Validity of inpatient electronic health record-based measures of oxygen-related therapy in the United States: Lessons applicable for studying COVID-19 endpoints.

INTRODUCTION: During the COVID-19 pandemic, inpatient electronic health records (EHRs) have been used to conduct public health surveillance and assess treatments and outcomes. Invasive mechanical ventilation (MV) and supplemental oxygen (O2) use are markers of severe illness in hospitalized COVID-19 patients. In a large US system (n = 142 hospitals), we assessed documentation of MV and O2 use during COVID-19 hospitalization in administrative data versus nursing documentation. METHODS: We identified 319 553 adult hospitalizations with a COVID-19 diagnosis, February 2020-October 2022, and extracted coded, administrative data for MV or O2. Separately, we developed classification rules for MV or O2 supplementation from semi-structured nursing documentation. We assessed MV and O2 supplementation in administrative data versus nursing documentation and calculated ordinal endpoints of decreasing COVID-19 disease severity. Nursing documentation was considered the gold standard in sensitivity and positive predictive value (PPV) analyses. RESULTS: In nursing documentation, the prevalence of MV and O2 supplementation among COVID-19 hospitalizations was 14% and 75%, respectively. The sensitivity of administrative data was 83% for MV and 41% for O2, with both PPVs above 91%. Concordance between sources was 97% for MV (κ = 0.85), and 54% for O2 (κ = 0.21). For ordinal endpoints, administrative data accurately identified intensive care and MV but underestimated hospitalizations with O2 requirements (42% vs. 18%). CONCLUSIONS: In comparison to nursing documentation, administrative data under-ascertained O2 supplementation but accurately estimated severe endpoints such as MV. Nursing documentation improved ascertainment of O2 among COVID-19 hospitalizations and can capture oxygen requirements in adults hospitalized with COVID-19 or other respiratory illnesses.

Treatment and care received by children hospitalized with COVID-19 in a large hospital network in the United States, February 2020 to September 2021.

We described care received by hospitalized children with COVID-19 or multi-system inflammatory syndrome (MIS-C) prior to the 2021 COVID-19 Omicron variant surge in the US. We identified hospitalized children <18 years of age with a COVID-19 or MIS-C diagnosis (COVID-19 not required), separately, from February 2020-September 2021 (n = 126 hospitals). We described high-risk conditions, inpatient treatments, and complications among these groups. Among 383,083 pediatric hospitalizations, 2,186 had COVID-19 and 395 had MIS-C diagnosis. Less than 1% had both COVID-19 and MIS-C diagnosis (n = 154). Over half were >6 years old (54% COVID-19, 70% MIS-C). High-risk conditions included asthma (14% COVID-19, 11% MIS-C), and obesity (9% COVID-19, 10% MIS-C). Pulmonary complications in children with COVID-19 included viral pneumonia (24%) and acute respiratory failure (11%). In reference to children with COVID-19, those with MIS-C had more hematological disorders (62% vs 34%), sepsis (16% vs 6%), pericarditis (13% vs 2%), myocarditis (8% vs 1%). Few were ventilated or died, but some required oxygen support (38% COVID-19, 45% MIS-C) or intensive care (42% COVID-19, 69% MIS-C). Treatments included: methylprednisolone (34% COVID-19, 75% MIS-C), dexamethasone (25% COVID-19, 15% MIS-C), remdesivir (13% COVID-19, 5% MIS-C). Antibiotics (50% COVID-19, 68% MIS-C) and low-molecular weight heparin (17% COVID-19, 34% MIS-C) were frequently administered. Markers of illness severity among hospitalized children with COVID-19 prior to the 2021 Omicron surge are consistent with previous studies. We report important trends on treatments in hospitalized children with COVID-19 to improve the understanding of real-world treatment patterns in this population.

A cohort study to assess risk of cutaneous small vessel vasculitis among users of different oral anticoagulants.

PURPOSE: Cutaneous small vessel vasculitis (CSVV) was identified as a safety signal among patients treated with direct oral anticoagulants (DOAC). This study aimed to determine if CSVV risk differed among patients with atrial fibrillation (Afib) who newly initiated warfarin or a DOAC. METHODS: We identified enrollees aged ≥21 years diagnosed with Afib who newly initiated rivaroxaban, dabigatran, apixaban, and warfarin in the Sentinel Distributed Database from October 19, 2010 to February 29, 2020. We selected and followed patients who did not have evidence of the following in the 183 days prior to initiating treatment: CSVV diagnosis, dispensing of other study drugs, select autoimmune diseases or autoimmune medications, cancer diagnoses or chemotherapeutic treatment, kidney dialysis or transplant, alternative anticoagulation indications, or an institutional (nursing home, hospice, hospital) stay on the treatment initiation date (index date) until CSVV outcome or pre-specified censoring. We conducted 1:1 propensity score matching in six comparisons. RESULTS: CSVV incidence rates for DOACs and warfarin ranged from 3.3 to 5.6 per 10 000-person years in our matched Afib population. The adjusted CSVV hazard ratio (HR) and 95% confidence interval (CI) was 0.94 (0.64, 1.39) for rivaroxaban versus warfarin; 1.17 (0.67, 2.06) for dabigatran vs. warfarin; 0.85 (0.62, 1.16) for apixaban vs. warfarin; 0.86 (0.49, 1.50) for rivaroxaban vs. dabigatran; 0.99 (0.68, 1.45) for rivaroxaban versus apixaban; and 1.70 (0.90, 3.21) for dabigatran versus apixaban. CONCLUSION: We did not find significant evidence of differential CSVV risk in pair-wise comparisons of DOACs and warfarin.

Evaluating Confounding Control in Estimations of Influenza Antiviral Effectiveness in Electronic Health Plan Data.

Observational studies of oseltamivir use and influenza complications could suffer from residual confounding. Using negative control risk periods and a negative control outcome, we examined confounding control in a health-insurance-claims-based study of oseltamivir and influenza complications (pneumonia, all-cause hospitalization, and dispensing of an antibiotic). Within the Food and Drug Administration's Sentinel System, we identified individuals aged ≥18 years who initiated oseltamivir use on the influenza diagnosis date versus those who did not, during 3 influenza seasons (2014-2017). We evaluated primary outcomes within the following 1-30 days (the primary risk period) and 61-90 days (the negative control period) and nonvertebral fractures (the negative control outcome) within days 1-30. We estimated propensity-score-matched risk ratios (RRs) per season. During the 2014-2015 influenza season, oseltamivir use was associated with a reduction in the risk of pneumonia (RR = 0.72, 95% confidence interval (CI): 0.70, 0.75) and all-cause hospitalization (RR = 0.54, 95% CI: 0.53, 0.55) in days 1-30. During days 61-90, estimates were near-null for pneumonia (RR = 1.04, 95% CI: 0.95, 1.15) and hospitalization (RR = 0.94, 95% CI: 0.91, 0.98) but slightly increased for antibiotic dispensing (RR = 1.14, 95% CI: 1.08, 1.21). The RR for fractures was near-null (RR = 1.09, 95% CI: 0.99, 1.20). Estimates for the 2016-2017 influenza season were comparable, while the 2015-2016 season had conflicting results. Our study suggests minimal residual confounding for specific outcomes, but results differed by season.

Using inpatient electronic medical records to study influenza for pandemic preparedness.

BACKGROUND: We assessed the ability to identify key data relevant to influenza and other respiratory virus surveillance in a large-scale US-based hospital electronic medical record (EMR) dataset using seasonal influenza as a use case. We describe characteristics and outcomes of hospitalized influenza cases across three seasons. METHODS: We identified patients with an influenza diagnosis between March 2017 and March 2020 in 140 US hospitals as part of the US FDA's Sentinel System. We calculated descriptive statistics on the presence of high-risk conditions, influenza antiviral administrations, and severity endpoints. RESULTS: Among 5.1 million hospitalizations, we identified 29,520 hospitalizations with an influenza diagnosis; 64% were treated with an influenza antiviral within 2 days of admission, and 25% were treated >2 days after admission. Patients treated >2 days after admission had more comorbidities than patients treated within 2 days of admission. Patients never treated during hospitalization had more documentation of cardiovascular and other diseases than treated patients. We observed more severe endpoints in patients never treated (death = 3%, mechanical ventilation [MV] = 9%, intensive care unit [ICU] = 26%) or patients treated >2 days after admission (death = 2%, MV = 14%, ICU = 32%) than in patients treated earlier (treated on admission: death = 1%, MV = 5%, ICU = 23%, treated within 2 days of admission: death = 1%, MV = 7%, ICU = 27%). CONCLUSIONS: We identified important trends in influenza severity related to treatment timing in a large inpatient dataset, laying the groundwork for the use of this and other inpatient EMR data for influenza and other respiratory virus surveillance.

Who gets treated for influenza: A surveillance study from the US Food and Drug Administration's Sentinel System.

OBJECTIVE: We describe the baseline characteristics and complications of individuals with influenza in the US FDA's Sentinel System by antiviral treatment timing. DESIGN: Retrospective cohort design. PATIENTS: Individuals aged ≥6 months with outpatient diagnoses of influenza in June 2014-July 2017, 3 influenza seasons. METHODS: We identified the comorbidities, vaccination history, influenza testing, and outpatient antiviral dispensings of individuals with influenza using administrative claims data from 13 data partners including the Centers for Medicare and Medicaid Services, integrated delivery systems, and commercial health plans. We assessed complications within 30 days: hospitalization, oxygen use, mechanical ventilation, critical care, ECMO, and death. RESULTS: There were 1,090,333 influenza diagnoses in 2014-2015; 1,005,240 in 2016-2017; and 578,548 in 2017-2018. Between 49% and 55% of patients were dispensed outpatient treatment within 5 days. In all periods >80% of treated individuals received treatment on the day of diagnosis. Those treated on days 1-5 after diagnosis had higher prevalences of diabetes, chronic obstructive pulmonary disease, asthma, and obesity compared to those treated on the day of diagnosis or not treated at all. They also had higher rates of hospitalization, oxygen use, and critical care. In 2014-2015, among those aged ≥65 years, the rates of hospitalization were 45 per 1,000 diagnoses among those treated on day 0; 74 per 1,000 among those treated on days 1-5; and 50 per 1,000 among those who were untreated. CONCLUSIONS: In a large, national analysis, approximately half of people diagnosed with influenza in the outpatient setting were treated with antiviral medications. Delays in outpatient dispensed treatment were associated with higher prevalence of comorbidities and higher rates of complication.

Utilization of hydroxyprogesterone caproate among pregnancies with live birth deliveries in the sentinel distributed database.

BACKGROUND: The U.S. Food and Drug Administration (FDA) approved Makena® (hydroxyprogesterone caproate [HPC] injection) in February 2011 for reducing the risk of preterm birth (PTB) in women with a singleton pregnancy who had a history of singleton spontaneous PTB (sPTB). Makena was approved under accelerated approval and required a postmarketing study to verify its clinical benefits. However, the postmarketing trial (PROLONG) failed to verify Makena's clinical benefit to neonates and substantiate its effect on reducing the risk of recurrent PTB. This study examined the utilization of HPC, along with another progestogen (vaginal progesterone) used to reduce the risk of sPTB during pregnancy, to inform the landscape of HPC use in the United States. METHODS: We included pregnant women aged 10-54 years with a live birth delivery from 1 January, 2008 to 31 December, 2018 in the Sentinel Distributed Database (SDD). We examined the prevalence of injectable HPC (Makena and its generics), compounded HPC, and vaginal progesterone use during the second and third trimesters during the study period. We also assessed the proportion of these HPC-exposed pregnancies with obstetrical conditions of interest as potential reasons for use: (1) history of preterm delivery; (2) cervical shortening in the current pregnancy; and (3) preterm labor in the current pregnancy. RESULTS: We identified a total of 3,445,739 live-birth pregnancies (among 2.9 million women) between 2008 and 2018 in the SDD. Of these pregnancies, 6.5 per 1,000 pregnancies used injectable HPC, 2.3 per 1,000 pregnancies used compounded HPC, and 1.5 per 1,000 pregnancies used vaginal progesterone during the second and/or third trimesters. The yearly uptakeof pregnancies with injectable HPC use increased during the study period from 2.1 per 1,000 pregnancies in 2012 to 12.6 per 1,000 pregnancies in 2018; use of compounded HPC decreased from 3.3 per 1,000 pregnancies to 0.25 per 1,000 pregnancies over the same period. Of 16,524 pregnancies with injectable HPC use, 12,054 (73%) had at least one related obstetrical condition, including 6,439 (39%) with a recorded history of preterm delivery. In addition, 4,665 (28%) had a PTB recorded as the outcome for the current pregnancy. CONCLUSIONS: We found modest use of HPC during the second and/or third trimesters among all live-birth pregnancies in SDD. The majority of pregnancies with injectable HPC use had at least one of three obstetrical indications of interest recorded before or during the pregnancy.

Real-world Use of and Spending on New Oral Targeted Cancer Drugs in the US, 2011-2018.

Importance: Launch prices of new cancer drugs in the US have substantially increased in recent years despite growing concerns about the quantity and quality of evidence supporting their approval by the US Food and Drug Administration (FDA). Objective: To assess the use of and spending on new oral targeted cancer drugs among US residents with employer-sponsored insurance between 2011 and 2018, stratified by the strength of available evidence of benefit. Design, Setting, and Participants: In this cross-sectional study, dispensing claims for oral targeted cancer drugs first approved by the FDA between January 1, 2011, and December 31, 2018, were analyzed. The number of patients with drugs dispensed and the total payment for all claims were aggregated by calendar year, and these outcomes were arrayed according to evidence underlying FDA approvals, including pivotal study design (availability of randomized clinical trials) and overall survival (OS) benefit, as documented in drug labels. This study was conducted from July 17, 2019, to July 23, 2021. Main Outcomes and Measures: Annual and cumulative numbers of patients who had dispensing events, and annual and cumulative sums of payment for eligible drugs. Results: Of 37 348 patients who had at least 1 of the 44 new oral targeted drugs dispensed between 2011 and 2018, 21 324 were men (57.1%); mean (SD) age was 64.1 (13.1) years. Most individuals (36 246 [97.0%]) received drugs for which evidence from randomized clinical trials existed; however, a growing share of patients received drugs without documented OS benefit during the study period: from 12.7% in 2011 to 58.8% in 2018. Cumulative spending on all sample drugs totaled $3.5 billion by the end of 2018, of which 96.8% was spent on drugs that were approved based on a pivotal randomized clinical trial. Cumulative spending on drugs without documented OS benefit ($1.8 billion [51.6%]) surpassed that on drugs with documented OS benefit ($1.7 billion [48.4%]) by the end of 2018. Conclusions and Relevance: The findings of this cross-sectional study suggest that drugs used for treatment of cancer without documented OS benefits are adopted in the health system and account for substantial spending.

Risk of Nonmelanoma Skin Cancer in Association With Use of Hydrochlorothiazide-Containing Products in the United States.

Background: European studies reported an increased risk of nonmelanoma skin cancer associated with hydrochlorothiazide (HCTZ)-containing products. We examined the risks of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) associated with HCTZ compared with angiotensin-converting enzyme inhibitors (ACEIs) in a US population. Methods: We conducted a retrospective cohort study in the US Food and Drug Administration's Sentinel System. From the date of HCTZ or ACEI dispensing, patients were followed until a SCC or BCC diagnosis requiring excision or topical chemotherapy treatment on or within 30 days after the diagnosis date or a censoring event. Using Cox proportional hazards regression models, we estimated the hazard ratios (HRs), overall and separately by age, sex, and race. We also examined site- and age-adjusted incidence rate ratios (IRRs) by cumulative HCTZ dose within the matched cohort. Results: Among 5.2 million propensity-score matched HCTZ and ACEI users, the incidence rate (per 1000 person-years) of BCC was 2.78 and 2.82, respectively, and 1.66 and 1.60 for SCC. Overall, there was no difference in risk between HCTZ and ACEIs for BCC (HR = 0.99, 95% confidence interval [CI] = 0.97 to 1.00), but there was an increased risk for SCC (HR = 1.04, 95% CI = 1.02 to 1.06). HCTZ use was associated with higher risks of BCC (HR = 1.09, 95% CI = 1.07 to 1.11) and SCC (HR = 1.15, 95% CI = 1.12 to 1.17) among Caucasians. Cumulative HCTZ dose of 50 000 mg or more was associated with an increased risk of SCC in the overall population (IRR = 1.19, 95% CI = 1.05 to 1.35) and among Caucasians (IRR = 1.27, 95% CI = 1.10 to 1.47). Conclusions: Among Caucasians, we identified small increased risks of BCC and SCC with HCTZ compared with ACEI. Appropriate risk mitigation strategies should be taken while using HCTZ.

Medical chart validation of inpatient diagnosis codes for transfusion-related acute lung injury 2013-2015.

INTRODUCTION: Transfusion-related acute lung injury (TRALI), an adverse event occurring during or within 6 hours of transfusion, is a leading cause of transfusion-associated fatalities reported to the US Food and Drug Administration. There is limited information on the validity of diagnosis codes for TRALI recorded in inpatient electronic medical records (EMRs). STUDY DESIGNS AND METHODS: We conducted a validation study to establish the positive predictive value (PPV) of TRALI International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes recorded within a large hospital system between 2013 and 2015. A physician with critical care expertise confirmed the TRALI diagnosis. As TRALI is likely underdiagnosed, we used the specific code (518.7), and codes for respiratory failure (518.82) in combination with transfusion reaction (999.80, 999.89, E934.7). RESULTS: Among almost four million inpatient stays, we identified 208 potential TRALI cases with ICD-9-CM codes and reviewed 195 medical records; 68 (35%) met clinical definitions for TRALI (26 [38%] definitive, 15 [22%] possible, 27 [40%] delayed). Overall, the PPV for all inpatient TRALI diagnoses was 35% (95% confidence interval (CI), 28-42). The PPV for the TRALI-specific code was 44% (95% CI, 35-54). CONCLUSION: We observed low PPVs (<50%) for TRALI ICD-9-CM diagnosis codes as validated by medical charts, which may relate to inconsistent code use, incomplete medical records, or other factors. Future studies using TRALI diagnosis codes in EMR databases may consider confirming diagnoses with medical records, assessing TRALI ICD, Tenth Revision, Clinical Modification codes, or exploring alternative ways for of accurately identifying TRALI in EMR databases. KEY POINTS: In 169 hospitals, we identified 208 potential TRALI cases, reviewed 195 charts, and confirmed 68 (35%) cases met TRALI clinical definitions. As many potential TRALI cases identified with diagnosis codes did not meet clinical definitions, medical record confirmation may be prudent.

Identification of potential drug name confusion errors in the Sentinel System.

PURPOSE: In July 2015, the US Food and Drug Administration (FDA) published a drug safety communication regarding errors in prescribing and dispensing of the antidepressant Brintellix (vortioxetine) and the antiplatelet Brilinta (ticagrelor) that arose due to proprietary drug name confusion. Brintellix is indicated for major depressive disorder; Brilinta is indicated to reduce cardiovascular death, myocardial infarction, and stroke in patients with acute coronary syndrome or history of myocardial infarction. Brintellix was renamed to Trintellix in May 2016. Using Brilinta and Brintellix as a proof-of-concept feasibility use case, we assessed whether drug name confusion errors between the pair could be identified in electronic health care data via the combination of a claims-based algorithm and limited manual claims data review. METHODS: Using data from the Sentinel System, we defined potential errors as Brintellix users without an on- or off-label indication for Brintellix, without a dispensing for a drug with the same indications as Brintellix, and with an on- or off-label indication for Brilinta between -365 and +30 days after index Brintellix dispensing; the reverse was done for Brilinta. We manually reviewed claims profiles of potential cases. RESULTS: We identified 27 (0.1%) potential errors among 21 208 Brintellix users; 16 appeared to be likely errors based on claims profile review. Fifty-one (0.3%) of the 16 779 Brilinta users were identified as potential errors, and four appeared to be likely errors. CONCLUSIONS: A claims-based algorithm combined with manual review of claims profiles could identify potential drug name confusion errors, and narrow down likely errors that warrant further investigation.

Evaluation of the US Food and Drug Administration Sentinel Analysis Tools Using a Comparator with a Different Indication: Comparing the Rates of Gastrointestinal Bleeding in Warfarin and Statin Users.

BACKGROUND: The US Food and Drug Administration's Sentinel System was established to monitor safety of regulated medical products. Sentinel investigators identified known associations between drugs and adverse events to test reusable analytic tools developed for Sentinel. This test case used a comparator with a different indication. OBJECTIVE: We tested the ability of Sentinel's reusable analytic tools to identify the known association between warfarin and gastrointestinal bleeding (GIB). Statins, expected to have no effect on GIB, were the comparator. We further explored the impact of analytic features, including matching ratio and stratifying Cox regression analyses, on matched pairs. METHODS: This evaluation included data from 14 Sentinel Data Partners. New users of warfarin and statins, aged 18 years and older, who had not received other anticoagulants or had recent GIB were matched on propensity score using 1:1 and 1:n variable ratio matching, matching statin users with warfarin users to estimate the average treatment effect in warfarin-treated patients. We compared the risk of GIB using Cox proportional hazards regression, following patients for the duration of their observed continuous treatment or until a GIB. For the 1:1 matched cohort, we conducted analyses with and without stratification on matched pair. The variable ratio matched cohort analysis was stratified on the matched set. RESULTS: We identified 141,398 new users of warfarin and 2,275,694 new users of statins. In analyses stratified on matched pair/set, the hazard ratios (HR) for GIB in warfarin users compared with statin users were 2.78 (95% confidence interval [CI] 2.36-3.28) in the 1:1 matched cohort and 3.10 (95% CI 2.76-3.49) in the variable ratio matched cohort. The HR was lower in the analysis of the 1:1 matched cohort not stratified by matched pair (2.22, 95% CI 1.97-2.49), and highest early in treatment. Follow-up for warfarin users tended to be shorter than for statin users. CONCLUSIONS: This study identified the expected GIB risk with warfarin compared with statins using an analytic tool developed for Sentinel. Our findings suggest that comparators with different indications may be useful in surveillance in select circumstances. Finally, in the presence of differential censoring, stratification by matched pair may reduce the potential for bias in Cox regression analyses.

Data Mining for Adverse Drug Events With a Propensity Score-matched Tree-based Scan Statistic.

The tree-based scan statistic is a statistical data mining tool that has been used for signal detection with a self-controlled design in vaccine safety studies. This disproportionality statistic adjusts for multiple testing in evaluation of thousands of potential adverse events. However, many drug safety questions are not well suited for self-controlled analysis. We propose a method that combines tree-based scan statistics with propensity score-matched analysis of new initiator cohorts, a robust design for investigations of drug safety. We conducted plasmode simulations to evaluate performance. In multiple realistic scenarios, tree-based scan statistics in cohorts that were propensity score matched to adjust for confounding outperformed tree-based scan statistics in unmatched cohorts. In scenarios where confounding moved point estimates away from the null, adjusted analyses recovered the prespecified type 1 error while unadjusted analyses inflated type 1 error. In scenarios where confounding moved point estimates toward the null, adjusted analyses preserved power, whereas unadjusted analyses greatly reduced power. Although complete adjustment of true confounders had the best performance, matching on a moderately mis-specified propensity score substantially improved type 1 error and power compared with no adjustment. When there was true elevation in risk of an adverse event, there were often co-occurring signals for clinically related concepts. TreeScan with propensity score matching shows promise as a method for screening and prioritization of potential adverse events. It should be followed by clinical review and safety studies specifically designed to quantify the magnitude of effect, with confounding control targeted to the outcome of interest.

Extension of Disease Risk Score-Based Confounding Adjustments for Multiple Outcomes of Interest: An Empirical Evaluation.

Use of disease risk score (DRS)-based confounding adjustment when estimating treatment effects on multiple outcomes is not well studied. We designed an empirical cohort study to compare dabigatran initiators and warfarin initiators with respect to risks of ischemic stroke and major bleeding in 12 sequential monitoring periods (90 days each), using data from the Truven Marketscan database (Truven Health Analytics, Ann Arbor, Michigan). We implemented 2 approaches to combine DRS for multiple outcomes: 1) 1:1 matching on prognostic propensity scores (PPS), created using DRS for bleeding and stroke as independent variables in a propensity score (PS) model; and 2) simultaneous 1:1 matching on DRS for bleeding and stroke using Mahalanobis distance (M-distance), and compared their performance with that of traditional PS matching. M-distance matching appeared to produce more stable results in the early marketing period than both PPS and traditional PS matching; hazard ratios from unadjusted analysis, traditional PS matching, PPS matching, and M-distance matching after 4 periods were 0.72 (95% confidence interval (CI): 0.51, 1.03), 0.61 (95% CI: 0.31, 1.09), 0.55 (95% CI: 0.33, 0.91), and 0.78 (95% CI: 0.45, 1.34), respectively, for stroke and 0.65 (95% CI: 0.53, 0.80), 0.78 (95% CI: 0.60, 1.01), 0.75 (95% CI: 0.59, 0.96), and 0.78 (95% CI: 0.64, 0.95), respectively, for bleeding. In later periods, estimates were similar for traditional PS matching and M-distance matching but suggested potential residual confounding with PPS matching. These results suggest that M-distance matching may be a valid approach for extension of DRS-based confounding adjustments for multiple outcomes of interest.