Predicting stroke risk after sepsis hospitalization with new-onset atrial fibrillation.

BACKGROUND: New-onset atrial fibrillation (AF) during sepsis is common, but models designed to stratify stroke risk excluded patients with secondary AF. We assessed the predictive validity of CHA2DS2VASc scores among patients with new-onset AF during sepsis and developed a novel stroke prediction model incorporating presepsis and intrasepsis characteristics. METHODS: We included patients ≥40 years old who survived hospitalizations with sepsis and new-onset AF across 21 Kaiser Permanente Northern California hospitals from January 1, 2011 to September 30, 2017. We calculated the area under the receiver operating curve (AUC) for CHA2DS2VASc scores to predict stroke or transient ischemic attack (TIA) within 1 year after a hospitalization with new-onset AF during sepsis using Fine-Gray models with death as competing risk. We similarly derived and validated a novel model using presepsis and intrasepsis characteristics associated with 1-year stroke/TIA risk. RESULTS: Among 82,748 adults hospitalized with sepsis, 3992 with new-onset AF (median age: 80 years, median CHA2DS2VASc of 4) survived to discharge, among whom 70 (2.1%) experienced stroke or TIA outcome and 1393 (41.0%) died within 1 year of sepsis. The CHA2DS2VASc score was not predictive of stroke risk after sepsis (AUC: 0.50, 95% confidence interval [CI]: 0.48-0.52). A newly derived model among 2555 (64%) patients in the derivation set and 1437 (36%) in the validation set included 13 variables and produced an AUC of 0.61 (0.49-0.73) in derivation and 0.54 (0.43-0.65) in validation. CONCLUSION: Current models do not accurately stratify risk of stroke following new-onset AF secondary to sepsis. New tools are required to guide anticoagulation decisions following new-onset AF in sepsis.

Variation in Sedative and Analgesic Use During the COVID-19 Pandemic and Associated Outcomes.

BACKGROUND: Providing analgesia and sedation is an essential component of caring for many mechanically ventilated patients. The selection of analgesic and sedative medications during the COVID-19 pandemic, and the impact of these sedation practices on patient outcomes, remain incompletely characterized. RESEARCH QUESTION: What were the hospital patterns of analgesic and sedative use for patients with COVID-19 who received mechanical ventilation (MV), and what differences in clinical patient outcomes were observed across prevailing sedation practices? STUDY DESIGN AND METHODS: We conducted an observational cohort study of hospitalized adults who received MV for COVID-19 from February 2020 through April 2021 within the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) COVID-19 Registry. To describe common sedation practices, we used hierarchical clustering to group hospitals based on the percentage of patients who received various analgesic and sedative medications. We then used multivariable regression models to evaluate the association between hospital analgesia and sedation cluster and duration of MV (with a placement of death [POD] approach to account for competing risks). RESULTS: We identified 1,313 adults across 35 hospitals admitted with COVID-19 who received MV. Two clusters of analgesia and sedation practices were identified. Cluster 1 hospitals generally administered opioids and propofol with occasional use of additional sedatives (eg, benzodiazepines, alpha-agonists, and ketamine); cluster 2 hospitals predominantly used opioids and benzodiazepines without other sedatives. As compared with patients in cluster 2, patients admitted to cluster 1 hospitals underwent a shorter adjusted median duration of MV with POD (ß-estimate, -5.9; 95% CI, -11.2 to -0.6; P = .03). INTERPRETATION: Patients who received MV for COVID-19 in hospitals that prioritized opioids and propofol for analgesia and sedation experienced shorter adjusted median duration of MV with POD as compared with patients who received MV in hospitals that primarily used opioids and benzodiazepines.

Outcomes of Acute Respiratory Failure in Patients With Cancer in the United States.

OBJECTIVE: To determine the epidemiological effect-magnitude and outcomes of patients with cancer vs those without cancer who are hospitalized with acute respiratory failure (ARF). PATIENTS AND METHODS: We reviewed hospitalizations within the National Inpatient Sample (NIS) database between January 1, 2016, and December 31, 2018. Patients were classified based on a diagnosis of solid-organ cancer, hematologic cancer, or no cancer. Noninvasive positive pressure ventilation (NIPPV) failure was defined as patients who initially received NIPPV and had progression to invasive mechanical ventilation. Weighted samples were used to derive population estimates. RESULTS: During the study period, there were an estimated 8,837,209 admissions with ARF in the United States, 8.9% (783,625) of which had solid-organ cancer and 2.0% (176,095) had hematologic cancers. Annually, 319,907 patients with cancer are admitted with ARF, with 27.3% (87,302) requiring invasive mechanical ventilation and 10.0% (31,998) requiring NIPPV. In-hospital mortality was higher in patients with cancer vs those without cancer (24.0% [76,813] vs 12.3% [322,465]; P<.001), and this proprotion persisted when stratified by the highest method of oxygen delivery. Patients with cancer had longer hospital length of stay (7.0 days [3.0 to 12.0 days] vs 5.0 days [3.0 to 10.0 days]; P<.001) and were more likely to have NIPPV failure (14.9% [3,992] vs 12.8% [41,875]). Compared with those with solid-organ cancer, patients with hematologic cancers experienced worse outcomes. The association between underlying cancer diagnosis and outcomes remained consistent when adjusted for age, sex, and comorbidities. CONCLUSION: In the United States, patients with cancer account for over 10% of ARF hospital admissions (959,720 of 8,837,209). They experience an approximately 2-fold higher mortality versus those without cancer. Those with hematologic cancers appear to experience worse outcomes than patients with solid-organ cancers.

Variation in Use of Medications for Opioid Use Disorder in Critically Ill Patients Across the United States.

OBJECTIVES: To describe practice patterns surrounding the use of medications to treat opioid use disorder (MOUD) in critically ill patients. DESIGN: Retrospective, multicenter, observational study using the Premier AI Healthcare Database. SETTING: The study was conducted in U.S. ICUs. PATIENTS: Adult (≥ 18 yr old) patients with a history of opioid use disorder (OUD) admitted to an ICU between 2016 and 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 108,189 ICU patients (658 hospitals) with a history of OUD, 20,508 patients (19.0%) received MOUD. Of patients receiving MOUD, 13,745 (67.0%) received methadone, 2,950 (14.4%) received buprenorphine, and 4,227 (20.6%) received buprenorphine/naloxone. MOUD use occurred in 37.9% of patients who received invasive mechanical ventilation. The median day of MOUD initiation was hospital day 2 (interquartile range [IQR] 1-3) and the median duration of MOUD use was 4 days (IQR 2-8). MOUD use per hospital was highly variable (median 16.0%; IQR 10-24; range, 0-70.0%); admitting hospital explained 8.9% of variation in MOUD use. A primary admitting diagnosis of unintentional poisoning (aOR 0.41; 95% CI, 0.38-0.45), presence of an additional substance use disorder (aOR 0.66; 95% CI, 0.64-0.68), and factors indicating greater severity of illness were associated with reduced odds of receiving MOUD in the ICU. CONCLUSIONS: In a large multicenter, retrospective study, there was large variation in the use of MOUD among ICU patients with a history of OUD. These results inform future studies seeking to optimize the approach to MOUD use during critical illness.

A novel measure to summarize blood transfusion practice during critical illness.

BACKGROUND: Large-scale observational studies have summarized transfusion practice using traditional measures of central tendency (e.g., the mean hemoglobin concentration at the time of transfusion). However, the mean hemoglobin concentration fails to identify specific hemoglobin concentration thresholds that drive practice. In the following brief report, we propose a novel measure of "practice discontinuity" that identifies specific practice-defining hemoglobin thresholds. STUDY DESIGN AND METHODS: We used the PINC AI Database (2016-2022) to identify adult patients admitted to an intensive care unit with at least one hemoglobin concentration measurement. For each day that hemoglobin was measured, we identified whether the patient received a red blood cell transfusion using hospital charge codes. We defined the "practice discontinuity" measure as the hemoglobin concentration at which there was the largest increase in transfusion use going from a higher to an incrementally lower hemoglobin concentration. We also calculated the mean and median pretransfusion hemoglobin concentrations. RESULTS: We identified 1,298,367 patients and 4,905,839 patient-days for inclusion. RBC transfusion occurred in a total of 530,654 (10.8%) patient-days. The overall pre-transfusion mean and median hemoglobin concentrations were 8.4 and 8.0 g/dL, respectively. The practice discontinuity measure identified 7.0 g/dL as the hemoglobin concentration at which transfusion use increased the most, from 46.6% of patient-days at a concentration of 7.0 g/dL to 74.8% of patient-days at a concentration of 6.9 g/dL. DISCUSSION: We propose that future studies of red blood cell transfusion practice consider inclusion of the practice discontinuity measure to more fully summarize clinical practice.

Incidence and prognostic significance of newly-diagnosed atrial fibrillation among older U.S. veterans hospitalized with COVID-19.

Most prior studies on the prognostic significance of newly-diagnosed atrial fibrillation (AF) in COVID-19 did not differentiate newly-diagnosed AF from pre-existing AF. To determine the association between newly-diagnosed AF and in-hospital and 30-day mortality among regular users of Veterans Health Administration using data linked to Medicare. We identified Veterans aged ≥ 65 years who were hospitalized for ≥ 24 h with COVID-19 from 06/01/2020 to 1/31/2022 and had ≥ 2 primary care visits within 24 months prior to the index hospitalization. We performed multivariable logistic regression analyses to estimate adjusted risks, risk differences (RD), and odds ratios (OR) for the association between newly-diagnosed AF and the mortality outcomes adjusting for patient demographics, baseline comorbidities, and presence of acute organ dysfunction on admission. Of 23,299 patients in the study cohort, 5.3% had newly-diagnosed AF, and 29.2% had pre-existing AF. In newly-diagnosed AF adjusted in-hospital and 30-day mortality were 16.5% and 22.7%, respectively. Newly-diagnosed AF was associated with increased mortality compared to pre-existing AF (in-hospital: OR 2.02, 95% confidence interval [CI] 1.72-2.37; RD 7.58%, 95% CI 5.54-9.62) (30-day: OR 1.86; 95% CI 1.60-2.16; RD 9.04%, 95% CI 6.61-11.5) or no AF (in-hospital: OR 2.24, 95% CI 1.93-2.60; RD 8.40%, 95% CI 6.44-10.4) (30-day: 2.07, 95% CI 1.80-2.37; RD 10.2%, 95% CI 7.89-12.6). There was a smaller association between pre-existing AF and the mortality outcomes. Newly-diagnosed AF is an important prognostic marker for patients hospitalized with COVID-19. Whether prevention or treatment of AF improves clinical outcomes in these patients remains unknown.

Effectiveness of Fludrocortisone Plus Hydrocortisone versus Hydrocortisone Alone in Septic Shock: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.

Rationale: The use of hydrocortisone in adult patients with septic shock is controversial, and the effectiveness of adding fludrocortisone to hydrocortisone remains uncertain. Objectives: To assess the comparative effectiveness and safety of fludrocortisone plus hydrocortisone, hydrocortisone alone, and placebo or usual care in adults with septic shock. Methods: A systematic review and a Bayesian network meta-analysis of peer-reviewed randomized trials were conducted. The primary outcome was all-cause mortality at last follow-up. Treatment effects are presented as relative risks (RRs) with 95% credible intervals (CrIs). Placebo or usual care was the reference treatment. Measurements and Main Results: Among 7,553 references, we included 17 trials (7,688 patients). All-cause mortality at last follow-up was lowest with fludrocortisone plus hydrocortisone (RR, 0.85; 95% CrI, 0.72-0.99; 98.3% probability of superiority, moderate-certainty evidence), followed by hydrocortisone alone (RR, 0.97; 95% CrI, 0.87-1.07; 73.1% probability of superiority, low-certainty evidence). The comparison of fludrocortisone plus hydrocortisone versus hydrocortisone alone was based primarily on indirect evidence (only two trials with direct evidence). Fludrocortisone plus hydrocortisone was associated with a 12% lower risk of all-cause mortality compared with hydrocortisone alone (RR, 0.88; 95% CrI, 0.74-1.03; 94.2% probability of superiority, moderate-certainty evidence). Conclusions: In adult patients with septic shock, fludrocortisone plus hydrocortisone was associated with lower risk of all-cause mortality at last follow-up than placebo and hydrocortisone alone. The scarcity of head-to-head trials comparing fludrocortisone plus hydrocortisone versus hydrocortisone alone led our network meta-analysis to rely primarily on indirect evidence for this comparison. Although we undertook several sensitivity analyses and assessments, these findings should be considered while also acknowledging the heterogeneity of included trials.

Comparative Effectiveness of Mepolizumab, Benralizumab and Dupilumab among Patients with Difficult-to-Control Asthma.

Rationale The comparative effectiveness of biologics used as add-on therapy in the management of difficult-to-control asthma is unclear. Objective To compare the effectiveness of dupilumab, mepolizumab and benralizumab among patients with difficult-to-control asthma. Methods Retrospective multicenter cohort study of adult patients with difficult-to-control asthma started on dupilumab, mepolizumab or benralizumab from a multicenter electronic health record and claims-based database between October 19, 2018 and September 30, 2022. Propensity score matching was used to minimize bias from non-randomized treatment assignment; prespecified alpha level was set at 0.017 to account for three primary comparisons. The exposure of interest was new initiation of dupilumab, benralizumab or mepolizumab. The primary outcome was the rate of asthma exacerbation in the year following initiation of biologic therapy modeled using a negative binomial approach. Results Among 893,668 patients with asthma who were prescribed an inhaled corticosteroid and were at least 12 years old, (65% female, mean age 49), 3,943 started dupilumab, 1,902 started benralizumab, and 2,012 started mepolizumab without an alternative indication for biologic therapy. After matching, there were 1,805 patients in each group for comparisons between dupilumab and benralizumab, 1,865 for comparisons between dupilumab and mepolizumab, and 1,721 for comparisons between mepolizumab and benralizumab. For all pairwise comparisons, covariates were well balanced after matching (all standardized mean differences <0.1). Patients initiating dupilumab had a significantly lower rate of asthma exacerbations (1.07/year) compared to benralizumab (1.47/year) with a rate ratio of 0.73 [95% confidence interval (CI) 0.63-0.85] and also had a significantly lower rate of asthma exacerbations compared to mepolizumab (1.04/year compared to 1.45/year) with a rate ratio of 0.72 [0.62-0.84]. There was no statistically significant difference in the rate of asthma exacerbations between mepolizumab (1.40/year) and benralizumab (1.41/year) with a rate ratio of 1.00 [CI 0.85-1.17]. Conclusions In patients with difficult-to-control asthma newly initiated on biologic therapy, dupilumab was associated with a decreased rate of asthma exacerbations in the year after initiation as compared with mepolizumab or benralizumab.

Racial Differences in 1-Year Mortality after Hospitalization for Chronic Obstructive Pulmonary Disease in the United States.

Rationale: One quarter of Medicare beneficiaries hospitalized for chronic obstructive pulmonary disease (COPD) die within 1 year. Although overall mortality rates are higher among White patients with COPD, racial and ethnic differences in the vulnerable period following hospitalization are unknown.Objectives: To determine the association between race and ethnicity and mortality following COPD hospitalization and to evaluate the extent to which differences are explained by clinical, geographic, socioeconomic, and post-acute care factors among Medicare beneficiaries in the United States.Methods: In this retrospective cohort study of Medicare beneficiaries hospitalized for COPD exacerbation, we constructed Cox regression models for 1-year mortality accounting for hospital-level clustering; sequentially adjusting for clinical, geographic, neighborhood socioeconomic, and post-acute care characteristics; and stratifying by sex and individual socioeconomic status.Results: Among 244,624 hospitalizations, Medicare beneficiaries of racial and ethnic minority groups had a lower risk of dying within 1 year of hospitalization than those of White race (hazard ratios, 0.78 [95% confidence interval, 0.75-0.80] for Black patients, 0.79 [0.76-0.82] for Hispanic patients, and 0.82 [0.77-0.86] for others). Differences in visits to physicians, attendance of pulmonary rehabilitation, and discharge disposition explained some of the mortality gap among dual-eligible beneficiaries but not among non-dual-eligible beneficiaries.Conclusions: Medicare beneficiaries of White race are at greater risk of mortality following COPD hospitalization compared with beneficiaries of minority race and ethnicity groups. Our findings should be interpreted in the context of the selection of a hospitalized population and a potentially incomplete assessment of illness severity in administrative data, and warrant further investigation.

Practice Patterns and Outcomes of Potassium Repletion Thresholds during Critical Illness.

Rationale: Potassium repletion is common in critically ill patients. However, practice patterns and outcomes related to different intensive care unit (ICU) potassium repletion strategies are unclear. Objectives: 1) Describe potassium repletion practices in critically ill adults; 2) compare the effectiveness of potassium repletion strategies; and 3) compare effectiveness and safety of specific potassium repletion thresholds on patient outcomes. Methods: This was a retrospective analysis of the PINC AI Healthcare Database (2016-2022), including all critically ill adults admitted to an ICU on Hospital Day 1 and with a serum potassium concentration measured on Hospital Day 2. We determined the frequency of potassium repletion (any formulation) at each measured serum potassium concentration in each ICU, then classified ICUs as having threshold-based (a large increase in potassium repletion rates at a specific serum potassium concentration) or probabilistic (linear relationship between serum concentration and the repletion probability) patterns of repletion. Between patients in threshold-based and probabilistic repletion ICUs, we compared outcomes (primary outcome: potassium repletion frequency). We reported unadjusted percentages per exposure group and the adjusted odds ratios (from hierarchical regression models) for each outcome. Among patients in threshold-based ICUs with the most common repletion thresholds (3.5 mEq/L and 4.0 mEq/L), we conducted regression discontinuity analyses to examine the effectiveness of potassium repletion at each potassium threshold. Results: We included 190,490 patients in 88 ICUs; 35.0% received at least one dose of potassium on the same calendar day. Rates of potassium repletion were similar between 22 threshold-based strategy ICUs (33.5%) and 22 probabilistic strategy ICUs (36.4%). There was no difference in the adjusted risk of potassium repletion between patients admitted to threshold-based strategy ICUs versus probabilistic strategy ICUs (adjusted odds ratio, 1.09; 95% confidence interval [CI], 0.76-1.57). In regression discontinuity analysis, crossing the 3.5 mEq/L threshold from high to low potassium levels resulted in a 39.1% (95% CI, 23.7-42.4) absolute increase in potassium repletion but no change in other outcomes. Similarly, crossing the 4.0 mEq/L threshold resulted in a 36.4% (95% CI, 22.4-42.2) absolute increase in potassium repletion but no change in other outcomes. Conclusions: Potassium repletion is common in critically ill patients and occurs over a narrow range of "normal" potassium levels (3.5-4.0 mEq/L); use of a threshold-based repletion strategy to guide potassium repletion in ICU patients is not associated with clinically meaningful differences in outcomes.

Clinical risk factors and blood protein biomarkers of 10-year pneumonia risk.

Background: Chronic inflammation may increase susceptibility to pneumonia. Research Question: To explore associations between clinical comorbidities, serum protein immunoassays, and long-term pneumonia risk. Methods: Framingham Heart Study Offspring Cohort participants ≥65 years were linked to their Centers for Medicare Services claims data. Clinical data and 88 serum protein immunoassays were evaluated for associations with 10-year incident pneumonia risk using Fine-Gray models for competing risks of death and least absolute shrinkage and selection operators for covariate selection. Results: We identified 1,370 participants with immunoassays and linkage to Medicare data. During 10 years of follow up, 428 (31%) participants had a pneumonia diagnosis. Chronic pulmonary disease [subdistribution hazard ratio (SHR) 1.87; 95% confidence interval (CI), 1.33-2.61], current smoking (SHR 1.79, CI 1.31-2.45), heart failure (SHR 1.74, CI 1.10-2.74), atrial fibrillation/flutter (SHR 1.43, CI 1.06-1.93), diabetes (SHR 1.36, CI 1.05-1.75), hospitalization within one year (SHR 1.34, CI 1.09-1.65), and age (SHR 1.06 per year, CI 1.04-1.08) were associated with pneumonia. Three baseline serum protein measurements were associated with pneumonia risk independent of measured clinical factors: growth differentiation factor 15 (SHR 1.32; CI 1.02-1.69), C-reactive protein (SHR 1.16, CI 1.06-1.27) and matrix metallopeptidase 8 (SHR 1.14, CI 1.01-1.30). Addition of C-reactive protein to the clinical model improved prediction (Akaike information criterion 4950 from 4960; C-statistic of 0.64 from 0.62). Conclusions: Clinical comorbidities and serum immunoassays were predictive of pneumonia risk. C-reactive protein, a routinely-available measure of inflammation, modestly improved pneumonia risk prediction over clinical factors. Our findings support the hypothesis that prior inflammation may increase the risk of pneumonia.

Patient Outcomes After Long-Term Acute Care Hospital Closures.

Importance: Long-term acute care hospitals (LTCHs) are common sites of postacute care for patients recovering from severe respiratory failure requiring mechanical ventilation (MV). However, federal payment reform led to the closure of many LTCHs in the US, and it is unclear how closure of LTCHs may have affected upstream care patterns at short-stay hospitals and overall patient outcomes. Objective: To estimate the association between LTCH closures and short-stay hospital care patterns and patient outcomes. Design, Setting, and Participants: This retrospective, national, matched cohort study used difference-in-differences analysis to compare outcomes at short-stay hospitals reliant on LTCHs that closed during 2012 to 2018 with outcomes at control hospitals. Data were obtained from the Medicare Provider Analysis and Review File, 2011 to 2019. Participants included Medicare fee-for-service beneficiaries aged 66 years and older receiving MV for at least 96 hours in an intensive care unit (ie, patients at-risk for prolonged MV) and the subgroup also receiving a tracheostomy (ie, receiving prolonged MV). Data were analyzed from October 2022 to June 2023. Exposure: Admission to closure-affected hospitals, defined as those discharging at least 60% of patients receiving a tracheostomy to LTCHs that subsequently closed, vs control hospitals. Main Outcomes and Measures: Upstream hospital care pattern outcomes were short-stay hospital do-not-resuscitate orders, palliative care delivery, tracheostomy placement, and discharge disposition. Patient outcomes included hospital length of stay, days alive and institution free within 90 days, spending per days alive within 90 days, and 90-day mortality. Results: Between 2011 and 2019, 99 454 patients receiving MV for at least 96 hours at 1261 hospitals were discharged to 459 LTCHs; 84 LTCHs closed. Difference-in-differences analysis included 8404 patients (mean age, 76.2 [7.2] years; 4419 [52.6%] men) admitted to 45 closure-affected hospitals and 45 matched-control hospitals. LTCH closure was associated with decreased LTCH transfer rates (difference, -5.1 [95% CI -8.2 to -2.0] percentage points) and decreased spending-per-days-alive (difference, -$8701.58 [95% CI, -$13 323.56 to -$4079.60]). In the subgroup of patients receiving a tracheostomy, there was additionally an increase in do-not-resuscitate rates (difference, 10.3 [95% CI, 4.2 to 16.3] percentage points) and transfer to skilled nursing facilities (difference, 10.0 [95% CI, 4.2 to 15.8] percentage points). There was no significant association of closure with 90-day mortality. Conclusions and Relevance: In this cohort study, LTCH closure was associated with changes in discharge patterns in patients receiving mechanical ventilation for at least 96 hours and advanced directive decisions in the subgroup receiving a tracheostomy, without change in mortality. Further studies are needed to understand how LTCH availability may be associated with other important outcomes, including functional outcomes and patient and family satisfaction.

Validation of automated data abstraction for SCCM discovery VIRUS COVID-19 registry: practical EHR export pathways (VIRUS-PEEP).

Background: The gold standard for gathering data from electronic health records (EHR) has been manual data extraction; however, this requires vast resources and personnel. Automation of this process reduces resource burdens and expands research opportunities. Objective: This study aimed to determine the feasibility and reliability of automated data extraction in a large registry of adult COVID-19 patients. Materials and methods: This observational study included data from sites participating in the SCCM Discovery VIRUS COVID-19 registry. Important demographic, comorbidity, and outcome variables were chosen for manual and automated extraction for the feasibility dataset. We quantified the degree of agreement with Cohen's kappa statistics for categorical variables. The sensitivity and specificity were also assessed. Correlations for continuous variables were assessed with Pearson's correlation coefficient and Bland-Altman plots. The strength of agreement was defined as almost perfect (0.81-1.00), substantial (0.61-0.80), and moderate (0.41-0.60) based on kappa statistics. Pearson correlations were classified as trivial (0.00-0.30), low (0.30-0.50), moderate (0.50-0.70), high (0.70-0.90), and extremely high (0.90-1.00). Measurements and main results: The cohort included 652 patients from 11 sites. The agreement between manual and automated extraction for categorical variables was almost perfect in 13 (72.2%) variables (Race, Ethnicity, Sex, Coronary Artery Disease, Hypertension, Congestive Heart Failure, Asthma, Diabetes Mellitus, ICU admission rate, IMV rate, HFNC rate, ICU and Hospital Discharge Status), and substantial in five (27.8%) (COPD, CKD, Dyslipidemia/Hyperlipidemia, NIMV, and ECMO rate). The correlations were extremely high in three (42.9%) variables (age, weight, and hospital LOS) and high in four (57.1%) of the continuous variables (Height, Days to ICU admission, ICU LOS, and IMV days). The average sensitivity and specificity for the categorical data were 90.7 and 96.9%. Conclusion and relevance: Our study confirms the feasibility and validity of an automated process to gather data from the EHR.

Effect of Respiratory Viral Panel Adoption on Antibiotic Use in Ventilated Patients.

Rationale: Rapid respiratory viral panel (RVP) testing has become widely used to aid in the diagnosis and treatment of acute respiratory failure. However, the impact of RVP on antibiotic stewardship in critically ill patients is unclear. Objectives: To assess if adoption of RVP testing at hospitals was associated with changes in antibiotic duration in intensive care unit patients receiving invasive mechanical ventilation. Methods: With data from the Premier Inc. database from 2016 to 2019, we used interrupted time series with multivariable hierarchical linear regression models to quantify trends in outcomes for 31,644 patients in the 12 months before RVP adoption, the level change in outcomes at the time of RVP adoption (estimand of interest), and changes in outcome trends in the 12 months after RVP adoption. Results: Hospital adoption of RVP testing (n = 62,603) was associated with a decrease in days of antibiotics by 0.5 days (95% confidence interval, -0.8, -0.1) in the first month after adoption. There was also a significant decrease in the risk of Clostridioides difficile infection by 0.9% (95% confidence interval, -1.6, -0.3). There were no significant changes in other outcomes, including hospitalization costs, hospital length of stay, or rates of ventilator-associated pneumonia. Conclusions: Hospital adoption of RVP testing was associated with modest reductions in both antibiotic duration and risk of C. difficile infection among intensive care unit patients with acute respiratory failure and suspected infection.

Implementation of a Virtual Interprofessional ICU Learning Collaborative: Successes, Challenges, and Initial Reactions From the Structured Team-Based Optimal Patient-Centered Care for Virus COVID-19 Collaborators.

Initial Society of Critical Care Medicine Discovery Viral Infection and Respiratory illness Universal Study (VIRUS) Registry analysis suggested that improvements in critical care processes offered the greatest modifiable opportunity to improve critically ill COVID-19 patient outcomes. OBJECTIVES: The Structured Team-based Optimal Patient-Centered Care for Virus COVID-19 ICU Collaborative was created to identify and speed implementation of best evidence based COVID-19 practices. DESIGN SETTING AND PARTICIPANTS: This 6-month project included volunteer interprofessional teams from VIRUS Registry sites, who received online training on the Checklist for Early Recognition and Treatment of Acute Illness and iNjury approach, a structured and systematic method for delivering evidence based critical care. Collaborators participated in weekly 1-hour videoconference sessions on high impact topics, monthly quality improvement (QI) coaching sessions, and received extensive additional resources for asynchronous learning. MAIN OUTCOMES AND MEASURES: Outcomes included learner engagement, satisfaction, and number of QI projects initiated by participating teams. RESULTS: Eleven of 13 initial sites participated in the Collaborative from March 2, 2021, to September 29, 2021. A total of 67 learners participated in the Collaborative, including 23 nurses, 22 physicians, 10 pharmacists, nine respiratory therapists, and three nonclinicians. Site attendance among the 11 sites in the 25 videoconference sessions ranged between 82% and 100%, with three sites providing at least one team member for 100% of sessions. The majority reported that topics matched their scope of practice (69%) and would highly recommend the program to colleagues (77%). A total of nine QI projects were initiated across three clinical domains and focused on improving adherence to established critical care practice bundles, reducing nosocomial complications, and strengthening patient- and family-centered care in the ICU. Major factors impacting successful Collaborative engagement included an engaged interprofessional team; an established culture of engagement; opportunities to benchmark performance and accelerate institutional innovation, networking, and acclaim; and ready access to data that could be leveraged for QI purposes. CONCLUSIONS AND RELEVANCE: Use of a virtual platform to establish a learning collaborative to accelerate the identification, dissemination, and implementation of critical care best practices for COVID-19 is feasible. Our experience offers important lessons for future collaborative efforts focused on improving ICU processes of care.