Variability in short-term mortality following repair of ruptured abdominal aortic aneurysms across centers and physicians.

BACKGROUND: Variation in the care management of repairs for ruptured infrarenal abdominal aortic aneurysms between centers and physicians, such as procedural volumes, may explain differences in mortality outcomes. First, we quantified the center and physician variability associated with 30- and 90-day mortality risk after ruptured open surgical repair (rOSR) and ruptured endovascular aneurysm repair (rEVAR). Second, we explored wheter part of this variability was attributable to procedural volume at the center and physician levels. METHODS: Two cohorts including rOSR and rEVAR procedures between 2013 and 2019 were analyzed from the Vascular Quality Initiative database. Thirty- and 90-day all-cause mortality rates were derived from linked Medicare claims data. The median odds ratio (MOR) (median mortality risk from low- to high-risk cluster) and intraclass correlation coefficient (ICC) (variability attributable to each cluster) for 30- and 90-day mortality risks associated with center and physician variability were derived using patient-level adjusted multilevel logistic regression models. Procedural volume was calculated at the center and physician levels and stratified by quartiles. The models were sequentially adjusted for volumes, and the difference in ICCs (without vs with accounting for volume) was calculated to describe the center and physician variability in mortality risk attributable to volumes. RESULTS: We included 450 rOSRs (mean age, 74.5 ± 7.6 years; 23.5% female) and 752 rEVARs (76.4 ± 8.4 years; 26.1% female). After rOSRs, the 30- and 90-day mortality rates were 32.9% and 38.7%, respectively. No variability across centers and physicians was noted (30- and 90-day MORs ≈1 and ICCs ≈0%). Neither center nor physician volume was associated with 30-day (P = .477 and P = .796) or 90-day mortality (P = .098 and P = .559). After rEVAR, the 30- and 90-day mortality rates were 21.3% and 25.5%, respectively. Significant center variability (30-day MOR, 1.82 [95% confidence interval (CI), 1.33-2.22]; ICC, 11% [95% CI, 2%-36%]; and 90-day MOR, 1.76 [95% CI, 1.37-2.09]; ICC, 10% [95% CI, 3%-30%]), but negligeable variability across physicians (30- and 90-day MORs ≈1 and ICCs ≈0%) were noted. Neither center nor physician volume were associated with 30-day (P = .076 and P = .336) or 90-day mortality risk (P = .066 and P = .584). The center variability attributable to procedural volumes was negligeable (difference in ICCs, 1% for 30-day mortality; 0% for 90-day mortality). CONCLUSIONS: Variability in practice from center to center was associated with short-term mortality outcomes in rEVAR, but not for rOSR. Physician variability was not associated with short-term mortality for rOSR or rEVAR. Annualized center and physician volumes did not significantly explain these associations. Further work is needed to identify center-level factors affecting the quality of care and outcomes for ruptured abdominal aortic aneurysms.

Psychosocial and socioeconomic factors are most predictive of health status in patients with claudication.

BACKGROUND: As a key treatment goal for patients with symptomatic peripheral artery disease (PAD), improving health status has also become an important end point for clinical trials and performance-based care. An understanding of patient factors associated with 1-year PAD health status is lacking in patients with PAD. METHODS: The health status of 1073 consecutive patients with symptomatic PAD in the international multicenter PORTRAIT (Patient-Centered Outcomes Related to Treatment Practices in Peripheral Arterial Disease: Investigating Trajectories) registry was measured at baseline and 1 year with the Peripheral Artery Questionnaire (PAQ). The association of 47 patient characteristics with 1-year PAQ scores was assessed using a random forest algorithm. Variables of clinical significance were retained and included in a hierarchical multivariable linear regression model predicting 1-year PAQ summary scores. RESULTS: The mean age of patients was 67.7 ± 9.3 years, and 37% were female. Variables with the highest importance ranking in predicting 1-year PAQ summary score were baseline PAQ summary score, Patient Health Questionnaire-8 depression score, Generalized Anxiety Disorder-2 anxiety score, new onset symptom presentation, insurance status, current or prior diagnosis of depression, low social support, initial invasive treatment, duration of symptoms, and race. The addition of 19 clinical variables in an extended model marginally improved the explained variance in 1-year health status (from R2 0.312 to 0.335). CONCLUSIONS: Patients' 1-year PAD-specific health status, as measured by the PAQ, can be predicted from 10 mostly psychosocial and socioeconomic patient characteristics including depression, anxiety, insurance status, social support, and symptoms. These characteristics should be validated and tested in other PAD cohorts so that this model can inform risk adjustment and prediction of PAD health status in comparative effectiveness research and performance-based care.

Clinician perspectives regarding CYP2C19 genotype testing in patients with critical limb ischemia: A Delphi approach.

OBJECTIVES: Antiplatelet therapy is an essential element in the management of patients with arterial vascular disease. In peripheral arterial disease (PAD), dual antiplatelet therapy (DAPT), primarily clopidogrel and aspirin, is routinely prescribed following intervention. There is sparse data regarding the need for DAPT, the appropriate duration, or the heterogeneity of treatment effects for antiplatelet regimens across patients, leading to potential uncertainty and heterogeneity around treatment practices. An example of heterogeneity of treatment effects is a patients' metabolizer status for the use of clopidogrel. The aim of the study was to (1) assess clinicians' knowledge of and attitudes toward managing patients with CYP2C19 mutations, (2) identify barriers to implementation of CYP2C19 testing and management policies, and (3) reach consensus for CYP2C19 testing and management strategies for patients with PAD who undergo peripheral vascular interventions (PVI). METHODS: A modified Delphi method was used to establish consensus amongst PAD interventionalists around CYP2C19 testing. All practicing Yale New Haven Hospital PAD interventionalists with backgrounds in interventional cardiology, vascular surgery, or interventional radiology were approached by email for participation. Round 1 included the collection of baseline demographic questions, knowledge questions, and three statements for consensus. Knowledge questions were rated on a 0-10 Likert scale with the following anchors: 0 ("Not at all"), 5 ("Neutral), and 10 ("Very Much"). Participants were asked to rate the importance of the three consensus statements on a 9-point Likert scale from 1 ("Strongly Disagree") to 10 ("Strongly Agree"). In Round 2, participants were shown the same consensus statements, the median response of the group from the previous round, and their previous answers. Participants were instructed to revise their rating using the results from the previous round. This process was repeated for Round 3. RESULTS: Of the 28 experts invited to participate, 13 agreed (46%). Participants were predominantly male (92.3%) and white (61.5%) with representation from interventional cardiology (46.2%) and vascular surgery (53.8%). Most participants reported more than 10+ years in practice (61.5%). PAD interventionalists felt they would benefit from more education regarding CYP2C19 mutations (median score 8.0, interquartile range 5.0-8.5). They indicated some familiarity with CYP2C19 mutations (7.0, 6.0-9.5) but did not feel strongly that CYP2C19 was important to their practice (6.0, 5.5-7.5). In each round, the median responses for the three consensus statements were 5, 6, and 9, respectively. With each successive round the interquartile range narrowed indicative of evolving consensus but did not reach the prespecified interquartile range for consensus of 1 for any of the statements. CONCLUSIONS: PAD interventionalists practicing at an academic health system recognize the heterogenous response of their patients to clopidogrel therapy but are unsure when to leverage genetic testing to improve outcomes for their patients. Our study identified gaps regarding PAD interventionalists' knowledge, perceived barriers, and attitudes toward CYP2C19 testing in PAD. This information highlights the need for randomized data on genetic testing for clopidogrel responsiveness in peripheral vascular disease following intervention to help guide antiplatelet management.

Chronic Cough: Characterizing and Quantifying Burden in Adults Using a Nationwide Electronic Health Records Database.

Chronic cough is a common condition; until recently, no International Classification of Diseases (ICD) code for chronic cough existed; therefore, the true scope and burden of chronic cough is unclear. Using established algorithms, we examined chronic cough patients and their risk profiles, recurrent cough episodes, and subsequent 1-year health care utilization in the nationwide Cerner EHR data resource, compared with those with acute cough. An ICD-based algorithm was applied to the Cerner Health Facts EHR database to derive a phenotype of chronic cough defined as three ICD-based "cough" encounters 14-days apart over a 56-to-120-day period from 2015 to 2017. Demographics, comorbidities, and outcomes (1-year outpatient, emergency, and inpatient encounters) were collected for the chronic cough cohort and acute cough cohort. The chronic cough cohort was 61.5% female, 70.4% white, and 15.2% African American, with 13.7% being of Asian, Native American, or unknown race. Compared with the acute cough cohort, chronic cough patients were more likely to be older, female, and have chronic pulmonary disease, obesity, and depression. Predictors of recurrent chronic cough were older age and race. Those with chronic cough had more outpatient (2.48 ± 2.10 vs. 1.48 ± 0.99; SMD = 0.94), emergency (1.90 ± 2.26 vs. 1.23 ± 0.68; SMD = 0.82), and inpatient (1.11 ± 0.36 vs. 1.05 ± 0.24, SMD = 0.24) encounters compared with acute cough. While EHR-based data may provide a useful resource to identify chronic cough phenotypes, supplementary data approaches and screening methods for chronic cough can further identify the scope of the problem.