital-level risk factors for 30-day readmission.The 30-day readmission rate following an inpatient otolaryngology procedure was 8.1%. The most common readmission diagnoses were nutrition, metabolic, or electrolyte problems (44% of readmissions) and surgical complications (10% of readmissions). New complications after discharge were the major drivers of readmission. Variables associated with 30-day readmission in hierarchical logistic regression modeling were: type of otolaryngologic procedure, Medicare or Medicaid health insurance, chronic anemia, chronic lung disease, chronic renal failure, index admission via the emergency department, in-hospital complication during the index admission, and discharge destination other than home.Approximately one out of 12 patients undergoing otolaryngologic surgery had a 30-day readmission. Readmissions occur across a variety of types of procedures and hospitals. Most of the variability was driven by patient-specific factors, not structural hospital characteristics.4. Laryngoscope, 2016 127:337-345, 2017.
| S-EPMC5490655 | biostudies-literature
Project description:In past decades, a rapid evolution of diabetes technology led to increased popularity and use of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) in the ambulatory setting for diabetes management, and recently, the artificial pancreas became available. Efforts to translate this technology to the hospital setting have shown accuracy and reliability of CGM, safety of CSII in appropriate populations, improvement of inpatient glycemic control with computerized glycemic management systems, and feasibility of inpatient CGM-CSII closed-loop systems. Several ongoing studies are focusing on continued translation of this technology to improve glycemic control and outcomes in hospitalized patients.
| S-EPMC7453786 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) has affected millions globally, with a continued need for effective treatments. N-acetylglucosamine has anti-inflammatory activities and modulates immune response. This study evaluated whether N-acetylglucosamine administered orally improves clinical outcomes for patients admitted to the hospital due to COVID-19.Materials and methodsThis single-center, prospective, observational cohort study used a retrospective control group for comparison. Multivariate analyses evaluated whether N-acetylglucosamine was an independent predictor of primary outcomes (rate of intubation, hospital length-of-stay, and mortality) and select secondary outcomes (intensive care unit [ICU] admission, ICU length-of-stay, supplemental oxygen use duration, hospice initiation, and poor clinical outcome [defined as combined hospice initiation/death]).ResultsOf the 50 patients enrolled in the N-acetylglucosamine treatment group, 48 patients had follow-up data (50.0% [24/48] male; median age 63 years, range: 29-88). Multivariate analysis showed the treatment group had improved hospital length-of-stay (β: 4.27 [95% confidence interval (CI) -5.67; -2.85], p < 0.001), ICU admission (odds ratio [OR] 0.32 [95% CI 0.10; 0.96], p = 0.049), and poor clinical outcome (OR 0.30 [95% CI 0.09; 0.86], p = 0.034). Mortality was significantly lower for treatment versus control on univariate analysis (12.5% vs. 28.0%, respectively; p = 0.039) and approached significance on multivariate analysis (p = 0.081).ConclusionsN-acetylglucosamine administration was associated with reduced hospital length-of-stay, ICU admission rates, and death/hospice rates in adults with COVID-19 compared to those who received standard care alone. An upcoming trial will further investigate N-acetylglucosamine's effects.Trial registrationNCT04706416.
| S-EPMC8282940 | biostudies-literature
Project description:IntroductionThe coronavirus disease (COVID-19) pandemic has continued to have a devastating impact on health worldwide. There has been a rapid evolution of evidence, establishing an increased risk of morbidity and mortality associated with diabetes and concurrent COVID-19. The objective of this review is to explore the current evidence for inpatient assessment and management of diabetes during the COVID-19 pandemic and highlight areas requiring further exploration.MethodsA literature search of databases was conducted to November 2020 using variations on keywords SARS-CoV-2, COVID-19, SARS, MERS and diabetes. Information relating to the impact of diabetes on severity of COVID-19 infection, the impact of COVID-19 infection on diabetes management and diabetes-related complications was integrated to create a narrative review.DiscussionPeople with diabetes and COVID-19 are at an increased risk of morbidity and mortality. It is important that people with both known and previously unrecognised diabetes and COVID-19 be promptly identified and assessed during acute illness, with close monitoring for clinical deterioration or complications. People with diabetes may require titration or alteration of their glycaemic management due to the potential for worse outcomes with hyperglycaemia and COVID-19 infection. Comprehensive discharge planning is vital to optimise ongoing glycaemic management.ConclusionFurther understanding of the risk of adverse outcomes and optimisation of glycaemic management for people with diabetes during COVID-19 is required to improve outcomes. Increased glucose and ketone monitoring, substitution of insulin for some oral anti-hyperglycaemic medications and careful monitoring for complications of diabetes such as diabetic ketoacidosis should be considered.
| S-EPMC7883197 | biostudies-literature