A Dynamic Prognostic Model for Identifying Vulnerable COVID-19 Patients at High Risk of Rapid Deterioration.

PURPOSE: We aimed to validate and, if performance was unsatisfactory, update the previously published prognostic model to predict clinical deterioration in patients hospitalized for COVID-19, using data following vaccine availability. METHODS: Using electronic health records of patients ≥18 years, with laboratory-confirmed COVID-19, from a large care-delivery network in Massachusetts, USA, from March 2020 to November 2021, we tested the performance of the previously developed prediction model and updated the prediction model by incorporating data after availability of COVID-19 vaccines. We randomly divided data into development (70%) and validation (30%) cohorts. We built a model predicting worsening in a published severity scale in 24 h by LASSO regression and evaluated performance by c-statistic and Brier score. RESULTS: Our study cohort consisted of 8185 patients (Development: 5730 patients [mean age: 62; 44% female] and Validation: 2455 patients [mean age: 62; 45% female]). The previously published model had suboptimal performance using data after November 2020 (N = 4973, c-statistic = 0.60. Brier score = 0.11). After retraining with the new data, the updated model included 38 predictors including 18 changing biomarkers. Patients hospitalized after Jun 1st, 2021 (when COVID-19 vaccines became widely available in Massachusetts) were younger and had fewer comorbidities than those hospitalized before. The c-statistic and Brier score were 0.77 and 0.13 in the development cohort, and 0.73 and 0.14 in the validation cohort. CONCLUSION: The characteristics of patients hospitalized for COVID-19 differed substantially over time. We developed a new dynamic model for rapid progression with satisfactory performance in the validation set.

Comparative Effectiveness and Safety of Apixaban, Rivaroxaban, and Warfarin in Patients With Cirrhosis and Atrial Fibrillation : A Nationwide Cohort Study.

BACKGROUND: Apixaban, rivaroxaban, and warfarin have shown benefit for preventing major ischemic events, albeit with increased bleeding risk, among patients in the general population with atrial fibrillation (AF). However, data are scarce in patients with cirrhosis and AF. OBJECTIVE: To compare the effectiveness and safety of apixaban versus rivaroxaban and versus warfarin in patients with cirrhosis and AF. DESIGN: Population-based cohort study. SETTING: Two U.S. claims data sets (Medicare and Optum's de-identified Clinformatics Data Mart Database [2013 to 2022]). PARTICIPANTS: 1:1 propensity score (PS)-matched patients with cirrhosis and nonvalvular AF initiating use of apixaban, rivaroxaban, or warfarin. MEASUREMENTS: Primary outcomes included ischemic stroke or systemic embolism and major hemorrhage (intracranial hemorrhage or major gastrointestinal bleeding). Database-specific and pooled PS-matched rate differences (RDs) per 1000 person-years (PY) and Cox proportional hazard ratios (HRs) with 95% CIs were estimated, controlling for 104 preexposure covariates. RESULTS: Rivaroxaban initiators had significantly higher rates of major hemorrhagic events than apixaban initiators (RD, 33.1 per 1000 PY [95% CI, 12.9 to 53.2 per 1000 PY]; HR, 1.47 [CI, 1.11 to 1.94]) but no significant differences in rates of ischemic events or death. Consistently higher rates of major hemorrhage were found with rivaroxaban across subgroup and sensitivity analyses. Warfarin initiators also had significantly higher rates of major hemorrhage than apixaban initiators (RD, 26.1 per 1000 PY [CI, 6.8 to 45.3 per 1000 PY]; HR, 1.38 [CI, 1.03 to 1.84]), particularly hemorrhagic stroke (RD, 9.7 per 1000 PY [CI, 2.2 to 17.2 per 1000 PY]; HR, 2.85 [CI, 1.24 to 6.59]). LIMITATION: Nonrandomized treatment selection. CONCLUSION: Among patients with cirrhosis and nonvalvular AF, initiators of rivaroxaban versus apixaban had significantly higher rates of major hemorrhage and similar rates of ischemic events and death. Initiation of warfarin versus apixaban also contributed to significantly higher rates of major hemorrhagic events, including hemorrhagic stroke. PRIMARY FUNDING SOURCE: National Institutes of Health.

Crosswalk Algorithms for Cognitive and Functional Outcomes Among 2013-2018 Medicare Beneficiaries With Dementia.

OBJECTIVE: Before 2019, the Minimum Data Set (MDS) and Outcome and Assessment Information Set (OASIS) had incongruent response categories for rating cognitive impairment and activities of daily living (ADLs), hindering direct comparisons between nursing facilities and home health. We devised rule-based algorithms to compare cognitive impairment and ADL limitations between these 2 care settings among people with Alzheimer's disease and Alzheimer's disease-related dementias (ADRD). DESIGN: A retrospective cohort study. SETTING AND PARTICIPANTS: Included fee-for-service Medicare beneficiaries (2013-2018) transitioning from nursing facilities to home health, with 1-year of continuous enrollment, aged ≥65 years, diagnosed ADRD, and with complete MDS discharge and OASIS admission assessments (N = 398,496). METHODS: We identified target phenotypes using the Cognitive Function Scale (CFS) and ADL items from the MDS discharge assessment as reference standards. We compared 6 OASIS-based algorithms for cognitive impairment and 1 for each ADL limitation by estimating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: The average age was 83.5 (SD = 7.5) years and 82.3% transitioned from nursing to home health within 3 days. In the MDS discharge assessment, 42.2% had moderate-to-severe cognitive impairment. ADL limitations ranged from 71.4% for feeding to 97.8% for bathing. Compared with the moderate-to-severe cognitive impairment (CFS ≥3) on the MDS, the OASIS cognitive assessment indicating "considerable assistance to total dependence in routine situations" had 24% sensitivity, 94% specificity, 75% PPV, and 63% NPV. The ADL limitation algorithms exhibited high sensitivities (>96%) and PPVs (>94%) except for feeding (Sensitivity: 82%; PPV: 74%). Despite the short time frame between the 2 assessments, the OASIS admission assessment showed a higher prevalence of ADL limitations than the MDS discharge assessment. CONCLUSIONS AND IMPLICATIONS: We highlighted differences in patient function between post-acute care settings. Our algorithms can help researchers, clinicians, and policymakers standardize patient-centered outcomes for comparative effectiveness research or quality initiatives.

Frailty and Clinical Outcomes of Ticagrelor Versus Clopidogrel in Older Adults With Acute Myocardial Infarction.

BACKGROUND: Ticagrelor is recommended over clopidogrel in acute coronary syndrome based on the results of the PLATO (Study of Platelet Inhibition and Patient Outcomes) trial. We aimed to emulate PLATO in older adults with and without frailty and with acute coronary syndrome treated with percutaneous coronary intervention. METHODS AND RESULTS: We created a new-user cohort of Medicare fee-for-service beneficiaries aged ≥65 years hospitalized for acute coronary syndrome from 2014 to 2018 and initiated ticagrelor or clopidogrel following percutaneous coronary intervention. Frailty was defined using a validated claims-based frailty index ≥0.25. Coprimary outcomes were major adverse cardiovascular events and major bleeding. Follow-up began on the date of first outpatient prescription for ticagrelor or clopidogrel and ended on the earliest date for an outcome event, death, discontinuation of the index drug, or disenrollment from Medicare. The study included 42 843 older adults; 23% were frail. After propensity score matching, the rates of major adverse cardiovascular events per 100 person-years comparing ticagrelor versus clopidogrel groups were 7.8 and 7.3 in the frail cohort (hazard ratio [HR], 1.07 [95% CI, 0.84-1.36]) and 3.7 and 4.2 in the nonfrail cohort (HR, 0.87 [95% CI, 0.75-1.02]). The corresponding rates of major bleeding were 4.3 and 3.8 in the frail cohort (HR, 1.12 95% CI, [0.80-1.56]) and 2.2 and 1.8 in the nonfrail cohort (HR, 1.22 [95% CI, 0.98-1.51]). CONCLUSIONS: There was a trend toward a modest reduction in risk of major adverse cardiovascular events and a trend toward a modest increase in risk of major bleeding with ticagrelor compared with clopidogrel in the nonfrail cohort. There was insufficient evidence for the benefit of ticagrelor in frail older adults.

Assessing the Benefits and Harms of Pharmacotherapy in Older Adults with Frailty: Insights from Pharmacoepidemiologic Studies of Routine Health Care Data.

The objective of this review is to summarize and appraise the research methodology, emerging findings, and future directions in pharmacoepidemiologic studies assessing the benefits and harms of pharmacotherapies in older adults with different levels of frailty. Older adults living with frailty are at elevated risk for poor health outcomes and adverse effects from pharmacotherapy. However, current evidence is limited due to the under-enrollment of frail older adults and the lack of validated frailty assessments in clinical trials. Recent advancements in measuring frailty in administrative claims and electronic health records (database-derived frailty scores) have enabled researchers to identify patients with frailty and to evaluate the heterogeneity of treatment effects by patients' frailty levels using routine health care data. When selecting a database-derived frailty score, researchers must consider the type of data (e.g., different coding systems), the length of the predictor assessment period, the extent of validation against clinically validated frailty measures, and the possibility of surveillance bias arising from unequal access to care. We reviewed 13 pharmacoepidemiologic studies published on PubMed from 2013 to 2023 that evaluated the benefits and harms of cardiovascular medications, diabetes medications, anti-neoplastic agents, antipsychotic medications, and vaccines by frailty levels. These studies suggest that, while greater frailty is positively associated with adverse treatment outcomes, older adults with frailty can still benefit from pharmacotherapy. Therefore, we recommend routine frailty subgroup analyses in pharmacoepidemiologic studies. Despite data and design limitations, the findings from such studies may be informative to tailor pharmacotherapy for older adults across the frailty spectrum.

Emulation of randomized trials of direct oral anticoagulants with claims data and implications for new Factor XI inhibitors.

Direct oral anticoagulants (DOACs) revolutionized the management of thromboembolic disorders. Clinical care may be further improved as Factor XIs undergo large-scale outcome trials. What role can non-randomized database studies play in expediting understanding of these drugs in clinical practice? The RCT-DUPLICATIVE Initiative emulated the design of eight DOAC randomized clinical trials (RCT) using non-randomized claims database studies. RCT study design parameters and measurements were closely emulated by the database studies and produced highly concordant results. The results of the single database study that did not meet all agreement metrics with the specific RCT it was emulating were aligned with a meta-analysis of six trials studying similar questions, suggesting the trial result was an outlier. Well-designed database studies using fit-for-purpose data came to the same conclusions as DOAC trials, illustrating how database studies could complement RCTs for Factor XI inhibitors-by accelerating insights in underrepresented populations, demonstrating effectiveness and safety in clinical practice, and testing broader indications.

Validation of alopecia coding in US claims data among women of childbearing age.

BACKGROUND: Accurately identifying alopecia in claims data is important to study this rare medication side effect. OBJECTIVES: To develop and validate a claims-based algorithm to identify alopecia in women of childbearing age. METHODS: We linked electronic health records from a large healthcare system in Massachusetts (Mass General Brigham) with Medicaid claims data from 2016 through 2018 to identify all women aged 18 to 50 years with an ICD-10 code for alopecia, including alopecia areata, androgenic alopecia, non-scarring alopecia, or cicatricial alopecia, from a visit to the MGB system. Using eight predefined algorithms to identify alopecia in Medicaid claims data, we randomly selected 300 women for whom we reviewed their charts to validate the alopecia diagnosis. Positive predictive values (PPVs) were computed for the primary algorithm and seven algorithm variations, stratified by race. RESULTS: Out of 300 patients with at least 1 ICD-10 code for alopecia in the Medicaid claims, 286 had chart-confirmed alopecia (PPV = 95.3%). The algorithm requiring two diagnosis codes plus one prescription claim for alopecia treatment identified 55 patients (PPV = 100%). The algorithm requiring 1 diagnosis code for alopecia plus 1 procedure claim for intralesional triamcinolone injection identified 35 patients (PPV = 100%). Across all 8 algorithms tested, the PPV varied between 95.3% and 100%. The PPV for alopecia ranged from 94% to 100% in White and 96%-100% in 48 non-White women. The exact date of alopecia onset was difficult to determine in charts. CONCLUSION: At least one recorded ICD-10 code for alopecia in claims data identified alopecia in women of childbearing age with high accuracy.

Development and Validation of an Intracranial Hemorrhage Risk Score in Older Adults with Atrial Fibrillation Treated with Oral Anticoagulant.

Background: High risk of intracranial hemorrhage (ICH) is a leading reason for withholding anticoagulation in patients with atrial fibrillation (AF). We aimed to develop a claims-based ICH risk prediction model in older adults with AF initiating oral anticoagulation (OAC). Methods: We used US Medicare claims data to identify new users of OAC aged ≥65 years with AF in 2010-2017. We used regularized Cox regression to select predictors of ICH. We compared our AF ICH risk score with the HAS-BLED bleed risk and Homer fall risk scores by area under the receiver operating characteristic curve (AUC) and assessed net reclassification improvement (NRI) when predicting 1-year risk of ICH. Results: Our study cohort comprised 840,020 patients (mean [SD] age 77.5 [7.4] years and female 52.2%) split geographically into training (3963 ICH events [0.6%] in 629,804 patients) and validation (1397 ICH events [0.7%] in 210,216 patients) sets. Our AF ICH risk score, including 50 predictors, had superior AUCs of 0.653 and 0.650 in the training and validation sets than the HAS-BLED score of 0.580 and 0.567 (p<0.001) and the Homer score of 0.624 and 0.623 (p<0.001). In the validation set, our AF ICH risk score reclassified 57.8%, 42.5%, and 43.9% of low, intermediate, and high-risk patients, respectively, by HAS-BLED score (NRI: 15.3%, p<0.001). Similarly, it reclassified 0.0, 44.1, and 19.4% of low, intermediate, and high-risk patients, respectively, by the Homer score (NRI: 21.9%, p<0.001). Conclusion: Our novel claims-based ICH risk prediction model outperformed the standard HAS-BLED score and can inform OAC prescribing decisions.

Patient Characteristics Associated With Using Transcatheter Left Atrial Appendage Occlusion Versus Oral Anticoagulants for Atrial Fibrillation.

BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to oral anticoagulants (OACs) for stroke prevention in patients with atrial fibrillation, but the predictors of LAAO use in routine care are unclear. We aimed to assess the utilization trends of LAAO and compare the change in characteristics of LAAO users versus OACs since its marketing. METHODS: Using the US Medicare claims database (March 15, 2015, to December 31, 2020), we identified patients with atrial fibrillation, ≥65 years, and CHA2DS2-VASc score ≥2 (men) or ≥3 (women), with either first implantation of an LAAO device or initiation of OACs, including apixaban, dabigatran, rivaroxaban, edoxaban, or warfarin. Patient characteristics, measured 365 days before the first LAAO or OAC use date, were compared using logistic regression. RESULTS: There were 30 058 LAAO recipients (mean age, 77.74 years; female, 42.1%) and 792 600 OAC initiators (mean age, 78.48; female, 53.3%). In 2020, patients had higher odds of initiating LAAO use than in 2015 (0.52 versus 9.32%; adjusted odds ratio [aOR], 13.64 [95% CI, 12.56-14.81]). Old age (ie, >85 versus 65-75 years; aOR, 0.84 [95% CI, 0.80-0.88]), female sex (aOR, 0.74 [95% CI, 0.71-0.76]), Black race (aOR, 0.63 [95% CI, 0.58-0.68]) versus White race, and Medicaid eligibility (aOR, 0.61 [95% CI, 0.58-0.64]) were associated with lower odds of receiving LAAO. Among clinical characteristics, frailty, cancer, fractures, and venous thromboembolism were associated with lower odds of LAAO use, while history of intracranial and extracranial bleeding, coagulopathy, and falls were associated with higher odds of receiving LAAO. CONCLUSIONS: Among patients with atrial fibrillation receiving stroke-preventive therapy, LAAO use increased rapidly from 2015 to 2020 and was positively associated with the risk factors for OAC complications but negatively associated with old age, advanced frailty, and cancer. Black race and female sex were associated with a lower likelihood of receiving LAAO.

Targeted Learning with an Undersmoothed Lasso Propensity Score Model for Large-Scale Covariate Adjustment in Healthcare Database Studies.

Lasso regression is widely used for large-scale propensity score (PS) estimation in healthcare database studies. In these settings, previous work has shown that undersmoothing (overfitting) Lasso PS models can improve confounding control, but it can also cause problems of non-overlap in covariate distributions. It remains unclear how to select the degree of undersmoothing when fitting large-scale Lasso PS models to improve confounding control while avoiding issues that can result from reduced covariate overlap. Here, we used simulations to evaluate the performance of using collaborative-controlled targeted learning to data-adaptively select the degree of undersmoothing when fitting large-scale PS models within both singly and doubly robust frameworks to reduce bias in causal estimators. Simulations showed that collaborative learning can data-adaptively select the degree of undersmoothing to reduce bias in estimated treatment effects. Results further showed that when fitting undersmoothed Lasso PS-models, the use of cross-fitting was important for avoiding non-overlap in covariate distributions and reducing bias in causal estimates.

Identifying Functional Status Impairment in People Living With Dementia Through Natural Language Processing of Clinical Documents: Cross-Sectional Study.

BACKGROUND: Assessment of activities of daily living (ADLs) and instrumental ADLs (iADLs) is key to determining the severity of dementia and care needs among older adults. However, such information is often only documented in free-text clinical notes within the electronic health record and can be challenging to find. OBJECTIVE: This study aims to develop and validate machine learning models to determine the status of ADL and iADL impairments based on clinical notes. METHODS: This cross-sectional study leveraged electronic health record clinical notes from Mass General Brigham's Research Patient Data Repository linked with Medicare fee-for-service claims data from 2007 to 2017 to identify individuals aged 65 years or older with at least 1 diagnosis of dementia. Notes for encounters both 180 days before and after the first date of dementia diagnosis were randomly sampled. Models were trained and validated using note sentences filtered by expert-curated keywords (filtered cohort) and further evaluated using unfiltered sentences (unfiltered cohort). The model's performance was compared using area under the receiver operating characteristic curve and area under the precision-recall curve (AUPRC). RESULTS: The study included 10,000 key-term-filtered sentences representing 441 people (n=283, 64.2% women; mean age 82.7, SD 7.9 years) and 1000 unfiltered sentences representing 80 people (n=56, 70% women; mean age 82.8, SD 7.5 years). Area under the receiver operating characteristic curve was high for the best-performing ADL and iADL models on both cohorts (>0.97). For ADL impairment identification, the random forest model achieved the best AUPRC (0.89, 95% CI 0.86-0.91) on the filtered cohort; the support vector machine model achieved the highest AUPRC (0.82, 95% CI 0.75-0.89) for the unfiltered cohort. For iADL impairment, the Bio+Clinical bidirectional encoder representations from transformers (BERT) model had the highest AUPRC (filtered: 0.76, 95% CI 0.68-0.82; unfiltered: 0.58, 95% CI 0.001-1.0). Compared with a keyword-search approach on the unfiltered cohort, machine learning reduced false-positive rates from 4.5% to 0.2% for ADL and 1.8% to 0.1% for iADL. CONCLUSIONS: In this study, we demonstrated the ability of machine learning models to accurately identify ADL and iADL impairment based on free-text clinical notes, which could be useful in determining the severity of dementia.

Comparative Safety and Effectiveness of Warfarin or Rivaroxaban Versus Apixaban in Patients With Advanced CKD and Atrial Fibrillation: Nationwide US Cohort Study.

RATIONALE & OBJECTIVE: Head-to-head data comparing the effectiveness and safety of oral anticoagulants in patients with atrial fibrillation (AF) and advanced chronic kidney disease (CKD) are lacking. We compared the safety and effectiveness of warfarin or rivaroxaban versus apixaban in patients with AF and non-dialysis-dependent CKD stage 4/5. STUDY DESIGN: Propensity score-matched cohort study. SETTING & PARTICIPANTS: 2 nationwide US claims databases, Medicare and Optum's deidentified Clinformatics Data Mart Database, were searched for the interval from January 1, 2013, through March 31, 2022, for patients with nonvalvular AF and CKD stage 4/5 who initiated warfarin versus apixaban (matched cohort, n=12,488) and rivaroxaban versus apixaban (matched cohort, n = 5,720). EXPOSURES: Warfarin, rivaroxaban, or apixaban. OUTCOMES: Primary outcomes included major bleeding and ischemic stroke. Secondary outcomes included all-cause mortality, major gastrointestinal bleeding, and intracranial bleeding. ANALYTICAL APPROACH: Cox regression was used to estimate HRs, and 1:1 propensity-score matching was used to adjust for 80 potential confounders. RESULTS: Compared with apixaban, warfarin initiation was associated with a higher rate of major bleeding (HR, 1.85; 95% CI, 1.59-2.15), including major gastrointestinal bleeding (1.86; 1.53-2.25) and intracranial bleeding (2.15; 1.42-3.25). Compared with apixaban, rivaroxaban was also associated with a higher rate of major bleeding (1.69; 1.33-2.15). All-cause mortality was similar for warfarin (1.08; 0.98-1.18) and rivaroxaban (0.94; 0.81-1.10) versus apixaban. Furthermore, no statistically significant differences for ischemic stroke were observed for warfarin (1.14; 0.83-1.57) or rivaroxaban (0.71; 0.40-1.24) versus apixaban, but the CIs were wide. Similar results were observed for warfarin versus apixaban in the positive control cohort of patients with CKD stage 3, consistent with randomized trial findings. LIMITATIONS: Few ischemic stroke events, potential residual confounding. CONCLUSIONS: In patients with AF and advanced CKD, rivaroxaban and warfarin were associated with higher rates of major bleeding compared with apixaban, suggesting a superior safety profile for apixaban in this high-risk population. PLAIN-LANGUAGE SUMMARY: Different anticoagulants have been shown to reduce the risk of stroke in patients with atrial fibrillation, such as warfarin and direct oral anticoagulants like apixaban and rivaroxaban. Unfortunately, the large-scale randomized trials that compared direct anticoagulants versus warfarin excluded patients with advanced chronic kidney disease. Therefore, the comparative safety and effectiveness of warfarin, apixaban, and rivaroxaban are uncertain in this population. In this study, we used administrative claims data from the United States to answer this question. We found that warfarin and rivaroxaban were associated with increased risks of major bleeding compared with apixaban. There were few stroke events, with no major differences among the 3 drugs in the risk of stroke. In conclusion, this study suggests that apixaban has a better safety profile than warfarin and rivaroxaban.

Development and Validation of a Claims-Based Model to Predict Categories of Obesity.

We developed and validated a claims-based algorithm that classifies patients into obesity categories. Using Medicare (2007-2017) and Medicaid (2000-2014) claims data linked to 2 electronic health record (EHR) systems in Boston, Massachusetts, we identified a cohort of patients with an EHR-based body mass index (BMI) measurement (calculated as weight (kg)/height (m)2). We used regularized regression to select from 137 variables and built generalized linear models to classify patients with BMIs of ≥25, ≥30, and ≥40. We developed the prediction model using EHR system 1 (training set) and validated it in EHR system 2 (validation set). The cohort contained 123,432 patients in the Medicare population and 40,736 patients in the Medicaid population. The model comprised 97 variables in the Medicare set and 95 in the Medicaid set, including BMI-related diagnosis codes, cardiovascular and antidiabetic drugs, and obesity-related comorbidities. The areas under the receiver-operating-characteristic curve in the validation set were 0.72, 0.75, and 0.83 (Medicare) and 0.66, 0.66, and 0.70 (Medicaid) for BMIs of ≥25, ≥30, and ≥40, respectively. The positive predictive values were 81.5%, 80.6%, and 64.7% (Medicare) and 81.6%, 77.5%, and 62.5% (Medicaid), for BMIs of ≥25, ≥30, and ≥40, respectively. The proposed model can identify obesity categories in claims databases when BMI measurements are missing and can be used for confounding adjustment, defining subgroups, or probabilistic bias analysis.

A population-based cohort defined risk of hyperkalemia after initiating SGLT-2 inhibitors, GLP1 receptor agonists or DPP-4 inhibitors to patients with chronic kidney disease and type 2 diabetes.

Hyperkalemia is a common adverse event in patients with chronic kidney disease (CKD) and type 2 diabetes and limits the use of guideline-recommended therapies such as renin-angiotensin system inhibitors. Here, we evaluated the comparative effects of sodium-glucose cotransporter-2 inhibitors (SGLT-2i), glucagon-like peptide-1 receptor agonists (GLP-1RA) and dipeptidyl peptidase-4 inhibitors (DPP-4i) on the risk of hyperkalemia. We conducted a population-based active-comparator, new-user cohort study using claims data from Medicare and two large United States commercial insurance databases (April 2013-April 2022). People with CKD stages 3-4 and type 2 diabetes who newly initiated SGLT-2i vs. DPP-4i (141671 patients), GLP-1RA vs. DPP-4i (159545 patients) and SGLT-2i vs. GLP-1RA (93033 patients) were included. The primary outcome was hyperkalemia diagnosed in inpatient or outpatient settings. Secondary outcomes included hyperkalemia diagnosed in inpatient or emergency department setting, and serum potassium levels of 5.5 mmol/L or more. Pooled hazard ratios and rate differences were estimated after propensity score matching to adjust for over 140 potential confounders. Initiation of SGLT-2i was associated with a lower risk of hyperkalemia compared with DPP-4i (hazard ratio 0.74; 95% confidence interval 0.68-0.80) and contrasted to GLP-1RA (0.92; 0.86-0.99). Compared with DPP-4i, GLP-1RA were also associated with a lower risk of hyperkalemia (0.80; 0.75-0.86). Corresponding absolute rate differences/1000 person-years were -24.8 (95% confidence interval -31.8 to -17.7), -5.0 (-10.9 to 0.8), and -17.7 (-23.4 to -12.1), respectively. Similar findings were observed for the secondary outcomes, among subgroups, and across single agents within the SGLT-2i and GLP-1RA classes. Thus, SGLT-2i and GLP-1RA are associated with a lower risk of hyperkalemia than DPP-4i in patients with CKD and type 2 diabetes, further supporting the use of these drugs in this population.

Frailty, Home Time, and Health Care Costs in Older Adults With Atrial Fibrillation Receiving Oral Anticoagulants.

Importance: There are no data on patient-centered outcomes and health care costs by frailty in patients with atrial fibrillation (AF) taking oral anticoagulants (OACs). Objective: To compare home time, clinical events, and health care costs associated with OACs by frailty levels in older adults with AF. Design, Setting, and Participants: This community-based cohort study assessed Medicare fee-for-service beneficiaries 65 years or older with AF from January 1, 2013, to December 31, 2019. Data analysis was performed from January to December 2022. Exposures: Apixaban, rivaroxaban, and warfarin use were measured from prescription claims. Frailty was measured using a validated claims-based frailty index. Main outcomes and measures: Outcome measures were (1) home time (days alive out of the hospital and skilled nursing facility) loss greater than 14 days; (2) a composite end point of ischemic stroke, systemic embolism, major bleeding, or death; and (3) total cost per member per year after propensity score overlap weighting. Results: The weighted population comprised 136 551 beneficiaries, including 45 950 taking apixaban (mean [SD] age, 77.6 [7.3] years; 51.3% female), 45 320 taking rivaroxaban (mean [SD] age, 77.6 [7.3] years; 51.9% female), and 45 281 taking warfarin (mean [SD] age, 77.6 [7.3] years; 52.0% female). Compared with apixaban, rivaroxaban was associated with increased risk of home time lost greater than 14 days (risk difference per 100 persons, 1.8 [95% CI, 1.5-2.1]), composite end point (rate difference per 1000 person-years, 21.3 [95% CI, 16.4-26.2]), and total cost (mean difference, $890 [95% CI, $652-$1127]), with greater differences among the beneficiaries with frailty. Use of warfarin relative to apixaban was associated with increased home time lost (risk difference per 100 persons, 3.2 [95% CI, 2.9-3.5]) and composite end point (rate difference per 1000 person-years, 29.4 [95% CI, 24.5-34.3]), with greater differences among the beneficiaries with frailty. Compared with apixaban, warfarin was associated with lower total cost (mean difference, -$1166 [95% CI, -$1396 to -$937]) but higher cost when excluding OAC cost (mean difference, $1409 [95% CI, $1177 to $1642]) regardless of frailty levels. Conclusions and Relevance: In older adults with AF, apixaban was associated with increased home time and lower rates of clinical events than rivaroxaban and warfarin, especially for those with frailty. Apixaban was associated with lower total cost compared with rivaroxaban but higher cost compared with warfarin due to higher OAC cost. These findings suggest that apixaban may be preferred for older adults with AF, particularly those with frailty.

Utilization of P2Y12 Inhibitors in Older Adults With ST-Elevation Myocardial Infarction and Frailty.

Choosing optimal P2Y12 inhibitor in frail older adults is challenging because they are at increased risk of both ischemic and bleeding events. We conducted a retrospective cohort study of Medicare Advantage Plan beneficiaries who were prescribed clopidogrel, prasugrel, or ticagrelor after percutaneous coronary intervention-treated ST-elevation myocardial infarction from January 1, 2010 to December 31, 2020. Frailty was defined using claims-based frailty index ≥0.25. We conducted multivariable logistic regression to identify factors associated with using potent P2Y12 inhibitors and multivariable-adjusted competing risk analyses to compare the rate of discontinuation of potent P2Y12 inhibitors in frail versus non-frail patients. There were 11,239 patients (mean age 74 years, 39% women). The prevalence of cardiovascular and geriatric co-morbidities was as follows: 32% chronic kidney disease, 28% heart failure, 10% previous myocardial infarction, 6% dementia, 20% anemia, and 12% frailty. The proportion of patients receiving clopidogrel decreased from 78.3% in 2010 to 2013 to 42.1% in 2018 to 2020, with a concurrent increase in those receiving potent P2Y12 inhibitors (mostly ticagrelor) from 21.7% to 57.9%. Frailty was independently associated with reduced odds of initiation (odds ratio 0.78, 95% confidence interval 0.67 to 0.90) but not with discontinuation of potent P2Y12 inhibitors (subdistribution hazard ratio 1.09, 95% confidence interval 0.98 to 1.22). In conclusion, frail older adults are less likely to receive potent P2Y12 inhibitors after percutaneous coronary intervention-treated ST-elevation myocardial infarction, but they are as likely as non-frail patients to continue with the prescribed P2Y12 inhibitor.

Comparison of EHR Data-Completeness in Patients with Different Types of Medical Insurance Coverage in the United States.

Prior studies have demonstrated that misclassification of study variables due to electronic health record (EHR)-discontinuity can be mitigated by restricting EHR-based analyses to subjects with high predicted EHR-continuity based on a simple algorithm. In this study, we compared EHR continuity in populations covered by Medicare, Medicaid, or commercial insurance. Using claims-linked EHRs from a multicenter network in Massachusetts, including Medicare (MA EHR-Medicare cohort) and Medicaid (MA EHR-Medicaid cohort) claims data; and TriNetX (TriNetX cohort) claims-linked EHR data from 11 US-based healthcare organizations, we assessed (1) EHR-continuity quantified by proportion of encounters captured by EHR (capture proportion (CP)); (2) area under receiver operating curve (AUROC) of previously validated model to identify patients with high EHR-continuity (CP ≥ 0.6); (3) misclassification of 40 patient characteristics, quantified by average standardized absolute mean difference (ASAMD). Study participants were ≥ 65 years (Medicare) or ≥ 18 years (Medicaid, TriNetX) with ≥ 365 days of continuous insurance enrollment overlapping with an EHR encounter. We found that the mean CP was 0.30, 0.18, and 0.19 and AUROC of the prediction model to identify patients with high EHR-continuity was 0.92, 0.89, and 0.77 in the MA EHR-Medicare, MA EHR-Medicaid, and TriNetX cohorts, respectively. Restricting to patients with predicted EHR-continuity percentile of top 20%, 50%, and 50% in MA EHR-Medicare, MA EHR-Medicaid, and TriNetX cohorts resulted in acceptable levels of misclassification (ASAMD < 0.1). Using a prediction model to identify cohorts with high EHR-continuity can improve validity, but cutoffs to achieve this goal vary by population.

The impact of electronic health record discontinuity on prediction modeling.

BACKGROUND: To determine the impact of electronic health record (EHR)-discontinuity on the performance of prediction models. METHODS: The study population consisted of patients with a history of cardiovascular (CV) comorbidities identified using US Medicare claims data from 2007 to 2017, linked to EHR from two networks (used as model training and validation set, respectively). We built models predicting one-year risk of mortality, major CV events, and major bleeding events, stratified by high vs. low algorithm-predicted EHR-continuity. The best-performing models for each outcome were chosen among 5 commonly used machine-learning models. We compared model performance by Area under the ROC curve (AUROC) and Area under the precision-recall curve (AUPRC). RESULTS: Based on 180,950 in the training and 103,061 in the validation set, we found EHR captured only 21.0-28.1% of all the non-fatal outcomes in the low EHR-continuity cohort but 55.4-66.1% of that in the high EHR-continuity cohort. In the validation set, the best-performing model developed among high EHR-continuity patients had consistently higher AUROC than that based on low-continuity patients: AUROC was 0.849 vs. 0.743 when predicting mortality; AUROC was 0.802 vs. 0.659 predicting the CV events; AUROC was 0.635 vs. 0.567 predicting major bleeding. We observed a similar pattern when using AUPRC as the outcome metric. CONCLUSIONS: Among patients with CV comorbidities, when predicting mortality, major CV events, and bleeding outcomes, the prediction models developed in datasets with low EHR-continuity consistently had worse performance compared to models developed with high EHR-continuity.

Claims-Based Frailty Index as a Measure of Dementia Severity in Medicare Claims Data.

BACKGROUND: Dementia severity is unavailable in administrative claims data. We examined whether a claims-based frailty index (CFI) can measure dementia severity in Medicare claims. METHODS: This cross-sectional study included the National Health and Aging Trends Study Round 5 participants with possible or probable dementia whose Medicare claims were available. We estimated the Functional Assessment Staging Test (FAST) scale (range: 3 [mild cognitive impairment] to 7 [severe dementia]) using information from the survey. We calculated CFI (range: 0-1, higher scores indicating greater frailty) using Medicare claims 12 months prior to the participants' interview date. We examined C-statistics to evaluate the ability of the CFI in identifying moderate-to-severe dementia (FAST stage 5-7) and determined the optimal CFI cut-point that maximized both sensitivity and specificity. RESULTS: Of the 814 participants with possible or probable dementia and measurable CFI, 686 (72.2%) patients were ≥75 years old, 448 (50.8%) were female, and 244 (25.9%) had FAST stage 5-7. The C-statistic of CFI to identify FAST stage 5-7 was 0.78 (95% confidence interval: 0.72-0.83), with a CFI cut-point of 0.280, achieving the maximum sensitivity of 76.9% and specificity of 62.8%. Participants with CFI ≥0.280 had a higher prevalence of disability (19.4% vs 58.3%) and dementia medication use (6.0% vs 22.8%) and higher risk of mortality (10.7% vs 26.3%) and nursing home admission (4.5% vs 10.6%) over 2 years than those with CFI <0.280. CONCLUSIONS: Our study suggests that CFI can be useful in identifying moderate-to-severe dementia from administrative claims among older adults with dementia.

Common non-cardiovascular multimorbidity groupings and clinical outcomes in older adults with major cardiovascular disease.

BACKGROUND: Among older adults, non-cardiovascular multimorbidity often coexists with cardiovascular disease (CVD) but their clinical significance is uncertain. We identified common non-cardiovascular comorbidity patterns and their association with clinical outcomes in Medicare fee-for-service beneficiaries with acute myocardial infarction (AMI), congestive heart failure (CHF), or atrial fibrillation (AF). METHODS: Using 2015-2016 Medicare data, we took 1% random sample to create 3 cohorts of beneficiaries diagnosed with AMI (n = 24,808), CHF (n = 57,285), and AF (n = 36,277) prior to 1/1/2016. Within each cohort, we applied latent class analysis to classify beneficiaries based on 9 non-cardiovascular comorbidities (anemia, cancer, chronic kidney disease, chronic lung disease, dementia, depression, diabetes, hypothyroidism, and musculoskeletal disease). Mortality, cardiovascular and non-cardiovascular hospitalizations, and home time lost over a 1-year follow-up period were compared across non-cardiovascular multimorbidity classes. RESULTS: Similar non-cardiovascular multimorbidity classes emerged from the 3 CVD cohorts: (1) minimal, (2) depression-lung, (3) chronic kidney disease (CKD)-diabetes, and (4) multi-system class. Across CVD cohorts, multi-system class had the highest risk of mortality (hazard ratio [HR], 2.7-3.9), cardiovascular hospitalization (HR, 1.6-3.3), non-cardiovascular hospitalization (HR, 3.1-7.2), and home time lost (rate ratio, 2.7-5.4). Among those with AMI, the CKD-diabetes class was more strongly associated with all the adverse outcomes than the depression-lung class. In CHF and AF, differences in risk between the depression-lung and CKD-diabetes classes varied per outcome; and the depression-lung and multi-system classes had double the rates of non-cardiovascular hospitalizations than cardiovascular hospitalizations. CONCLUSION: Four non-cardiovascular multimorbidity patterns were found among Medicare beneficiaries with CHF, AMI, or AF. Compared to the minimal class, the multi-system, CKD-diabetes, and depression-lung classes were associated with worse outcomes. Identification of these classes offers insight into specific segments of the population that may benefit from more than the usual cardiovascular care.