Electroanalytical Assessment of the Effect of Ni:Fe Stoichiometry and Architectural Expression on the Bifunctional Activity of Nanoscale NiyFe1-yOx.

Electrocatalysis of the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) was assessed for a series of Ni-substituted ferrites (NiyFe1-yOx, where y = 0.1 to 0.9) as expressed in porous, high-surface-area forms (ambigel and aerogel nanoarchitectures). We then correlate electrocatalytic activity with Ni:Fe stoichiometry as a function of surface area, crystallite size, and free volume. In order to ensure in-series comparisons, calcination at 350 °C/air was necessary to crystallize the respective NiyFe1-yOx nanoarchitectures, which index to the inverse spinel structure for Fe-rich materials (y ≤ 0.33), rock salt for the most Ni-rich material (y = 0.9), and biphasic for intermediate stoichiometry (0.5 ≤ y ≤ 0.67). In the intermediate Ni:Fe stoichiometric range (0.33 ≤ y ≤ 0.67), the OER current density at 390 mV increases monotonically with increasing Ni content and increasing surface area, but with different working curves for ambigels versus aerogels. At a common stoichiometry within this range, ambigels and aerogels yield comparable OER performance, but do so by expressing larger crystallite size (ambigel) versus higher surface area (aerogel). Effective OER activity can be achieved without requiring supercritical-fluid extraction as long as moderately high surface area, porous materials can be prepared. We find improved OER performance (η decreases from 390 to 373 mV) for Ni0.67Fe0.33Ox aerogel heat-treated at 300 °C/Ar, owing to an increase in crystallite size (2.7 to 4.1 nm). For the ORR, electrocatalytic activity favors Fe-rich NiyFe1-yOx materials; however, as the Ni-content increases beyond y = 0.5, a two-electron reduction pathway is still exhibited, demonstrating that bifunctional OER and ORR activity may be possible by choosing a nickel ferrite nanoarchitecture that provides high OER activity with sufficient ORR activity. Assessing the catalytic activity requires an appreciation of the multivariate interplay among Ni:Fe stoichiometry, surface area, crystallographic phase, and crystallite size.

Should Risk Adjustment for Surgical Outcomes Reporting Include Sociodemographic Status? A Study of Coronary Artery Bypass Grafting in California.

BACKGROUND: Public reporting of surgical outcomes must adjust for patient risk. However, whether patient sociodemographic status (SDS) should be included is debatable. Our objective was to empirically compare risk-adjustment models and hospital ratings with or without SDS factors for patients undergoing coronary artery bypass grafting. STUDY DESIGN: This is a retrospective analysis of the California Coronary Artery Bypass Grafting Outcomes Reporting Program, 2011-2012. Outcomes included 30-day or in-hospital mortality, perioperative stroke, and 30-day readmission. Sociodemographic status factors included race, language, insurance, ZIP code-based median income, and percent that were a college graduate. The c-statistic and goodness-of-fit were compared between models with and without SDS factors. Differences in hospital performance rating when adjusting for SDS were also compared. RESULTS: None of the SDS factors predicted mortality. Income, education, and language had no impact on any outcomes. Insurance predicted stroke (MediCal vs private insurance, odds ratio [OR] = 1.91; 95% CI, 1.11-3.31; p = 0.020) and readmissions (Medicare vs private insurance, OR = 1.36; 95% CI, 1.16-1.61; p < 0.001; MediCal vs private insurance, OR = 1.56; 95% CI, 1.26-1.94; p < 0.001). Race also predicted stroke (Asian vs white, OR = 2.26; p < 0.001). Adding SDS factors improved the c-statistic in readmission only (0.652 vs 0.645; p = 0.008). Goodness-of-fit worsened when adding SDS factors to mortality models, but was no different in stroke or readmissions. Hospital performance rating only changed in readmissions; of 124 hospitals, only 1 hospital moved from "better" to "average" when adjusting for SDS. CONCLUSIONS: Adjusting for insurance improves statistical models when analyzing readmissions after coronary artery bypass grafting, but does not impact hospital performance ratings substantially. Deciding whether SDS should be included in a patient's risk profile depends on valid measurements of SDS and requires a nuanced approach to assessing how these variables improve risk-adjusted models.

Idiopathic Pulmonary Fibrosis in United States Automated Claims. Incidence, Prevalence, and Algorithm Validation.

RATIONALE: Estimates of idiopathic pulmonary fibrosis (IPF) incidence and prevalence from electronic databases without case validation may be inaccurate. OBJECTIVES: Develop claims algorithms to identify IPF and assess their positive predictive value (PPV) to estimate incidence and prevalence in the United States. METHODS: We developed three algorithms to identify IPF cases in the HealthCore Integrated Research Database. Sensitive and specific algorithms were developed based on literature review and consultation with clinical experts. PPVs were assessed using medical records. A third algorithm used logistic regression modeling to generate an IPF score and was validated using a separate set of medical records. We estimated incidence and prevalence of IPF using the sensitive algorithm corrected for the PPV. MEASUREMENTS AND MAIN RESULTS: We identified 4,598 patients using the sensitive algorithm and 2,052 patients using the specific algorithm. After medical record review, the PPVs of these algorithms using the treating clinician's diagnosis were 44.4 and 61.7%, respectively. For the IPF score, the PPV was 76.2%. Using the clinical adjudicator's diagnosis, the PPVs were 54 and 57.6%, respectively, and for the IPF score, the PPV was 83.3%. The incidence and period prevalences of IPF, corrected for the PPV, were 14.6 per 100,000 person-years and 58.7 per 100,000 persons, respectively. CONCLUSIONS: Sensitive algorithms without correction for false positive errors overestimated incidence and prevalence of IPF. An IPF score offered the greatest PPV, but it requires further validation.

Hospitalization with acute exacerbation of chronic obstructive pulmonary disease and associated health resource utilization: a population-based Danish cohort study.

OBJECTIVE: Health resource utilization (HRU) and outcomes associated with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) are not well described. Therefore, a population-based cohort study was conducted to characterize patients hospitalized with AECOPD with regard to HRU, mortality, recurrence, and predictors of readmission with AECOPD. METHODS: Using Danish healthcare databases, this study identified COPD patients with at least one AECOPD hospitalization between 2005-2009 in Northern Denmark. Hospitalized AECOPD patients' HRU, in-hospital mortality, 30-day, 60-day, 90-day, and 180-day post-discharge mortality and recurrence risk, and predictors of readmission with AECOPD in the year following study inclusion were characterized. RESULTS: This study observed 6612 AECOPD hospitalizations among 3176 prevalent COPD patients. Among all AECOPD hospitalizations, median length of stay was 6 days (interquartile range [IQR] 3-9 days); 5 days (IQR 3-9) among those without ICU stay and 11 days (IQR 7-20) among the 8.6% admitted to the ICU. Mechanical ventilation was provided to 193 (2.9%) and non-invasive ventilation to 479 (7.2%) admitted patients. In-hospital mortality was 5.6%. Post-discharge mortality was 4.2%, 7.8%, 10.5%, and 17.4% at 30, 60, 90, and 180 days, respectively. Mortality and readmission risk increased with each AECOPD hospitalization experienced in the first year of follow-up. Readmission at least twice in the first year of follow-up was observed among 286 (9.0%) COPD patients and was related to increasing age, male gender, obesity, asthma, osteoporosis, depression, myocardial infarction, diabetes I and II, any malignancy, and hospitalization with AECOPD or COPD in the prior year. LIMITATIONS: The study included only hospitalized AECOPD patients among prevalent COPD patients. Furthermore, information was lacking on clinical variables. CONCLUSION: These findings indicate that AECOPD hospitalizations are associated with substantial mortality and risk of recurrence.

Hospital discharge to other healthcare facilities: impact on in-hospital mortality.

BACKGROUND: In-hospital mortality is frequently used as an outcomes measure for surgical procedures. Recently, hospitals have developed subacute care facilities to allow earlier discharge. Outcomes of patients discharged (transferred) to these units or to other similar facilities may not be captured in reports of in-hospital mortality. STUDY DESIGN: The California Office of Statewide Health Planning and Development (OSHPD) patient discharge abstract database was examined to determine the rates of discharge to other facilities (transfer) and the number of in-hospital deaths occurring during the index hospitalization and after transfer in patients undergoing cardiac surgery procedures. Data were collected for 1997, 1998, and 1999 for coronary artery bypass grafting (CABG-only, n = 82,897), CABG plus additional procedures (CABG-plus, n = 11,869), and valve repair or replacement (Valve-only, n = 14,872). In-hospital mortality and transfer rates (same-day discharge and readmission to another facility) were determined for all hospitals through the index hospitalization and subsequent transfers. RESULTS: Aggregated 3-year in-hospital mortality rates for the index hospitalization were 2.98% for CABG-only, 9.25% for CABG-plus, and 4.85% in Valve-only groups. Transfer rates were 12.41%, 23.16%, and 13.43%, respectively. The percentages of all in-hospital deaths occurring after transfer from the index hospital were 13.5% (385 of 2,857) in CABG-only, 13.3% (168 of 1,266) in CABG-plus, and 11.0% (89 of 811) in Valve-only patients. When corrected for these additional deaths, the actual in-hospital mortality rate was 3.45% for CABG-only, 10.67% for CABG-plus, and 5.45% for Valve-only procedures. CONCLUSIONS: Transfer to another healthcare facility rather than discharge home is a common practice after cardiac surgery. A substantial percentage of in-hospital deaths occurs after discharge from the primary institution.