Effectiveness and safety of early treatment with spironolactone for new-onset acute heart failure.

BACKGROUND: The effectiveness and safety of mineralocorticoid receptor antagonists (MRA) in acute heart failure (HF) is uncertain. We sought to describe the prescription of spironolactone during acute HF and whether early treatment is effective and safe in a real-world setting. METHODS: We performed a retrospective cohort study of adult (≥18 years) nonpregnant patients hospitalized with new-onset HF with reduced ejection fraction (HFrEF, defined by ejection fraction ≤40%) within 15 Kaiser Permanente Southern California medical centers between 2016 and 2021. Early treatment was defined by spironolactone prescription at discharge. The primary effectiveness outcome was a composite of HF readmission or all-cause mortality at 180 days. Safety outcomes were hypotension and hyperkalemia at 90 days. RESULTS: Among 2318 HFrEF patients, 368 (15.9%) were treated with spironolactone at discharge. After 1:2 propensity score matching, 354 early treatment and 708 delayed/no treatment patients were included in the analysis. The median age was 63 (IQR: 52-74) years; 61.6% were male, and 38.6% were White. By 90 days, ~20% had crossed over in the two groups. Early treatment was not associated with the composite outcome at 180 days (HR [95% CI]: 0.81 [0.56-1.17]), but a trend towards benefit by 365 days that did not reach statistical significance (0.78 [0.58-1.06]). Early treatment was also associated with hyperkalemia (subdistribution HR [95% CI]: 2.33 [1.30-4.18]) but not hypotension (0.93 [0.51-1.72]). CONCLUSIONS: Early treatment with spironolactone at discharge for new-onset HFrEF in a real-world setting did not reduce the risk of HF readmission or mortality in the first year after discharge. The risk of hyperkalemia was increased.

Association Between Coronary Artery Disease Testing in Patients with New-Onset Heart Failure and Heart Failure Readmission and Mortality.

BACKGROUND: In patients with new-onset heart failure (HF), coronary artery disease (CAD) testing remains underutilized. Whether widespread CAD testing in patients with new-onset HF leads to improved outcomes remains to be determined. OBJECTIVE: We sought to examine whether CAD testing, and its timing, among patients hospitalized with new-onset HF with reduced ejection fraction (HFrEF), is associated with improved outcomes. DESIGN: Retrospective cohort study. PARTICIPANTS: Adult (≥ 18 years) non-pregnant patients with new-onset HFrEF hospitalized within one of 15 Kaiser Permanente Southern California medical centers between 2016 and 2021. Key exclusion criteria included history of heart transplant, hospice, and a do-not-resuscitate order. MAIN MEASURES: Primary outcome was a composite of HF readmission or all-cause mortality through end of follow-up on 12/31/2022. KEY RESULTS: Among 2729 patients hospitalized with new-onset HFrEF, 1487 (54.5%) received CAD testing. The median age was 66 (56-76) years old, 1722 (63.1%) were male, and 1074 (39.4%) were White. After a median of 1.8 (0.6-3.4) years, the testing group had a reduced risk of HF readmission or all-cause mortality (aHR [95%CI], 0.71 [0.63-0.79]). These results were consistent across subgroups by history of atrial fibrillation, diabetes, renal disease, myocardial infarction, and elevated troponin during hospitalization. In a secondary analysis where CAD testing was further divided to early (received testing before discharge) and late testing (up to 90 days after discharge), there was no difference in late vs early testing (0.97 [0.81-1.16]). CONCLUSIONS: In a contemporary and diverse cohort of patients hospitalized with new-onset HFrEF, CAD testing within 90 days of hospitalization was associated with a lower risk of HF readmission or all-cause mortality. Testing within 90 days after discharge was not associated with worse outcomes.

Development and validation of the COVID-19 Hospitalized Patient Deterioration Index.

OBJECTIVES: To develop a COVID-19-specific deterioration index for hospitalized patients: the COVID Hospitalized Patient Deterioration Index (COVID-HDI). This index builds on the proprietary Epic Deterioration Index, which was not developed for predicting respiratory deterioration events among patients with COVID-19. STUDY DESIGN: A retrospective observational cohort was used to develop and validate the COVID-HDI model to predict respiratory deterioration or death among hospitalized patients with COVID-19. Deterioration events were defined as death or requiring high-flow oxygen, bilevel positive airway pressure, mechanical ventilation, or intensive-level care within 72 hours of run time. The sample included hospitalized patients with COVID-19 diagnoses or positive tests at Kaiser Permanente Southern California between May 3, 2020, and October 17, 2020. METHODS: Machine learning models and 118 candidate predictors were used to generate benchmark performance. Logit regression with least absolute shrinkage and selection operator and physician input were used to finalize the model. Split-sample cross-validation was used to train and test the model. RESULTS: The area under the receiver operating curve was 0.83. COVID-HDI identifies patients at low risk (negative predictive value [NPV] > 98.5%) and borderline low risk (NPV > 95%) of an event. Of all patients, 74% were identified as being at low or borderline low risk at some point during their hospitalization and could be considered for discharge with or without home monitoring. A high-risk group with a positive predictive value of 51% included 12% of patients. Model performance remained high in a recent cohort of patients. CONCLUSIONS: COVID-HDI is a parsimonious, well-calibrated, and accurate model that may support clinical decision-making around discharge and escalation of care.

Disease-Specific Factors Associated with Readmissions or Mortality After Hospital Discharge in COVID-19 Patients: a Retrospective Cohort Study.

BACKGROUND: Understanding 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. OBJECTIVE: Assess whether disease-specific factors are associated with adverse events post-discharge using a data-driven approach. DESIGN: Retrospective cohort study. SETTING: Fifteen medical centers within Kaiser Permanente Southern California. PARTICIPANTS: Adult patients (n=3508) discharged alive following hospitalization for COVID-19 between 05/01/2020 and 09/30/2020. INTERVENTIONS: None. MAIN MEASURES: Adverse 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 RESULTS: Four 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]). CONCLUSIONS: Disease-specific factors including treatment with remdesivir, symptom duration, and their interplay may help guide clinical decision making at time of discharge.

Association Between Dexamethasone Treatment After Hospital Discharge for Patients With COVID-19 Infection and Rates of Hospital Readmission and Mortality.

Importance: Current guidelines recommend use of dexamethasone, 6 mg/d, up to 10 days or until discharge for patients hospitalized with COVID-19. Whether patients who received less than 10 days of corticosteroids during hospitalization for COVID-19 benefit from continuing treatment at discharge has not been determined. Objective: To assess whether continuing dexamethasone treatment at discharge is associated with reduced all-cause readmissions or mortality postdischarge. Design, Setting, and Participants: A retrospective cohort study was conducted at 15 medical centers within Kaiser Permanente Southern California. The population included adults who received less than 10 days of dexamethasone, 6 mg/d, until discharge during hospitalization for COVID-19 and were discharged alive between May 1 and September 30, 2020. Exposures: Continued dexamethasone treatment at discharge. Main Outcomes and Measures: All-cause readmissions or mortality within 14 days from discharge. Results: A total of 1164 patients with a median age of 55 (IQR, 44-66) years were identified. Most patients were of Hispanic ethnicity (822 [70.6%]) and male (674 [57.9%]) and required oxygen support during hospitalization (1048 [90.0%]). Of the 1164 patients, 692 (59.5%) continued dexamethasone, 6 mg/d, at discharge. A balanced cohort was created using propensity score and inverse probability of treatment weighting. The adjusted odds ratio (OR) for readmissions or mortality within 14 days was 0.87 (95% CI, 0.58-1.30) for patients who continued dexamethasone therapy at discharge compared with those who did not. Similar results were produced by a sensitivity analysis that restricted the treatment group to those who received exactly 10 days of dexamethasone (OR, 0.89; 95% CI, 0.55-1.43) and by subgroup analyses stratified by the duration of dexamethasone treatment as an inpatient (1-3 days: OR, 0.71; 95% CI, 0.43-1.16; 4-9 days: OR, 1.01; 95% CI, 0.48-2.12), oxygen requirement at discharge (room air: OR, 0.91; 95% CI, 0.53-1.59; supplemental oxygen use: OR, 0.76; 95% CI, 0.42-1.37), and disease duration at discharge (≤10 days: OR, 0.81; 95% CI, 0.49-1.33; >10 days: OR, 0.94; 95% CI, 0.48-1.86). Conclusions and Relevance: In this cohort study of patients with COVID-19, continuing treatment with dexamethasone, 6 mg/d, at discharge was not associated with a reduction in 14-day all-cause readmission or mortality. This finding suggests that dexamethasone should not be routinely prescribed beyond discharge for individuals with COVID-19.

Healthcare Utilization Among Patients Diagnosed with COVID-19 in a Large Integrated Health System.

BACKGROUND: The demands for healthcare resources following a COVID-19 diagnosis are substantial, but not currently quantified. OBJECTIVE: To describe trends in healthcare utilization within 180 days for patients diagnosed with COVID-19 and identify patient factors associated with increased healthcare use. DESIGN: Observational cohort study. PATIENTS: A total of 64,011 patients with a test-confirmed COVID-19 diagnosis from March to September 2020 in a large integrated healthcare system in Southern California. MAIN MEASURES: Overall healthcare utilization during the 180 days following COVID-19 diagnosis, as well as encounter types and reasons for visits during the first 30 days. Poisson regression was used to identify patient factors associated with higher utilization. Analyses were performed separately for patients who were and were not hospitalized for COVID-19. KEY RESULTS: Healthcare utilization was about twice as high for hospitalized patients compared to non-hospitalized patients in all time periods. The average number of visits was highest in the first 30 days (hospitalized: 12.3 visits/30 person-days; non-hospitalized: 6.6) and gradually decreased over time. In the first 30 days, the majority of healthcare visits were telehealth encounters (hospitalized: 9.0 visits; non-hospitalized: 5.6 visits), and the most prevalent reasons for visits were COVID-related diagnoses, COVID-related symptoms, and respiratory-related conditions. For hospitalized patients, older age (≥65: RR 1.27, 95% CI 1.15-1.41), female gender (RR 1.07, 95% CI 1.05-1.09), and higher BMI (≥40: RR 1.07, 95% CI 1.03-1.10) were associated with higher total utilization. For non-hospitalized patients, older age, female gender, higher BMI, non-white race/ethnicity, former smoking, and greater number of pre-existing comorbidities were all associated with increased utilization. CONCLUSIONS: Patients with COVID-19 seek healthcare frequently within 30 days of diagnosis, placing high demands on health systems. Identifying ways to support patients diagnosed with COVID-19 while adequately providing the usual recommended care to our communities will be important as we recover from the pandemic.

Identifying patients with symptoms suspicious for COVID-19 at elevated risk of adverse events: The COVAS score.

OBJECTIVE: Develop and validate a risk score using variables available during an Emergency Department (ED) encounter to predict adverse events among patients with suspected COVID-19. METHODS: A retrospective cohort study of adult visits for suspected COVID-19 between March 1 - April 30, 2020 at 15 EDs in Southern California. The primary outcomes were death or respiratory decompensation within 7-days. We used least absolute shrinkage and selection operator (LASSO) models and logistic regression to derive a risk score. We report metrics for derivation and validation cohorts, and subgroups with pneumonia or COVID-19 diagnoses. RESULTS: 26,600 ED encounters were included and 1079 experienced an adverse event. Five categories (comorbidities, obesity/BMI ≥ 40, vital signs, age and sex) were included in the final score. The area under the curve (AUC) in the derivation cohort was 0.891 (95% CI, 0.880-0.901); similar performance was observed in the validation cohort (AUC = 0.895, 95% CI, 0.874-0.916). Sensitivity ranging from 100% (Score 0) to 41.7% (Score of ≥15) and specificity from 13.9% (score 0) to 96.8% (score ≥ 15). In the subgroups with pneumonia (n = 3252) the AUCs were 0.780 (derivation, 95% CI 0.759-0.801) and 0.832 (validation, 95% CI 0.794-0.870), while for COVID-19 diagnoses (n = 2059) the AUCs were 0.867 (95% CI 0.843-0.892) and 0.837 (95% CI 0.774-0.899) respectively. CONCLUSION: Physicians evaluating ED patients with pneumonia, COVID-19, or symptoms suspicious for COVID-19 can apply the COVAS score to assist with decisions to hospitalize or discharge patients during the SARS CoV-2 pandemic.