Validation of Respiratory Rate-Oxygenation Index in Patients With COVID-19-Related Respiratory Failure.

OBJECTIVES: The respiratory rate-oxygenation (ROX) index is a fraction of oxygen saturation, Fio2, and respiratory rate that has been validated to predict receipt of invasive mechanical ventilation in patients receiving high-flow nasal cannula (HFNC). This study aimed to validate ROX in a cohort of inpatients with COVID-19-related respiratory failure. DESIGN: Retrospective validation of the ROX index. We calculated sensitivity, specificity, positive predictive value, negative predictive value, and 95% CIs of ROX for invasive mechanical ventilation any time during hospitalization. SETTING: Twenty-one hospitals of Kaiser Permanente Northern California, an integrated healthcare delivery system. PATIENTS: We identified adults with positive severe acute respiratory syndrome coronavirus 2 polymerase chain reaction test within 3 weeks of, or during, hospitalization between February 1, 2020, and December 31, 2020. We calculated ROX at 12 hours after HFNC initiation. We grouped patients as low (≥ 4.88), intermediate (< 4.88 and ≥ 3.85), or high (< 3.85) risk using previously published thresholds. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified 1,847 patients who had no limitation of life support. Of these, 525 (31.7%) received invasive mechanical ventilation any time during hospitalization and 511 died (27.7%). The sensitivity, specificity, positive predictive value, and negative predictive value of 12-hour ROX threshold (< 3.85) predicting invasive mechanical ventilation were 32.3% (95% CI, 28.5-36.3%), 89.8% (95% CI, 88.0-91.4%), 59.4% (95% CI, 53.8-64.9%), and 74.1% (95% CI, 71.8-76.3%), respectively. CONCLUSIONS: The 12-hour ROX index has a positive predictive value (59.4%) using threshold of less than 3.85 for COVID-19 patients needing invasive mechanical ventilation. Our health system has embedded ROX into the electronic health record to prioritize rounding during periods of inpatient surge.

Evaluation Following Staggered Implementation of the "Rethinking Critical Care" ICU Care Bundle in a Multicenter Community Setting.

OBJECTIVES: To evaluate process metrics and outcomes after implementation of the "Rethinking Critical Care" ICU care bundle in a community setting. DESIGN: Retrospective interrupted time-series analysis. SETTING: Three hospitals in the Kaiser Permanente Northern California integrated healthcare delivery system. PATIENTS: ICU patients admitted between January 1, 2009, and August 30, 2013. INTERVENTIONS: Implementation of the Rethinking Critical Care ICU care bundle which is designed to reduce potentially preventable complications by focusing on the management of delirium, sedation, mechanical ventilation, mobility, ambulation, and coordinated care. Rethinking Critical Care implementation occurred in a staggered fashion between October 2011 and November 2012. MEASUREMENTS AND MAIN RESULTS: We measured implementation metrics based on electronic medical record data and evaluated the impact of implementation on mortality with multivariable regression models for 24,886 first ICU episodes in 19,872 patients. After implementation, some process metrics (e.g., ventilation start and stop times) were achieved at high rates, whereas others (e.g., ambulation distance), available late in the study period, showed steep increases in compliance. Unadjusted mortality decreased from 12.3% to 10.9% (p < 0.01) before and after implementation, respectively. The adjusted odds ratio for hospital mortality after implementation was 0.85 (95% CI, 0.73-0.99) and for 30-day mortality was 0.88 (95% CI, 0.80-0.97) compared with before implementation. However, the mortality rate trends were not significantly different before and after Rethinking Critical Care implementation. The mean duration of mechanical ventilation and hospital stay also did not demonstrate incrementally greater declines after implementation. CONCLUSIONS: Rethinking Critical Care implementation was associated with changes in practice and a 12-15% reduction in the odds of short-term mortality. However, these findings may represent an evaluation of changes in practices and outcomes still in the midimplementation phase and cannot be directly attributed to the elements of bundle implementation.