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.

Correction to: Drug Delivery from an Innovative LAMA/LABA Co-suspension Delivery Technology Fixed-Dose Combination MDI: Evidence of Consistency, Robustness, and Reliability.

This article was originally published Online First without open access. After publication it was discovered that the author had ordered open access during the production process. The incorrect license was assigned to this paper due to a technical error.

Drug Delivery from an Innovative LAMA/LABA Co-suspension Delivery Technology Fixed-Dose Combination MDI: Evidence of Consistency, Robustness, and Reliability.

To ensure consistency of clinical outcomes, orally inhaled therapies must exhibit consistent delivered dose and aerosol properties at the time of manufacturing, throughout storage, and during various patient-use conditions. Achieving consistency across these scenarios has presented a significant challenge, especially for combination products that contain more than one drug. This study characterized the delivered dose and aerosol properties of glycopyrrolate/formoterol fumarate metered dose inhaler (GFF MDI; Bevespi Aerosphere™). GFF MDI, a fixed-dose combination (FDC) of a long-acting muscarinic antagonist, glycopyrrolate (18 µg, equivalent to glycopyrronium 14.4 µg), and a long-acting ß2-agonist, formoterol fumarate (9.6 µg; equivalent to formoterol fumarate dihydrate 10 µg), is formulated using innovative co-suspension delivery technology, which suspends micronized drug crystals with spray-dried phospholipid porous particles in hydrofluoroalkane propellant. In this study, delivered dose uniformity was assessed through the labeled number of doses, and aerosol properties, such as percent fine particle fraction (FPF) and mass median aerodynamic diameter, were determined by cascade impaction. GFF MDI achieved reproducible dose delivery and an FPF greater than 55%, whether formulated and delivered as a monocomponent or dual FDC. The performance of GFF MDI was maintained across various manufacturing batches, under extended storage, and with variations in flow rate. Furthermore, unlike a GFF drug crystal-only suspension, drug delivery remained consistent for GFF MDI when simulated patient-handling errors were applied, such as reduced shake energy and delays between shaking and actuation. These results demonstrate that co-suspension delivery technology overcomes well-known sources of variability in MDI drug delivery.

Determination of dissolved thiols using solid-phase extraction and liquid chromatographic determination of fluorescently derivatized thiolic compounds.

A method employing solid-phase extraction coupled with HPLC separation of thiol-monobromobimane (mBBr) derivatives was developed and optimized to quantify dissolved thiols at concentrations as low as 0.1 nM for glutathione (GSH) and gamma-glutamylcysteine (gammaEC) in natural waters. The reducing reagent, tri-n-butylphosphine (TBP), is needed for complete derivatization. At the optimal addition of TBP ([TBP]/[mBBr] = -0.4-1.6), no interference from copper was observed. The thiol fluorescence signal was totally suppressed if the mole ratio of TBP to mBBr was 2.6 or greater. Consistent recovery of thiols standards in a NaCl solution (0.5 M) was obtained using the Waters HLB reversed-phase resin, and blank levels of GSH and gammaEC were extremely low (less than 0.03 nM). The detection limits for GSH, gammaEC and phytochelatin-2 (PC-2) were 0.03, 0.03, and 0.06 nM, respectively.