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.

Defining the transition from new to normal: a qualitative investigation of the clinical change process.

Background: Understanding how and when a new evidence-based clinical intervention becomes standard practice is crucial to ensure that healthcare is delivered in alignment with the most up-to-date knowledge. However, rigorous methods are needed to determine when a new clinical practice becomes normalized to the standard of care. To address this gap, this study qualitatively explores how, when, and why a clinical practice change becomes normalized within healthcare organizations. Methods: We used purposive sampling to recruit clinical leaders who worked in implementation science across diverse health contexts. Enrolled participants completed semi-structured interviews. Qualitative data analysis was guided by a modified version of the Normalization Process Theory (NPT) framework to identify salient themes. Identified normalization strategies were mapped to the Expert Recommendations for Implementation Change (ERIC) project. Results: A total of 17 individuals were interviewed. Participants described four key signals for identifying when a novel clinical practice becomes the new normal: 1) integration into existing workflows; 2) scaling across the entire organizational unit; 3) staff buy-in and ownership; and 4) sustainment without ongoing monitoring. Participants identified salient strategies to normalize new clinical interventions: 1) taking a patient approach; 2) gaining staff buy-in and ownership; and 3) conducting ongoing measurement of progress towards normalization. Conclusions: The results offer valuable insight into the indicators that signify when a novel clinical practice becomes normalized, and the strategies employed to facilitate this transition. These findings can inform future research to develop instruments that implementation leaders can use to systematically measure the clinical change process.

Intravenous Opioid Administration During Mechanical Ventilation and Use After Hospital Discharge.

Importance: Guidelines recommend an analgesia-first strategy for sedation during mechanical ventilation, but associations between opioids provided during mechanical ventilation and posthospitalization opioid-related outcomes are unclear. Objective: To evaluate associations between an intravenous opioid dose received during mechanical ventilation and postdischarge opioid-related outcomes in medical (nonsurgical) patients. Design, Setting, and Participants: This retrospective cohort study evaluated adults receiving mechanical ventilation lasting 24 hours or more for acute respiratory failure and surviving hospitalization. Participants from 21 Kaiser Permanente Northern California hospitals from January 1, 2012, to December 31, 2019, were included. Data were analyzed from October 1, 2020, to October 31, 2023. Exposures: Terciles of median daily intravenous fentanyl equivalents during mechanical ventilation. Main Outcomes and Measures: The primary outcome was the first filled opioid prescription in 1 year after discharge. Secondary outcomes included persistent opioid use and opioid-associated complications. Secondary analyses tested for interaction between opioid doses during mechanical ventilation, prior opioid use, and posthospitalization opioid use. Estimates were based on multivariable-adjusted time-to-event analyses, with death as a competing risk, and censored for hospice or palliative care referral, rehospitalization with receipt of opioid, or loss of Kaiser Permanente plan membership. Results: The study included 6746 patients across 21 hospitals (median age, 67 years [IQR, 57-76 years]; 53.0% male). Of the participants, 3114 (46.2%) filled an opioid prescription in the year prior to admission. The median daily fentanyl equivalent during mechanical ventilation was 200 µg (IQR, 40-1000 µg), with terciles of 0 to 67 µg, more than 67 to 700 µg, and more than 700 µg. Compared with patients who did not receive opioids during mechanical ventilation (n = 1013), a higher daily opioid dose was associated with opioid prescriptions in the year after discharge (n = 2942 outcomes; tercile 1: adjusted hazard ratio [AHR], 1.00 [95% CI, 0.85-1.17], tercile 2: AHR, 1.20 [95% CI, 1.03-1.40], and tercile 3: AHR, 1.25 [95% CI, 1.07-1.47]). Higher doses of opioids during mechanical ventilation were also associated with persistent opioid use after hospitalization (n = 1410 outcomes; tercile 3 vs no opioids: odds ratio, 1.44 [95% CI, 1.14-1.83]). No interaction was observed between opioid dose during mechanical ventilation, prior opioid use, and posthospitalization opioid use. Conclusions and Relevance: In this retrospective cohort study of patients receiving mechanical ventilation, opioids administered during mechanical ventilation were associated with opioid prescriptions following hospital discharge. Additional studies to evaluate risks and benefits of strategies using lower opioid doses are warranted.

SNAP: Supportive non-invasive ventilation for acute chest syndrome prevention for hospitalized children with sickle cell disease: Perspectives of patients, parents, and the healthcare team.

RATIONALE: Acute chest syndrome (ACS) often develops during hospitalizations for sickle cell disease (SCD) vaso-occlusive episodes and may be triggered by a combination of chest wall splinting, opioid use, hypoventilation, and atelectasis. In 2017, Boston Medical Center's general pediatric inpatient unit instituted the novel use of bi-level positive airway pressure (BiPAP) as "supportive non-invasive ventilation for ACS prevention" (SNAP) to prevent ACS and respiratory decompensation. OBJECTIVE: The goals of this qualitative study were to identify perceived benefits, harms, facilitators, and barriers to use of SNAP. METHODS: We conducted semi-structured key informant interviews at three sites with different levels of SNAP implementation (Site 1: extensive implementation; Site 2: limited implementation; Site 3: not yet implemented) regarding experiences with and/or perceptions of SNAP. Interviews and coding were guided by the Promoting Action on Research Implementation in Health Services (PARiHS) framework. RESULTS: Thirty-four participants (physicians, nurses, respiratory therapists, child life specialists, psychologists, youth with SCD, and parents) completed interviews. Major themes included: (i) participants perceive BiPAP as effective at preventing ACS, and for those with medically stable ACS, for preventing respiratory decompensation. (ii) BiPAP use is appropriate on the general pediatric inpatient unit for medically stable patients with SCD. (iii) Improving the patient experience is the most important factor to optimize acceptance of BiPAP by patients and families. CONCLUSION/FUTURE DIRECTIONS: SNAP is perceived as effective and appropriate for hospitalized pediatric patients with SCD. Improving the patient experience is the biggest challenge. These data will inform a future protocol for a multicenter hybrid effectiveness/implementation trial of SNAP.

In-Hospital vs 30-Day Sepsis Mortality at US Safety-Net and Non-Safety-Net Hospitals.

Importance: In-hospital mortality of patients with sepsis is frequently measured for benchmarking, both by researchers and policymakers. Prior studies have reported higher in-hospital mortality among patients with sepsis at safety-net hospitals compared with non-safety-net hospitals; however, in critically ill patients, in-hospital mortality rates are known to be associated with hospital discharge practices, which may differ between safety-net hospitals and non-safety-net hospitals. Objective: To assess how admission to safety-net hospitals is associated with 2 metrics of short-term mortality (in-hospital mortality and 30-day mortality) and discharge practices among patients with sepsis. Design, Setting, and Participants: Retrospective, national cohort study of Medicare fee-for-service beneficiaries aged 66 years and older, admitted with sepsis to an intensive care unit from January 2011 to December 2019 based on information from the Medicare Provider Analysis and Review File. Data were analyzed from October 2022 to September 2023. Exposure: Admission to a safety-net hospital (hospitals with a Medicare disproportionate share index in the top quartile per US region). Main Outcomes and Measures: Coprimary outcomes: in-hospital mortality and 30-day mortality. Secondary outcomes: (1) in-hospital do-not-resuscitate orders, (2) in-hospital palliative care delivery, (3) discharge to a postacute facility (skilled nursing facility, inpatient rehabilitation facility, or long-term acute care hospital), and (4) discharge to hospice. Results: Between 2011 and 2019, 2 551 743 patients with sepsis (mean [SD] age, 78.8 [8.2] years; 1 324 109 [51.9%] female; 262 496 [10.3%] Black, 2 137 493 [83.8%] White, and 151 754 [5.9%] other) were admitted to 666 safety-net hospitals and 1924 non-safety-net hospitals. Admission to safety-net hospitals was associated with higher in-hospital mortality (odds ratio [OR], 1.09; 95% CI, 1.06-1.13) but not 30-day mortality (OR, 1.01; 95% CI, 0.99-1.04). Admission to safety-net hospitals was associated with lower do-not-resuscitate rates (OR, 0.86; 95% CI, 0.81-0.91), palliative care delivery rates (OR, 0.66; 95% CI, 0.60-0.73), and hospice discharge (OR, 0.82; 95% CI, 0.78-0.87) but not with discharge to postacute facilities (OR, 0.98; 95% CI, 0.95-1.01). Conclusions and Relevance: In this cohort study, among patients with sepsis, admission to safety-net hospitals was associated with higher in-hospital mortality but not with 30-day mortality. Differences in in-hospital mortality may partially be explained by greater use of hospice at non-safety-net hospitals, which shifts attribution of death from the index hospitalization to hospice. Future investigations and publicly reported quality measures should consider time-delimited rather than hospital-delimited measures of short-term mortality to avoid undue penalty to safety-net hospitals with similar short-term mortality.

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.

A Novel Machine Learning Algorithm for Creating Risk-Adjusted Payment Formulas.

Importance: Models predicting health care spending and other outcomes from administrative records are widely used to manage and pay for health care, despite well-documented deficiencies. New methods are needed that can incorporate more than 70 000 diagnoses without creating undesirable coding incentives. Objective: To develop a machine learning (ML) algorithm, building on Diagnostic Item (DXI) categories and Diagnostic Cost Group (DCG) methods, that automates development of clinically credible and transparent predictive models for policymakers and clinicians. Design, Setting, and Participants: DXIs were organized into disease hierarchies and assigned an Appropriateness to Include (ATI) score to reflect vagueness and gameability concerns. A novel automated DCG algorithm iteratively assigned DXIs in 1 or more disease hierarchies to DCGs, identifying sets of DXIs with the largest regression coefficient as dominant; presence of a previously identified dominating DXI removed lower-ranked ones before the next iteration. The Merative MarketScan Commercial Claims and Encounters Database for commercial health insurance enrollees 64 years and younger was used. Data from January 2016 through December 2018 were randomly split 90% to 10% for model development and validation, respectively. Deidentified claims and enrollment data were delivered by Merative the following November in each calendar year and analyzed from November 2020 to January 2024. Main Outcome and Measures: Concurrent top-coded total health care cost. Model performance was assessed using validation sample weighted least-squares regression, mean absolute errors, and mean errors for rare and common diagnoses. Results: This study included 35 245 586 commercial health insurance enrollees 64 years and younger (65 901 460 person-years) and relied on 19 clinicians who provided reviews in the base model. The algorithm implemented 218 clinician-specified hierarchies compared with the US Department of Health and Human Services (HHS) hierarchical condition category (HCC) model's 64 hierarchies. The base model that dropped vague and gameable DXIs reduced the number of parameters by 80% (1624 of 3150), achieved an R2 of 0.535, and kept mean predicted spending within 12% ($3843 of $31 313) of actual spending for the 3% of people with rare diseases. In contrast, the HHS HCC model had an R2 of 0.428 and underpaid this group by 33% ($10 354 of $31 313). Conclusions and Relevance: In this study, by automating DXI clustering within clinically specified hierarchies, this algorithm built clinically interpretable risk models in large datasets while addressing diagnostic vagueness and gameability concerns.

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.

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.

Complication Rates of Central Venous Catheters: A Systematic Review and Meta-Analysis.

Importance: Central venous catheters (CVCs) are commonly used but are associated with complications. Quantifying complication rates is essential for guiding CVC utilization decisions. Objective: To summarize current rates of CVC-associated complications. Data Sources: MEDLINE, Embase, CINAHL, and CENTRAL databases were searched for observational studies and randomized clinical trials published between 2015 to 2023. Study Selection: This study included English-language observational studies and randomized clinical trials of adult patients that reported complication rates of short-term centrally inserted CVCs and data for 1 or more outcomes of interest. Studies that evaluated long-term intravascular devices, focused on dialysis catheters not typically used for medication administration, or studied catheters placed by radiologists were excluded. Data Extraction and Synthesis: Two reviewers independently extracted data and assessed risk of bias. Bayesian random-effects meta-analysis was applied to summarize event rates. Rates of placement complications (events/1000 catheters with 95% credible interval [CrI]) and use complications (events/1000 catheter-days with 95% CrI) were estimated. Main Outcomes and Measures: Ten prespecified complications associated with CVC placement (placement failure, arterial puncture, arterial cannulation, pneumothorax, bleeding events requiring action, nerve injury, arteriovenous fistula, cardiac tamponade, arrhythmia, and delay of ≥1 hour in vasopressor administration) and 5 prespecified complications associated with CVC use (malfunction, infection, deep vein thrombosis [DVT], thrombophlebitis, and venous stenosis) were assessed. The composite of 4 serious complications (arterial cannulation, pneumothorax, infection, or DVT) after CVC exposure for 3 days was also assessed. Results: Of 11 722 screened studies, 130 were included in the analyses. Seven of 15 prespecified complications were meta-analyzed. Placement failure occurred at 20.4 (95% CrI, 10.9-34.4) events per 1000 catheters placed. Other rates of CVC placement complications (per 1000 catheters) were arterial canulation (2.8; 95% CrI, 0.1-10), arterial puncture (16.2; 95% CrI, 11.5-22), and pneumothorax (4.4; 95% CrI, 2.7-6.5). Rates of CVC use complications (per 1000 catheter-days) were malfunction (5.5; 95% CrI, 0.6-38), infection (4.8; 95% CrI, 3.4-6.6), and DVT (2.7; 95% CrI, 1.0-6.2). It was estimated that 30.2 (95% CrI, 21.8-43.0) in 1000 patients with a CVC for 3 days would develop 1 or more serious complication (arterial cannulation, pneumothorax, infection, or DVT). Use of ultrasonography was associated with lower rates of arterial puncture (risk ratio [RR], 0.20; 95% CrI, 0.09-0.44; 13.5 events vs 68.8 events/1000 catheters) and pneumothorax (RR, 0.25; 95% CrI, 0.08-0.80; 2.4 events vs 9.9 events/1000 catheters). Conclusions and Relevance: Approximately 3% of CVC placements were associated with major complications. Use of ultrasonography guidance may reduce specific risks including arterial puncture and pneumothorax.

Efficacy of Digital Outreach Strategies for Collecting Smoking Data: Pragmatic Randomized Trial.

BACKGROUND: Tobacco smoking is an important risk factor for disease, but inaccurate smoking history data in the electronic medical record (EMR) limits the reach of lung cancer screening (LCS) and tobacco cessation interventions. Patient-generated health data is a novel approach to documenting smoking history; however, the comparative effectiveness of different approaches is unclear. OBJECTIVE: We designed a quality improvement intervention to evaluate the effectiveness of portal questionnaires compared to SMS text message-based surveys, to compare message frames, and to evaluate the completeness of patient-generated smoking histories. METHODS: We randomly assigned patients aged between 50 and 80 years with a history of tobacco use who identified English as a preferred language and have never undergone LCS to receive an EMR portal questionnaire or a text survey. The portal questionnaire used a "helpfulness" message, while the text survey tested frame types informed by behavior economics ("gain," "loss," and "helpfulness") and nudge messaging. The primary outcome was the response rate for each modality and framing type. Completeness and consistency with documented structured smoking data were also evaluated. RESULTS: Participants were more likely to respond to the text survey (191/1000, 19.1%) compared to the portal questionnaire (35/504, 6.9%). Across all text survey rounds, patients were less responsive to the "helpfulness" frame compared with the "gain" frame (odds ratio [OR] 0.29, 95% CI 0.09-0.91; P<.05) and "loss" frame (OR 0.32, 95% CI 11.8-99.4; P<.05). Compared to the structured data in the EMR, the patient-generated data were significantly more likely to be complete enough to determine LCS eligibility both compared to the portal questionnaire (OR 34.2, 95% CI 3.8-11.1; P<.05) and to the text survey (OR 6.8, 95% CI 3.8-11.1; P<.05). CONCLUSIONS: We found that an approach using patient-generated data is a feasible way to engage patients and collect complete smoking histories. Patients are likely to respond to a text survey using "gain" or "loss" framing to report detailed smoking histories. Optimizing an SMS text message approach to collect medical information has implications for preventative and follow-up clinical care beyond smoking histories, LCS, and smoking cessation therapy.

Comparative Effectiveness of Mepolizumab, Benralizumab, and Dupilumab among Patients with Difficult-to-Control Asthma: A Multicenter Retrospective Propensity-matched Analysis.

Rationale: The comparative effectiveness of biologic agents 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 starting treatment with dupilumab, mepolizumab, or benralizumab as documented in 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 nonrandomized treatment assignment; a prespecified α-level was set at 0.017 to account for three primary comparisons. The exposure of interest was the new initiation of dupilumab, benralizumab, or mepolizumab treatment. The primary outcome was the rate of asthma exacerbations in the 1 year after 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 ⩾12 years old (65% female; mean age, 49 yr), 3,943 started dupilumab, 1,902 started benralizumab, and 2,012 started mepolizumab, all 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 who initiated dupilumab had a significantly lower rate of asthma exacerbations (1.07 per year) compared with benralizumab (1.47 per year), with a rate ratio (RR) of 0.73 (95% confidence interval, 0.63-0.85), and also had a significantly lower rate of asthma exacerbations compared with mepolizumab (1.04 per year vs. 1.45 per year), with an RR of 0.72 (0.62-0.84). There was no statistically significant difference in the rate of asthma exacerbations between mepolizumab (1.40 per year) and benralizumab (1.41 per year), with an RR of 1.00 (0.85-1.17). Conclusions: In patients with difficult-to-control asthma who had newly initiated biologic therapy, dupilumab was associated with a decreased rate of asthma exacerbations in the 1 year after initiation compared with mepolizumab or benralizumab.

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.

Safety-Net Primary Care and Endocrinology Clinicians' Knowledge and Perspectives on Screening for Nonalcoholic Fatty Liver Disease: A Mixed-Methods Evaluation.

OBJECTIVE: Clinical guidelines have expanded the indications for nonalcoholic fatty liver disease (NAFLD) screening to type 2 diabetes mellitus and obesity, which are conditions common in populations who receive care in urban safety-net settings. This study aimed to evaluate safety-net primary care and endocrinology clinicians' knowledge of NAFLD, determine barriers and facilitators to screening, and examine perspectives on the use of electronic health record tools for risk assessment. METHODS: Sequential explanatory mixed methods using survey and qualitative interviews with primary care, primary care subspecialty, and endocrinology clinicians in an urban safety-net health care system. RESULTS: A total of 109 participants completed the survey (36.5% response rate), and 13 participated in interviews. Most respondents underestimated or did not know the prevalence of NAFLD (68%), did not use the recommended noninvasive tests for risk stratification (65%), and few were comfortable with screening for (27%) or managing (17%) NAFLD. Endocrinologists had greater knowledge of risk factors but lower rates of comfort and more often felt that screening was not their responsibility. The qualitative themes included the following: (1) lack of knowledge about screening, (2) concern for underdiagnosing NAFLD, (3) perception of severity impacts beliefs about screening, (4) screening should occur in primary care but is not normative practice, (5) concerns exist about benefit, (6) competing demands with a complex population hinder screening, and (7) a need for easier ways to integrate screening into practice. CONCLUSION: Knowledge gaps may hamper uptake of new guidelines for NAFLD screening in primary care and endocrinology clinics in an urban safety-net health care system. Implementation strategies focused on training and educating clinicians and informed by behavioral economics may increase screening.