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Background: The prevalence, incidence, and interrelationships of persistent symptoms after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection vary. There are limited data on specific phenotypes of persistent symptoms. Using latent class analysis (LCA) modeling, we sought to identify whether specific phenotypes of COVID-19 were present 3 months and 6 months post-infection., Methods: This was a multicenter study of symptomatic adults tested for SARS-CoV-2 with prospectively collected data on general symptoms and fatigue-related symptoms up to 6 months postdiagnosis. Using LCA, we identified symptomatically homogenous groups among COVID-positive and COVID-negative participants at each time period for both general and fatigue-related symptoms., Results: Among 5963 baseline participants (4504 COVID-positive and 1459 COVID-negative), 4056 had 3-month and 2856 had 6-month data at the time of analysis. We identified 4 distinct phenotypes of post-COVID conditions (PCCs) at 3 and 6 months for both general and fatigue-related symptoms; minimal-symptom groups represented 70% of participants at 3 and 6 months. When compared with the COVID-negative cohort, COVID-positive participants had higher occurrence of loss of taste/smell and cognition problems. There was substantial class-switching over time; those in 1 symptom class at 3 months were equally likely to remain or enter a new phenotype at 6 months., Conclusions: We identified distinct classes of PCC phenotypes for general and fatigue-related symptoms. Most participants had minimal or no symptoms at 3 and 6 months of follow-up. Significant proportions of participants changed symptom groups over time, suggesting that symptoms present during the acute illness may differ from prolonged symptoms and that PCCs may have a more dynamic nature than previously recognized. Clinical Trials Registration.  NCT04610515., Competing Interests: Potential conflicts of interest. M. G. reports funding from the Rush Center for Emerging Infectious Diseases Research Grant, Emergency Medicine Foundation/Council of Residency Directors in Emergency Medicine Education Research Grant, Emergency Medicine: Reviews and Perspectives Medical Education Research Grant, University of Ottawa Department of Medicine Education Grant, and Society of Directors of Research in Medical Education Grant. E. S. S. receives grant funding from the National Institute on Minority Health and Health Disparities (U54MD010711-01), the US Food and Drug Administration to support projects within the Yale-Mayo Clinic Center of Excellence in Regulatory Science and Innovation (CERSI, U01FD005938), the National Institute of Biomedical Imaging and Bioengineering (R01EB028106-01), and the National Heart, Lung, and Blood Institute (R01HL151240). J. G. E. reports serving as Editor-in-Chief of Adult Primary Care topics for UpToDate. N. L. G. receives grant funding from the CDC (BAA75D301-20-75D30121C10207). A. V. reports funding for COVID-19–related studies from the Society of Academic Emergency Medicine Foundation Emerging Infectious Disease and Preparedness Grant, the Agency for Healthcare Research and Quality (R01 HS 28340-01), the Food and Drug Administration (ID: 75F40120C00174), and the Centers for Medicare and Medicaid Services. G. N. reports the following: funding for COVID-19–related studies from the National Institute of Allergy and Infectious Diseases (NIAID) (1R01AI66967), research funding from Abiomed, Vapotherm, and ZOLL Medical; consultant to CPR Therapeutics, Heartbeam Inc, Invero Health LLC, Kestra Medical Technologies, Orixha, and ZOLL Circulation; and reports a patent (Method for non-imaging ultrasound to measure blood flow during CPR) and nonprovisional patent (Method for modifying cell injury associated with reduced blood flow). K. N. O. reports funding for COVID-19–related studies from NIAID (1R01AI66967). K. L. R. reports funding for COVID-19–related studies from NIAID (1R01AI66967) and the Philadelphia Department of Public Health. All other authors report no potential conflicts., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background: While prior work examining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern focused on hospitalization and death, less is known about differences in clinical presentation. We compared the prevalence of acute symptoms across pre-Delta, Delta, and Omicron., Methods: We conducted an analysis of the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE), a cohort study enrolling symptomatic SARS-CoV-2-positive participants. We determined the association between the pre-Delta, Delta, and Omicron time periods and the prevalence of 21 coronavirus disease 2019 (COVID-19) acute symptoms., Results: We enrolled 4113 participants from December 2020 to June 2022. Pre-Delta vs Delta vs Omicron participants had increasing sore throat (40.9%, 54.6%, 70.6%; P < .001), cough (50.9%, 63.3%, 66.7%; P < .001), and runny noses (48.9%, 71.3%, 72.9%; P < .001). We observed reductions during Omicron in chest pain (31.1%, 24.2%, 20.9%; P < .001), shortness of breath (42.7%, 29.5%, 27.5%; P < .001), loss of taste (47.1%, 61.8%, 19.2%; P < .001), and loss of smell (47.5%, 55.6%, 20.0%; P < .001). After adjustment, those infected during Omicron had significantly higher odds of sore throat vs pre-Delta (odds ratio [OR], 2.76; 95% CI, 2.26-3.35) and Delta (OR, 1.96; 95% CI, 1.69-2.28)., Conclusions: Participants infected during Omicron were more likely to report symptoms of common respiratory viruses, such as sore throat, and less likely to report loss of smell and taste., Trial Registration: NCT04610515., Competing Interests: Potential conflicts of interest. Dr. Elmore reports serving as Editor in Chief of Adult Primary Care topics for UpToDate. Dr. Venkatesh reports funding for COVID-19-related studies from the Society of Academic Emergency Medicine Foundation Emerging Infectious Disease and Preparedness Grant, the Agency for Healthcare Research and Quality (R01 HS 28340-01) the Food and Drug Administration (ID: 75F40120C00174), and the Emergency Medicine Health Policy Institute/Emergency Medicine Foundation. Dr. Wang reports funding from CDC for research on N95 respirators. Dr. Gottlieb reports grant funding from the Rush Center for Emerging Infectious Diseases Research Grant, Emergency Medicine Foundation/Council of Residency Directors in Emergency Medicine Education Research Grant, Emergency Medicine: Reviews and Perspectives Medical Education Research Grant, University of Ottawa Department of Medicine Education Grant; and Society of Directors of Research in Medical Education Grant. Dr. Nichol reports the following: Vapotherm Inc, Exeter, NH- Research funding; ZOLL Medical, Chelmsford, MA- Research funding; Abiomed Inc., Danvers, MA- Consultant; CellPhire Inc., Rockville, MD- Consultant; CPR Therapeutics, Putney, VT- Consultant; ZOLL Circulation, San Jose, CA- Consultant; Patent- Method for non-imaging ultrasound to measure blood flow during CPR; Non-provisional patent- Method for modifying cell injury associated with reduced blood flow; Heartbeam Inc., Santa Clara, CA- Consultant; Invero Health, LLC., Montvale, NJ- Consultant; Orixha Inc., Saint Cyr Au Mont d’Or, France- Consultant; Kestra Medical Technologies, Kirkland, WA- Consultant; Medic One Foundation, Seattle, WA- Salary Support via Univ. Washington (UW). Dr. Elmore reports serving as Editor in Chief of Adult Primary Care topics for UpToDate. Dr. Venkatesh reports funding for COVID-19-related studies from the Society of Academic Emergency Medicine Foundation Emerging Infectious Disease and Preparedness Grant, the Agency for Healthcare Research and Quality (R01 HS 28340-01), the Food and Drug Administration (ID: 75F40120C00174), and the Emergency Medicine Health Policy Institute/Emergency Medicine Foundation. Dr. Wang reports funding from CDC for research on N95 respirators. All other authors report no potential conflicts., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background: Long-term symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are a major concern, yet their prevalence is poorly understood., Methods: We conducted a prospective cohort study comparing adults with SARS-CoV-2 infection (coronavirus disease-positive [COVID+]) with adults who tested negative (COVID-), enrolled within 28 days of a Food and Drug Administration (FDA)-approved SARS-CoV-2 test result for active symptoms. Sociodemographic characteristics, symptoms of SARS-CoV-2 infection (assessed with the Centers for Disease Control and Prevention [CDC] Person Under Investigation Symptom List), and symptoms of post-infectious syndromes (ie, fatigue, sleep quality, muscle/joint pains, unrefreshing sleep, and dizziness/fainting, assessed with CDC Short Symptom Screener for myalgic encephalomyelitis/chronic fatigue syndrome) were assessed at baseline and 3 months via electronic surveys sent via text or email., Results: Among the first 1000 participants, 722 were COVID+ and 278 were COVID-. Mean age was 41.5 (SD 15.2); 66.3% were female, 13.4% were Black, and 15.3% were Hispanic. At baseline, SARS-CoV-2 symptoms were more common in the COVID+ group than the COVID- group. At 3 months, SARS-CoV-2 symptoms declined in both groups, although were more prevalent in the COVID+ group: upper respiratory symptoms/head/eyes/ears/nose/throat (HEENT; 37.3% vs 20.9%), constitutional (28.8% vs 19.4%), musculoskeletal (19.5% vs 14.7%), pulmonary (17.6% vs 12.2%), cardiovascular (10.0% vs 7.2%), and gastrointestinal (8.7% vs 8.3%); only 50.2% and 73.3% reported no symptoms at all. Symptoms of post-infectious syndromes were similarly prevalent among the COVID+ and COVID- groups at 3 months., Conclusions: Approximately half of COVID+ participants, as compared with one-quarter of COVID- participants, had at least 1 SARS-CoV-2 symptom at 3 months, highlighting the need for future work to distinguish long COVID., Clinical Trials Registration: NCT04610515., Competing Interests: Potential conflicts of interest . All authors: No potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: The aim of the present study was to detect the association between platelet glycoprotein-specific autoantibodies and the patient response to short-term high-dose dexamethasone (HD-DXM) + prednisone maintenance treatment., Methods: The data from 112 adult patients newly diagnosed with ITP who were administered first-line HD-DXM + prednisone maintenance therapy between January 2016 and January 2021 were retrospectively analyzed., Results: A total of 72 patients positive for platelet glycoprotein-specific antibodies were enrolled in the antibody-positive group, and 40 patients not positive for platelet glycoprotein-specific antibodies were enrolled in the antibody-negative group. In the antibody-positive group, six platelet glycoprotein-specific antibody types were found: 41.67% of the patients were anti-GP IIb/IIIa-positive only, 5.56% were anti-GP Ib/IX-positive only, 5.56% were anti-P-selectin-positive only, 19.44% were anti-GP IIb/IIIa- and anti-GP Ib/IX-positive, 16.67% were anti-GP Ib/IX- and P-selectin-positive and 11.11% were positive for all three antibodies. There was no significant difference in the overall response rate between the antibody-positive group and the antibody-negative group (94.44 versus 80.00%, p  = .221). However, the CR rate was significantly higher in the antibody-positive group than in the antibody-negative group (69.44% versus 40.00%, p  = .032). The logistic regression analysis revealed that platelet glycoprotein-specific antibody positivity and age were two factors that could affect patient response., Conclusions: The present study discovered that adult patients newly diagnosed with ITP who had positive platelet glycoprotein-specific antibody test results were likely to achieve a better response after treatment with HD-DXM + prednisone maintenance.

Importance: An increasing proportion of people in the US hospitalized for acute myocardial infarction (AMI) are younger than 55 years, with the largest increase in young women. Effective prevention requires an understanding of risk factors associated with risk of AMI in young women compared with men., Objectives: To assess the sex-specific associations of demographic, clinical, and psychosocial risk factors with first AMI among adults younger than 55 years, overall, and by AMI subtype., Design, Setting, and Participants: This study used a case-control design with 2264 patients with AMI, aged 18 to 55 years, from the VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients) study and 2264 population-based controls matched for age, sex, and race and ethnicity from the National Health and Nutrition Examination Survey from 2008 to 2012. Data were analyzed from April 2020 to November 2021., Exposures: A wide range of demographic, clinical, and psychosocial risk factors., Main Outcomes and Measures: Odds ratios (ORs) and population attributable fractions (PAF) for first AMI associated with demographic, clinical, and psychosocial risk factors., Results: Of the 4528 case patients and matched controls, 3122 (68.9%) were women, and the median (IQR) age was 48 (44-52) years. Seven risk factors (diabetes [OR, 3.59 (95% CI, 2.72-4.74) in women vs 1.76 (1.19-2.60) in men], depression [OR, 3.09 (95% CI, 2.37-4.04) in women vs 1.77 (1.15-2.73) in men], hypertension [OR, 2.87 (95% CI, 2.31-3.57) in women vs 2.19 (1.65-2.90) in men], current smoking [OR, 3.28 (95% CI, 2.65-4.07) in women vs 3.28 (2.65-4.07) in men], family history of premature myocardial infarction [OR, 1.48 (95% CI, 1.17-1.88) in women vs 2.42 (1.71-3.41) in men], low household income [OR, 1.79 (95% CI, 1.28-2.50) in women vs 1.35 (0.82-2.23) in men], hypercholesterolemia [OR, 1.02 (95% CI, 0.81-1.29) in women vs 2.16 (1.49-3.15) in men]) collectively accounted for the majority of the total risk of AMI in women (83.9%) and men (85.1%). There were significant sex differences in risk factor associations: hypertension, depression, diabetes, current smoking, and family history of diabetes had stronger associations with AMI in young women, whereas hypercholesterolemia had a stronger association in young men. Risk factor profiles varied by AMI subtype, and traditional cardiovascular risk factors had higher prevalence and stronger ORs for type 1 AMI compared with other AMI subtypes., Conclusions and Relevance: In this case-control study, 7 risk factors, many potentially modifiable, accounted for 85% of the risk of first AMI in young women and men. Significant differences in risk factor profiles and risk factor associations existed by sex and by AMI subtype. These findings suggest the need for sex-specific strategies in risk factor modification and prevention of AMI in young adults. Further research is needed to improve risk assessment of AMI subtypes.

Background: New methods such as machine learning techniques have been increasingly used to enhance the performance of risk predictions for clinical decision-making. However, commonly reported performance metrics may not be sufficient to capture the advantages of these newly proposed models for their adoption by health care professionals to improve care. Machine learning models often improve risk estimation for certain subpopulations that may be missed by these metrics., Methods and Results: This article addresses the limitations of commonly reported metrics for performance comparison and proposes additional metrics. Our discussions cover metrics related to overall performance, discrimination, calibration, resolution, reclassification, and model implementation. Models for predicting acute kidney injury after percutaneous coronary intervention are used to illustrate the use of these metrics., Conclusions: We demonstrate that commonly reported metrics may not have sufficient sensitivity to identify improvement of machine learning models and propose the use of a comprehensive list of performance metrics for reporting and comparing clinical risk prediction models.

The COVID-19 pandemic has disproportionately affected Hispanic or Latino, non-Hispanic Black (Black), non-Hispanic American Indian or Alaska Native (AI/AN), and non-Hispanic Native Hawaiian or Other Pacific Islander (NH/PI) populations in the United States. These populations have experienced higher rates of infection and mortality compared with the non-Hispanic White (White) population (1-5) and greater excess mortality (i.e., the percentage increase in the number of persons who have died relative to the expected number of deaths for a given place and time) (6). A limitation of existing research on excess mortality among racial/ethnic minority groups has been the lack of adjustment for age and population change over time. This study assessed excess mortality incidence rates (IRs) (e.g., the number of excess deaths per 100,000 person-years) in the United States during December 29, 2019-January 2, 2021, by race/ethnicity and age group using data from the National Vital Statistics System. Among all assessed racial/ethnic groups (non-Hispanic Asian [Asian], AI/AN, Black, Hispanic, NH/PI, and White populations), excess mortality IRs were higher among persons aged ≥65 years (426.4 to 1033.5 excess deaths per 100,000 person-years) than among those aged 25-64 years (30.2 to 221.1) and those aged <25 years (-2.9 to 14.1). Among persons aged <65 years, Black and AI/AN populations had the highest excess mortality IRs. Among adults aged ≥65 years, Black and Hispanic persons experienced the highest excess mortality IRs of >1,000 excess deaths per 100,000 person-years. These findings could help guide more tailored public health messaging and mitigation efforts to reduce disparities in mortality associated with the COVID-19 pandemic in the United States,* by identifying the racial/ethnic groups and age groups with the highest excess mortality rates., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Zhenqiu Lin reports contract support from the Centers for Medicare & Medicaid Services (CMS) to develop and maintain measures of hospital performance that are publicly reported. Harlan M. Krumholz reports the following outside the current work: honoraria for presentations at various educational events; grants from Medtronic and the Food and Drug Administration, Medtronic and Johnson & Johnson, Shenzhen Center for Health Information, Foundation for a Smoke-Free World, and Connecticut Department of Public Health and CMS; payment from law firms Martin/Baughman, Arnold & Porter, and Siegfried & Jensen for expert testimony; chairmanship or member of United Healthcare cardiac scientific advisory board, IBM Watson Health life sciences board, Element Science scientific advisor, Aetna health care advisory board, and Facebook advisory board; and ownership of Hugo Health and Refractor Health. No other potential conflicts of interest were disclosed.

Objective: Although timely administration of antibiotics has an established benefit in serious bacterial infection, the majority of studies evaluating antibiotic delay focus only on the first dose. Recent evidence suggests that delays in redosing may also be associated with worse clinical outcome. In light of the increasing burden of boarding in Emergency Departments (ED) and subsequent need to redose antibiotic in the ED, we examined the association between delayed second antibiotic dose administration and mortality among patients admitted from the ED with a broad array of infections and characterized risk factors associated with delayed second dose administration., Methods: We performed a retrospective cohort study of patients admitted through five EDs in a single healthcare system from 1/2018 through 12/2018. Our study included all patients, aged 18 years or older, who received two intravenous antibiotic doses within a 30-h period, with the first dose administered in the ED. Patients with end stage renal disease, cirrhosis and extremes of weight were excluded due to a lack of consensus on antibiotic dosing intervals for these populations. Delay was defined as administration of the second dose at a time-point greater than 125% of the recommended interval. The primary outcome was in-hospital mortality., Results: A total of 5605 second antibiotic doses, occurring during 4904 visits, met study criteria. Delayed administration of the second dose occurred during 21.1% of visits. After adjustment for patient characteristics, delayed second dose administration was associated with increased odds of in-hospital mortality (OR 1.50, 95%CI 1.05-2.13). Regarding risk factors for delay, every one-hour increase in allowable compliance time was associated with a 18% decrease in odds of delay (OR 0.82 95%CI 0.75-0.88). Other risk factors for delay included ED boarding more than 4 h (OR 1.47, 95%CI 1.27-1.71) or a high acuity presentation as defined by emergency severity index (ESI) (OR 1.54, 95%CI 1.30-1.81 for ESI 1-2 versus 3-5)., Conclusions: Delays in second antibiotic dose administration were frequent in the ED and early hospital course, and were associated with increased odds of in-hospital mortality. Several risk factors associated with delays in second dose administration, including ED boarding, were identified., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Infection fatality rate and infection hospitalization rate, defined as the proportion of deaths and hospitalizations, respectively, of the total infected individuals, can estimate the actual toll of coronavirus disease 2019 (COVID-19) on a community, as the denominator is ideally based on a representative sample of a population, which captures the full spectrum of illness, including asymptomatic and untested individuals., Objective: To determine the COVID-19 infection hospitalization rate and infection fatality rate among the non-congregate population in Connecticut between March 1 and June 1, 2020., Methods: The infection hospitalization rate and infection fatality rate were calculated for adults residing in non-congregate settings in Connecticut prior to June 2020. Individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies were estimated using the seroprevalence estimates from the recently conducted Post-Infection Prevalence study. Information on total hospitalizations and deaths was obtained from the Connecticut Hospital Association and the Connecticut Department of Public Health, respectively., Results: Prior to June 1, 2020, nearly 113,515 (90% confidence interval [CI] 56,758-170,273) individuals were estimated to have SARS-CoV-2 antibodies, and there were 7792 hospitalizations and 1079 deaths among the non-congregate population. The overall COVID-19 infection hospitalization rate and infection fatality rate were estimated to be 6.86% (90% CI, 4.58%-13.72%) and 0.95% (90% CI, 0.63%-1.90%), respectively, and there was variation in these rate estimates across subgroups; older people, men, non-Hispanic Black people, and those belonging to 2 of the counties had a higher burden of adverse outcomes, although the differences between most subgroups were not statistically significant., Conclusions: Using representative seroprevalence estimates, the overall COVID-19 infection hospitalization rate and infection fatality rate were estimated to be 6.86% and 0.95%, respectively, among community residents in Connecticut., (Published by Elsevier Inc.)

Importance: Present-on-admission (POA) indicators in administrative claims data allow researchers to distinguish between preexisting conditions and those acquired during a hospital stay. The impact of adding POA information to claims-based measures of hospital quality has not yet been investigated to better understand patient underlying risk factors in the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision setting., Objective: To assess POA indicator use on Medicare claims and to assess the hospital- and patient-level outcomes associated with incorporating POA indicators in identifying risk factors for publicly reported outcome measures used by the Centers for Medicare & Medicaid Services (CMS)., Design, Setting, and Participants: This comparative effectiveness study used national CMS claims data between July 1, 2015, and June 30, 2018. Six hospital quality measures assessing readmission and mortality outcomes were modified to include POA indicators in risk adjustment models. The models using POA were then compared with models using the existing complications-of-care algorithm to evaluate changes in risk model performance. Patient claims data were included for all Medicare fee-for-service and Veterans Administration beneficiaries aged 65 years or older with inpatient hospitalizations for acute myocardial infarction, heart failure, or pneumonia within the measurement period. Data were analyzed between September 2019 and March 2020., Main Outcomes and Measures: Changes in patient-level (C statistics) and hospital-level (quintile shifts in risk-standardized outcome rates) model performance after including POA indicators in risk adjustment., Results: Data from a total of 6 027 988 index admissions were included for analysis, ranging from 491 366 admissions (269 209 [54.8%] men; mean [SD] age, 78.2 [8.3] years) for the acute myocardial infarction mortality outcome measure to 1 395 870 admissions (677 158 [48.5%] men; mean [SD] age, 80.3 [8.7] years) for the pneumonia readmission measure. Use of POA indicators was associated with improvements in risk adjustment model performance, particularly for mortality measures (eg, the C statistic increased from 0.728 [95% CI, 0.726-0.730] to 0.774 [95% CI, 0.773-0.776] when incorporating POA indicators into the acute myocardial infarction mortality measure)., Conclusions and Relevance: The findings of this quality improvement study suggest that leveraging POA indicators in the risk adjustment methodology for hospital quality outcome measures may help to more fully capture patients' risk factors and improve overall model performance. Incorporating POA indicators does not require extra effort on the part of hospitals and would be easy to implement in publicly reported quality outcome measures.

Background: To estimate, prior to finalization of claims, the national monthly numbers of admissions and rates of 30-day readmissions and post-discharge observation-stays for Medicare fee-for-service beneficiaries hospitalized with acute myocardial infarction (AMI), heart failure (HF), or pneumonia., Methods: The centers for Medicare & Medicaid Services (CMS) Integrated Data Repository, including the Medicare beneficiary enrollment database, was accessed in June 2015, February 2017, and February 2018. We evaluated patterns of delay in Medicare claims accrual, and used incomplete, non-final claims data to develop and validate models for real-time estimation of admissions, readmissions, and observation stays., Results: These real-time reporting models accurately estimate, within 2 months from admission, the monthly numbers of admissions, 30-day readmission and observation-stay rates for patients with AMI, HF, or pneumonia., Conclusions: This work will allow CMS to track the impact of policy decisions in real time and enable hospitals to better monitor their performance nationally.

Importance: Determining the association of contrast volume during percutaneous coronary intervention (PCI) with the risk of acute kidney injury (AKI) is important for optimizing PCI safety., Objective: To quantify how the risk of AKI is associated with contrast volume, accounting for the possibility of nonlinearity and heterogeneity among different baseline risks., Design, Setting, and Participants: This prognostic study used data from the American College of Cardiology National Cardiovascular Data Registry CathPCI Registry for 1694 US hospitals. Derivation analysis included 2 076 694 individuals who underwent PCI from July 1, 2011, to June 30, 2015. Validation analysis included 961 863 individuals who underwent PCI from July 1, 2015, to March 31, 2017. Data analysis took place from July 2018 to May 2019., Exposure: Contrast volume during PCI., Main Outcomes and Measures: Acute kidney injury was defined using 3 thresholds for preprocedure to postprocedure creatinine level increase (ie, ≥0.3 mg/dL, ≥0.5 mg/dL, and ≥1.0 mg/dL). A model quantifying the association of contrast volume with AKI was developed, and the existence of nonlinearity and heterogeneity were examined by likelihood ratio tests. The model was derived in the training set (a random 50% of the derivation cohort), and performance was evaluated in the test set (the remaining 50% of the derivation cohort) and an independent validation set by area under the receiver operating characteristic curve (AUC) and calibration slope of observed vs predicted risks., Results: The 2 076 694 patients in the derivation set had a mean (SD) age of 65.1 (12.1) years, and 662 525 (31.9%) were women; 133 306 (6.4%) had creatinine level increases of at least 0.3 mg/dL, 66 626 (3.2%) had creatinine level increases of at least 0.5 mg/dL, and 28 378 (1.4%) had creatinine level increases of at least 1.0 mg/dL. In the validation set of 961 843 patients (mean [SD] age, 65.7 [12.1] years; 305 577 [31.8%] women), these rates were 62 913 (6.5%), 34 229 (3.6%), and 15 555 (1.6%), respectively. The association of contrast volume and AKI risk was nonlinear (χ226 = 1436.2; P < .001) and varied by preprocedural risk (χ220 = 105.6; P < .001). In the test set, the model yielded an AUC of 0.777 (95% CI, 0.775-0.779) for predicting risk of a creatinine level increase of at least 0.3 mg/dL, 0.839 (95% CI, 0.837-0.841) for predicting risk of a creatinine level increase of at least 0.5 mg/dL, and 0.870 (95% CI, 0.867-0.873) for predicting risk of a creatinine level increase of at least 1.0 mg/dL; it achieved a calibration slope of 0.998 (95% CI, 0.989-1.007), 0.999 (95% CI, 0.989-1.008), and 0.986 (95% CI, 0.973-0.998), respectively, for the AKI severity levels. The model had similar performance in the validation set (creatinine level increase of ≥0.3 mg/dL: AUC, 0.794; 95% CI, 0.792-0.795; calibration slope, 1.039; 95% CI, 1.030-1.047; creatinine level increase of ≥0.5 mg/dL: AUC, 0.845; 95% CI, 0.843-0.848; calibration slope, 1.063; 95% CI, 1.054-1.074; creatinine level increase of ≥1.0 mg/dL: AUC, 0.872; 95% CI, 0.869-0.875; calibration slope, 1.103; 95% CI, 1.089-1.117)., Conclusions and Relevance: The association of contrast volume with AKI risk is complex, varies by baseline risk, and can be predicted by a model. Future research to evaluate the effect of the model on AKI is needed.

Importance: Predicting payments for particular conditions or populations is essential for research, benchmarking, public reporting, and calculations for population-based programs. Centers for Medicare & Medicaid Services (CMS) models often group codes into disease categories, but using single, rather than grouped, diagnostic codes and leveraging present on admission (POA) codes may enhance these models., Objective: To determine whether changes to the candidate variables in CMS models would improve risk models predicting patient total payment within 30 days of hospitalization for acute myocardial infarction (AMI), heart failure (HF), and pneumonia., Design, Setting, and Participants: This comparative effectiveness research study used data from Medicare fee-for-service hospitalizations for AMI, HF, and pneumonia at acute care hospitals from July 1, 2013, through September 30, 2015. Payments across multiple care settings, services, and supplies were included and adjusted for geographic and policy variations, corrected for inflation, and winsorized. The same data source was used but varied for the candidate variables and their selection, and the method used by CMS for public reporting that used grouped codes was compared with variations that used POA codes and single diagnostic codes. Combinations of use of POA codes, separation of index admission diagnoses from those in the previous 12 months, and use of individual International Classification of Diseases, Ninth Revision, Clinical Modification codes instead of grouped diagnostic categories were tested. Data analysis was performed from December 4, 2017, to June 10, 2019., Main Outcomes and Measures: The models' goodness of fit was compared using root mean square error (RMSE) and the McFadden pseudo R2., Results: Among the 1 943 049 total hospitalizations of the study participants, 343 116 admissions were for AMI (52.5% male; 37.4% aged ≤74 years), 677 044 for HF (45.5% male; 25.9% aged ≤74 years), and 922 889 for pneumonia (46.4% male; 28.2% aged ≤74 years). The mean (SD) 30-day payment was $23 103 ($18 221) for AMI, $16 365 ($12 527) for HF, and $17 097 ($12 087) for pneumonia. Each incremental model change improved the pseudo R2 and RMSE. Incorporating all 3 changes improved the pseudo R2 of the patient-level models from 0.077 to 0.129 for AMI, from 0.042 to 0.129 for HF, and from 0.114 to 0.237 for pneumonia. Parallel improvements in RMSE were found for all 3 conditions., Conclusions and Relevance: Leveraging POA codes, separating index from previous diagnoses, and using single diagnostic codes improved payment models. Better models can potentially improve research, benchmarking, public reporting, and calculations for population-based programs.

Importance: Risk adjustment models using claims-based data are central in evaluating health care performance. Although US Centers for Medicare & Medicaid Services (CMS) models apply well-vetted statistical approaches, recent changes in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding system and advances in computational capabilities may provide an opportunity for enhancement., Objective: To examine whether changes using already available data would enhance risk models and yield greater discrimination in hospital-level performance measures., Design, Setting, and Participants: This comparative effectiveness study used ICD-9-CM codes from all Medicare fee-for-service beneficiary claims for hospitalizations for acute myocardial infarction (AMI), heart failure (HF), or pneumonia among patients 65 years and older from July 1, 2013, through September 30, 2015. Changes to current CMS mortality risk models were applied incrementally to patient-level models, and the best model was tested on hospital performance measures to model 30-day mortality. Analyses were conducted from April 19, 2018, to September 19, 2018., Main Outcomes and Measures: The main outcome was all-cause death within 30 days of hospitalization for AMI, HF, or pneumonia, examined using 3 changes to current CMS mortality risk models: (1) incorporating present on admission coding to better exclude potential complications of care, (2) separating index admission diagnoses from those of the 12-month history, and (3) using ungrouped ICD-9-CM codes., Results: There were 361 175 hospital admissions (mean [SD] age, 78.6 [8.4] years; 189 225 [52.4%] men) for AMI, 716 790 hospital admissions (mean [SD] age, 81.1 [8.4] years; 326 825 [45.6%] men) for HF, and 988 225 hospital admissions (mean [SD] age, 80.7 [8.6] years; 460 761 [46.6%] men) for pneumonia during the study; mean 30-day mortality rates were 13.8% for AMI, 12.1% for HF, and 16.1% for pneumonia. Each change to the models was associated with incremental gains in C statistics. The best model, incorporating all changes, was associated with significantly improved patient-level C statistics, from 0.720 to 0.826 for AMI, 0.685 to 0.776 for HF, and 0.715 to 0.804 for pneumonia. Compared with current CMS models, the best model produced wider predicted probabilities with better calibration and Brier scores. Hospital risk-standardized mortality rates had wider distributions, with more hospitals identified as good or bad performance outliers., Conclusions and Relevance: Incorporating present on admission coding and using ungrouped index and historical ICD-9-CM codes were associated with improved patient-level and hospital-level risk models for mortality compared with the current CMS models for all 3 conditions.

The grey wolf optimizer (GWO) is a novel type of swarm intelligence optimization algorithm. An improved grey wolf optimizer (IGWO) with evolution and elimination mechanism was proposed so as to achieve the proper compromise between exploration and exploitation, further accelerate the convergence and increase the optimization accuracy of GWO. The biological evolution and the "survival of the fittest" (SOF) principle of biological updating of nature are added to the basic wolf algorithm. The differential evolution (DE) is adopted as the evolutionary pattern of wolves. The wolf pack is updated according to the SOF principle so as to make the algorithm not fall into the local optimum. That is, after each iteration of the algorithm sort the fitness value that corresponds to each wolf by ascending order, and then eliminate R wolves with worst fitness value, meanwhile randomly generate wolves equal to the number of eliminated wolves. Finally, 12 typical benchmark functions are used to carry out simulation experiments with GWO with differential evolution (DGWO), GWO algorithm with SOF mechanism (SGWO), IGWO, DE algorithm, particle swarm algorithm (PSO), artificial bee colony (ABC) algorithm and cuckoo search (CS) algorithm. Experimental results show that IGWO obtains the better convergence velocity and optimization accuracy.

Background: Efforts to decrease hospitalization costs could increase post-acute care costs. This effect could undermine initiatives to reduce overall episode costs and have implications for the design of health care under alternative payment models., Methods: Among Medicare fee-for-service beneficiaries aged ≥65 years hospitalized with acute myocardial infarction (AMI) between July 2010 and June 2013 in the Premier Healthcare Database, we studied the association of in-hospital and post-acute care resource utilization and outcomes by in-hospital cost tertiles., Results: Among patients with AMI at 326 hospitals, the median (range) of each hospital's mean per-patient in-hospital risk-standardized cost (RSC) for the low, medium, and high cost tertiles were $16,257 ($13,097-$17,648), $18,544 ($17,663-$19,875), and $21,831 ($19,923-$31,296), respectively. There was no difference in the median (IQR) of risk-standardized post-acute payments across cost-tertiles: $5014 (4295-6051), $4980 (4349-5931) and $4922 (4056-5457) for the low (n = 90), medium (n = 98), and high (n = 86) in-hospital RSC tertiles (p = 0.21), respectively. In-hospital and 30-day mortality rates did not differ significantly across the in-hospital RSC tertiles; however, 30-day readmission rates were higher at hospitals with higher in-hospital RSCs: median = 17.5, 17.8, and 18.0% at low, medium, and high in-hospital RSC tertiles, respectively (p = 0.005 for test of trend across tertiles)., Conclusions: In our study of patients hospitalized with AMI, greater resource utilization during the hospitalization was not associated with meaningful differences in costs or mortality during the post-acute period. These findings suggest that it may be possible for higher cost hospitals to improve efficiency in care without increasing post-acute care utilization or worsening outcomes.

Background: The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether models using machine learning techniques could significantly improve AKI risk prediction after PCI., Methods and Findings: We used the same cohort and candidate variables used to develop the current NCDR CathPCI Registry AKI model, including 947,091 patients who underwent PCI procedures between June 1, 2009, and June 30, 2011. The mean age of these patients was 64.8 years, and 32.8% were women, with a total of 69,826 (7.4%) AKI events. We replicated the current AKI model as the baseline model and compared it with a series of new models. Temporal validation was performed using data from 970,869 patients undergoing PCIs between July 1, 2016, and March 31, 2017, with a mean age of 65.7 years; 31.9% were women, and 72,954 (7.5%) had AKI events. Each model was derived by implementing one of two strategies for preprocessing candidate variables (preselecting and transforming candidate variables or using all candidate variables in their original forms), one of three variable-selection methods (stepwise backward selection, lasso regularization, or permutation-based selection), and one of two methods to model the relationship between variables and outcome (logistic regression or gradient descent boosting). The cohort was divided into different training (70%) and test (30%) sets using 100 different random splits, and the performance of the models was evaluated internally in the test sets. The best model, according to the internal evaluation, was derived by using all available candidate variables in their original form, permutation-based variable selection, and gradient descent boosting. Compared with the baseline model that uses 11 variables, the best model used 13 variables and achieved a significantly better area under the receiver operating characteristic curve (AUC) of 0.752 (95% confidence interval [CI] 0.749-0.754) versus 0.711 (95% CI 0.708-0.714), a significantly better Brier score of 0.0617 (95% CI 0.0615-0.0618) versus 0.0636 (95% CI 0.0634-0.0638), and a better calibration slope of observed versus predicted rate of 1.008 (95% CI 0.988-1.028) versus 1.036 (95% CI 1.015-1.056). The best model also had a significantly wider predictive range (25.3% versus 21.6%, p < 0.001) and was more accurate in stratifying AKI risk for patients. Evaluated on a more contemporary CathPCI cohort (July 1, 2015-March 31, 2017), the best model consistently achieved significantly better performance than the baseline model in AUC (0.785 versus 0.753), Brier score (0.0610 versus 0.0627), calibration slope (1.003 versus 1.062), and predictive range (29.4% versus 26.2%). The current study does not address implementation for risk calculation at the point of care, and potential challenges include the availability and accessibility of the predictors., Conclusions: Machine learning techniques and data-driven approaches resulted in improved prediction of AKI risk after PCI. The results support the potential of these techniques for improving risk prediction models and identification of patients who may benefit from risk-mitigation strategies., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: SSD is supported by the Department of Veterans Affairs. WLS is a consultant for Hugo, a personal health information platform. CIM is a consultant for Cook, Bard, Medtronic, Abbott and Cardinal Health. FPW is supported by the National Science Foundation grant R01DK113191. JSR is the Chief Innovation Officer for the American College of Cardiology. HMK is a recipient of research agreements from Medtronic and from Johnson & Johnson (Janssen), through Yale University, to develop methods of clinical trial data sharing; was the recipient of a grant from the Food and Drug Administration and Medtronic to develop methods for postmarket surveillance of medical devices; works under contract with the Centers for Medicare and Medicaid Services to develop and maintain performance measures; chairs a cardiac scientific advisory board for UnitedHealth; is a member of the Advisory Board for Element Science and the Physician Advisory Board for Aetna; is a participant/participant representative of the IBM Watson Health Life Sciences Board; and is the founder of Hugo, a personal health information platform. JAS is supported by grants from Gilead, Genentech, Lilly, Amorcyte, and EvaHeart and has a patent for the Seattle Angina Questionnaire with royalties paid. He also owns the copyright to the Seattle Angina Questionnaire. He is the PI of an Analytic Center for the American College of Cardiology Foundation and has an equity interest in Health Outcomes Sciences. FAM has a contract (through his primary institution) for his role as Chief Science Officer of the NCDR. BJM is an associate editor for PLOS ONE, which is involved in this special issue. He has a relationship with the American College of Cardiology in selecting and pursuing innovative research based upon their registry data (unrelated to this paper). He has a pending patent application for an EHR-based prediction tool in Yale New Haven Health, as well as two funded studies, one by the DoD-Advanced Research Projects Agency and one with the NSF to support student travel to conferences in the body sensor networks field. American College of Cardiology may incorporate this work, or future iterations, into its registry. No other organisation named above has a competing interest in relation to this work. The other authors report no potential competing interests.

Objectives: To characterize hospital phenotypes by their combined utilization pattern of percutaneous coronary interventions (PCI), coronary artery bypass grafting (CABG) procedures, and intensive care unit (ICU) admissions for patients hospitalized for acute myocardial infarction (AMI)., Research Design: Using the Premier Analytical Database, we identified 129,138 hospitalizations for AMI from 246 hospitals with the capacity for performing open-heart surgery during 2010-2013. We calculated year-specific, risk-standardized estimates of PCI procedure rates, CABG procedure rates, and ICU admission rates for each hospital, adjusting for patient clinical characteristics and within-hospital correlation of patients. We used a mixture modeling approach to identify groups of hospitals (ie, hospital phenotypes) that exhibit distinct longitudinal patterns of risk-standardized PCI, CABG, and ICU admission rates., Results: We identified 3 distinct phenotypes among the 246 hospitals: (1) high PCI-low CABG-high ICU admission (39.2% of the hospitals), (2) high PCI-low CABG-low ICU admission (30.5%), and (3) low PCI-high CABG-moderate ICU admission (30.4%). Hospitals in the high PCI-low CABG-high ICU admission phenotype had significantly higher risk-standardized in-hospital costs and 30-day risk-standardized payment yet similar risk-standardized mortality and readmission rates compared with hospitals in the low PCI-high CABG-moderate ICU admission phenotype. Hospitals in these phenotypes differed by geographic region., Conclusions: Hospitals differ in how they manage patients hospitalized for AMI. Their distinctive practice patterns suggest that some hospital phenotypes may be more successful in producing good outcomes at lower cost.

Background: The treatment for patients with acute myocardial infarction (AMI) was transformed by the introduction of intensive care units (ICUs), yet we know little about how contemporary hospitals use this resource-intensive setting and whether higher use is associated with better outcomes., Methods: We identified 114,136 adult hospitalizations for AMI from 307 hospitals in the 2009 to 2010 Premier database using codes from the International Classification of Diseases, Ninth Revision, Clinical Modification. Hospitals were stratified into quartiles by rates of ICU admission for AMI patients. Across quartiles, we examined in-hospital risk-standardized mortality rates and usage rates of critical care therapies for these patients., Results: Rates of ICU admission for AMI patients varied markedly among hospitals (median 48%, Q1-Q4 20%-71%, range 0%-98%), and there was no association with in-hospital risk-standardized mortality rates (6% all quartiles, P = .7). However, hospitals admitting more AMI patients to the ICU were more likely to use critical care therapies overall (mechanical ventilation [from Q1 with lowest rate of ICU use to Q4 with highest rate 13%-16%], vasopressors/inotropes [17%-21%], intra-aortic balloon pumps [4%-7%], and pulmonary artery catheters [4%-5%]; P for trend < .05 in all comparisons)., Conclusions: Rates of ICU admission for patients with AMI vary substantially across hospitals and were not associated with differences in mortality, but were associated with greater use of critical care therapies. These findings suggest uncertainty about the appropriate use of this resource-intensive setting and a need to optimize ICU triage for patients who will truly benefit., (Copyright © 2015. Published by Elsevier Inc.)

To detect the expression of RKIP, E-cadherin and NF-kB p65 in esophageal squamous cell carcinoma (ESCC) and study their correlations. Steptavidin-peroxidase (S-P) method was employed to detect the expressions of RKIP, E-cadherin and NF-kB p65 in ESCC tissues from 77 cases and paracancerous tissues from 77 cases. The correlations between their expressions and clinicopathological indices and between the expressions of these proteins themselves were analyzed. The expressions of RKIP and E-cadherin in ESCC tissues were obviously lower than those in the paracancerous tissues (P<0.01); the expressions in ESCC tissues from cases with lymph node metastasis were lower than those from cases without lymph node metastasis (P<0.01); the expression of RKIP was positively correlated with the expression of E-cadherin in ESCC tissues (P<0.01). The expression of NF-kB p65 in ESCC tissues was correlated with clinical staging, lymph node metastasis and tumor differentiation (P<0.01); the expression of RKIP was negatively correlated with the expression of NF-kB p65 in ESCC tissues (P<0.05). Downregulation or depletion of RKIP was related to the onset and progression of ESCC, and facilitated the invasion and metastasis of ESCC by downregulating E-cadherin and upregulating NF-kB p65.

Background: The present study aimed to assess the role of C3435T polymorphism in drug-resistance in epilepsy by a meta-analysis., Material and Methods: Databases were obtained from the Cochrane Library, MEDLINE, EMBASE, PubMed, Science Direct database, CNKI, and Wanfang up to October 2014. All the case-control association studies evaluating the role of ABCB1 C3435T in pharmacoresistance to anti-epileptic drug (AED) were identified. RevMan 5.0 software was utilized to perform quantitative analyses in an allele model (C vs. T) and a genotype model (CC vs. CT+TT)., Results: From the 189 potential studies, we included 28 articles for the meta-analysis, including 30 independent case-control studies involving 4124 drug-resistant epileptic patients and 4480 epileptic patients for whom drug treatment was effective. We excluded 164 studies because of duplication, lack of genotype data, and non-clinical research. We found that C3435T polymorphism was not significantly associated with drug resistance in epilepsy, either in allele model (C vs. T: OR=1.07; 95%CI: 0.95-1.19) or in genotype model (CC vs. CT+TT: OR=1.05; 95%CI: 0.89-1.24, P=0.55). Subgroup analyses suggested that in Caucasian populations there are significant differences between resistance group (NR) and control group (R) in both allele model (C vs. T: OR=1.09; 95%CI: 1.00-1.18, P=0.05) and genotype model (CC vs. CT+TT: OR=1.20; 95%CI: 1.04-1.40, P=0.01). However, we did not find this association in Asian populations., Conclusions: We conclude that the ABCB1 C3435T polymorphism may be a genetic marker for drug resistance in epilepsy in Caucasian populations.

Objective: To characterize hospitals based on patterns of their combined financial and clinical outcomes for heart failure hospitalizations longitudinally., Data Source: Detailed cost and administrative data on hospitalizations for heart failure from 424 hospitals in the 2005-2011 Premier database., Study Design: Using a mixture modeling approach, we identified groups of hospitals with distinct joint trajectories of risk-standardized cost (RSC) per hospitalization and risk-standardized in-hospital mortality rate (RSMR), and assessed hospital characteristics associated with the distinct patterns using multinomial logistic regression., Principal Findings: During 2005-2011, mean hospital RSC decreased from $12,003 to $10,782, while mean hospital RSMR declined from 3.9 to 3.2 percent. We identified five distinct hospital patterns: highest cost and low mortality (3.2 percent of the hospitals), high cost and low mortality (20.4 percent), medium cost and low mortality (34.6 percent), medium cost and high mortality (6.2 percent), and low cost and low mortality (35.6 percent). Longer hospital stay and greater use of intensive care unit and surgical procedures were associated with phenotypes with higher costs or greater mortality., Conclusions: Hospitals vary substantially in the joint longitudinal patterns of cost and mortality, suggesting marked difference in value of care. Understanding determinants of the variation will inform strategies for improving the value of hospital care., (© Health Research and Educational Trust.)

Background: The Centers for Medicare & Medicaid Services publicly reports risk-standardized mortality rates (RSMRs) within 30-days of admission and, in 2013, risk-standardized unplanned readmission rates (RSRRs) within 30-days of discharge for patients hospitalized with acute myocardial infarction (AMI), heart failure (HF), and pneumonia. Current publicly reported data do not focus on variation in national results or annual changes., Objective: Describe U.S. hospital performance on AMI, HF, and pneumonia mortality and updated readmission measures to provide perspective on national performance variation., Design: To identify recent changes and variation in national hospital-level mortality and readmission for AMI, HF, and pneumonia, we performed cross-sectional panel analyses of national hospital performance on publicly reported measures., Participants: Fee-for-service Medicare and Veterans Health Administration beneficiaries, 65 years or older, hospitalized with principal discharge diagnoses of AMI, HF, or pneumonia between July 2009 and June 2012. RSMRs/RSRRs were calculated using hierarchical logistic models risk-adjusted for age, sex, comorbidities, and patients' clustering among hospitals., Results: Median (range) RSMRs for AMI, HF, and pneumonia were 15.1% (9.4-21.0%), 11.3% (6.4-17.9%), and 11.4% (6.5-24.5%), respectively. Median (range) RSRRs for AMI, HF, and pneumonia were 18.2% (14.4-24.3%), 22.9% (17.1-30.7%), and 17.5% (13.6-24.0%), respectively. Median RSMRs declined for AMI (15.5% in 2009-2010, 15.4% in 2010-2011, 14.7% in 2011-2012) and remained similar for HF (11.5% in 2009-2010, 11.9% in 2010-2011, 11.7% in 2011-2012) and pneumonia (11.8% in 2009-2010, 11.9% in 2010-2011, 11.6% in 2011-2012). Median hospital-level RSRRs declined: AMI (18.5% in 2009-2010, 18.5% in 2010-2011, 17.7% in 2011-2012), HF (23.3% in 2009-2010, 23.1% in 2010-2011, 22.5% in 2011-2012), and pneumonia (17.7% in 2009-2010, 17.6% in 2010-2011, 17.3% in 2011-2012)., Conclusions: We report the first national unplanned readmission results demonstrating declining rates for all three conditions between 2009-2012. Simultaneously, AMI mortality continued to decline, pneumonia mortality was stable, and HF mortality experienced a small increase.

IMPORTANCE Current guidelines allow substantial discretion in use of noninvasive cardiac imaging for patients without acute myocardial infarction (AMI) who are being evaluated for ischemia. Imaging use may affect downstream testing and outcomes. OBJECTIVE To characterize hospital variation in use of noninvasive cardiac imaging and the association of imaging use with downstream testing, interventions, and outcomes. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional study of hospitals using 2010 administrative data from Premier, Inc, including patients with suspected ischemia on initial evaluation who were seen in the emergency department, observation unit, or inpatient ward; received at least 1 cardiac biomarker test on day 0 or 1; and had a principal discharge diagnosis for a common cause of chest discomfort, a sign or symptom of cardiac ischemia, and/or a comorbidity associated with coronary disease. We excluded patients with AMI. MAIN OUTCOMES AND MEASURES At each hospital, the proportion of patients who received noninvasive imaging to identify cardiac ischemia and the subsequent rates of admission, coronary angiography, and revascularization procedures. RESULTS We identified 549,078 patients at 224 hospitals. The median (interquartile range) hospital noninvasive imaging rate was 19.8% (10.9%-27.7%); range, 0.2% to 55.7%. Median hospital imaging rates by quartile were Q1, 6.0%; Q2, 15.9%; Q3, 23.5%; Q4, 34.8%. Compared with Q1, Q4 hospitals had higher rates of admission (Q1, 32.1% vs Q4, 40.0%), downstream coronary angiogram (Q1, 1.2% vs Q4, 4.9%), and revascularization procedures (Q1, 0.5% vs Q4, 1.9%). Hospitals in Q4 had a lower yield of revascularization for noninvasive imaging (Q1, 7.6% vs Q4, 5.4%) and for angiograms (Q1, 41.2% vs Q4, 38.8%). P <.001 for all comparisons. Readmission rates to the same hospital for AMI within 2 months were not different by quartiles (P = .51). Approximately 23% of variation in imaging use was attributable to the behavior of individual hospitals. CONCLUSIONS AND RELEVANCE Hospitals vary in their use of noninvasive cardiac imaging in patients with suspected ischemia who do not have AMI. Hospitals with higher imaging rates did not have substantially different rates of therapeutic interventions or lower readmission rates for AMI but were more likely to admit patients and perform angiography.

Background: Prior claims analyses suggest that the use of intravenous inotropic therapy for patients hospitalized with heart failure varies substantially by hospital. Whether differences in the clinical characteristics of the patients explain observed differences in the use of inotropic therapy is not known., Methods and Results: We sought to characterize institutional variation in inotrope use among patients hospitalized with heart failure before and after accounting for clinical factors of patients. Hierarchical generalized linear regression models estimated risk-standardized hospital-level rates of inotrope use within 209 hospitals participating in Get With The Guidelines-Heart Failure (GWTG-HF) registry between 2005 and 2011. The association between risk-standardized rates of inotrope use and clinical outcomes was determined. Overall, an inotropic agent was administered in 7691 of 126 564 (6.1%) heart failure hospitalizations: dobutamine 43%, dopamine 24%, milrinone 17%, or a combination 16%. Patterns of inotrope use were stable during the 7-year study period. Use of inotropes varied significantly between hospitals even after accounting for patient and hospital characteristics (median risk-standardized hospital rate, 5.9%; interquartile range, 3.7%-8.6%; range, 1.3%-32.9%). After adjusting for case-mix and hospital structural differences, model intraclass correlation indicated that 21% of the observed variation in inotrope use was potentially attributable to random hospital effects (ie, institutional preferences). Hospitals with higher risk-standardized inotrope use had modestly longer risk-standardized length of stay (P=0.005) but had no difference in risk-standardized inpatient mortality (P=0.12)., Conclusions: Use of intravenous inotropic agents during hospitalization for heart failure varies significantly among US hospitals even after accounting for patient and hospital factors.

For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC) production process, a fault diagnosis strategy based on the self-organizing map (SOM) neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. The particle swarm optimization (PSO) algorithm with a new dynamical adjustment method of inertial weights is adopted to optimize the structural parameters of SOM neural network. The fault pattern classification of the polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the simulation experiments of fault diagnosis are conducted by combining with the industrial on-site historical data of the polymerization kettle and the simulation results show that the proposed PSO-SOM fault diagnosis strategy is effective.

For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix, and the shape characteristics based on the geometric theory of flotation froth images are extracted, respectively, as the input variables of the proposed soft-sensor model. Then the isometric mapping method is used to reduce the input dimension, the network size, and learning time of BP neural network. Finally, a shuffled cuckoo search algorithm is adopted to optimize the BP neural network soft-sensor model. Simulation results show that the model has better generalization results and prediction accuracy.

Background: Because relative value unit (RVU)-based costs vary across hospitals, it is difficult to use them to compare hospital utilization., Objective: To compare estimates of hospital utilization using RVU-based costs and standardized costs., Design: Retrospective cohort., Setting and Patients: Years 2009 to 2010 heart failure hospitalizations in a large, detailed hospital billing database that contains an itemized log of costs incurred during hospitalization., Intervention: We assigned every item in the database with a standardized cost that was consistent for that item across all hospitals., Measurements: Standardized costs of hospitalization versus RVU-based costs of hospitalization., Results: We identified 234 hospitals with 165,647 heart failure hospitalizations. We observed variation in the RVU-based cost for a uniform "basket of goods" (10th percentile cost $1,552; 90th percentile cost of $3,967). The interquartile ratio (Q75/Q25) of the RVU-based costs of a hospitalization was 1.35 but fell to 1.26 after costs were standardized, suggesting that the use of standardized costs can reduce the "noise" due to differences in overhead and other fixed costs. Forty-six (20%) hospitals had reported costs of hospitalizations exceeding standardized costs (indicating that reported costs inflated apparent utilization); 42 hospitals (17%) had reported costs that were less than standardized costs (indicating that reported costs underestimated utilization)., Conclusions: Standardized costs are a novel method for comparing utilization across hospitals and reduce variation observed with RVU-based costs. They have the potential to help hospitals understand how they use resources compared to their peers and will facilitate research comparing the effectiveness of higher and lower utilization., (© 2013 Society of Hospital Medicine.)

Aim: This study aimed to investigate the factors associated with the health behavior of hypertensive elderly patients., Methods: This cross-sectional survey used a general data scale, a health conception scale, a scale for self-rated abilities for health practice, and health-promoting lifestyle profiles to investigate the health behavior of hypertensive elderly patients from clinical check-up to hospitalization., Results: The health behavior score of hypertensive patients was 72.25 ± 16.66, and 23.8 % of the patients had high scores. The health-promotion score was positively correlated with those of health conception, self-efficacy, and education level, but negatively correlated with that of unhealthy habits (P < 0.05)., Conclusions: Health practitioners should promote the health conception, enhance the self-efficacy, and improve the health behavior of hypertensive elderly patients.

Objective: To investigate the molecular mechanisms underlying the treatment of inflammatory bowel disease (IBD) by Pulsatilla decoction., Methods: 84 BALB/c mice were randomly divided into ethanol control group, model group, SASP group, Pulsatilla decoction group (further divided into low, middle and high dose group) and zVAD group (n = 12). Intragastric and celiac drug administration were used in each group respectively. The expression of NLRP3, ASC, Caspase-1, IL-18 and IL-1beta in the colons were detected by fluorescence quantitative RT-PCR, Elisa and immunohistochemistry after treatment respectively., Results: Compared with the model group, SASP group, middle and high dose group could treat IBD effectively (P < 0.01), while this effect was restrained in zVAD group (P < 0.05). In the meantime, middle and high dose group could effectively raise the expression of NLRP3, ASC, Caspase-1, IL-18 and IL-1beta in the colons (P < 0.05), while this effect was also inhibited in zVAD group (P < 0.05)., Conclusion: Pulsatilla decoction is likely to exert their therapeutic effect by activating NLRP3 inflammasome which further promote the formation of the corresponding inflammation factors such as 1L-18 and IL-1beta.

Objective: To investigate the clinicopathological characteristics, histological diagnosis, immunohistochemistry and prognosis of cervical glassy cell carcinoma (GCC)., Methods: The clinical characteristics, cytology, histology and immunohistochemistry were analyzed in 5 cases of GCC., Results: The average age of the five patients was 34.4 years (31 - 41 years). Abnormal vaginal bleeding and/or watery discharge were clinical presentations. One case was complicated with pregnancy and another one had a seven-year history of using contraceptives. All patients had an obvious mass in the cervix. Characteristic morphological features of GCC were present in 2 cases. Morphologically, the tumors consisted of clusters of tumor cells with distinct cell bounders, a large amount of eosinophilic granules in the cytoplasm imparting ground glass appearance, and thin nuclear membrane and prominent nucleoli. Nuclear enlargement and multinucleation were frequently noted. Mitosis and apoptosis were common. Numerous eosinophils and plasma cells were present in the stroma. Immunohistochemically, GCC expressed markers for both squamous cell carcinoma (p63 and CK34βE12) and adenocarcinoma (CAM5.2, MUC1, MUC2 and CEA). Ki-67 proliferation index was high (≥ 70%). All the five patients were treated with radical hysterectomy, followed by radiation and chemotherapy. The tumor-free survival time ranged from 25 days to 33 months., Conclusions: GCC is a distinct variant of adenosquamous carcinoma of the cervix with high proliferation index and expression of markers of both squamous cell carcinoma and adenocarcinoma. The tumor has characteristic cytological and histological features.

Purpose: To investigate the clinicopathologic significance and predictive value of Bmi-1 expression in patients with colon cancer., Methods: Bmi-1 expression was assessed by immunohistochemistry, PCR, and western blotting in specimens from 203 patients and by immunohistochemistry in 66 specimens of lymph node metastasis (LNM)., Results: Positive staining of Bmi-1 occurred in 7.9% (16/203), 66.5% (135/203), and 86.4% (57/66) of specimens from normal tissue, colon cancer, and LNM, respectively. Staining was significantly correlated with clinical stage, depth of invasion, nodal involvement, distant metastasis, and Ki67 level. Bmi-1 was upregulated at the transcriptional and translational levels. Patients with Bmi-1-positive localized tumors had a much lower 5-year disease-free survival (relative risk 2.919, P < 0.0001) and overall survival (relative risk 5.056, P < 0.0001). Bmi-1 immunoreactivity emerged as an independent prognostic factor in the multivariate analysis., Conclusions: We have shown that expression of Bmi-1 was elevated in colon cancer and might serve as an independent prognostic marker.

Objective: To investigate the roles of surviving and caspase-3 in the development of oral cancer., Methods: Archival tissue sections of 17 oral squamous cell carcinoma (OSCC), 28 oral leukoplakia with dysplasia, 10 normal oral mucosa were obtained from Capital Medical University School of Stomatology for immunohistochemical staining of markers of survivin and caspase-3. The cell apoptosis was detected with terminal deoxynucleotidyl transferase-mediated nucleotide shift enzyme (TdT) mediated d-UTP end labeling (TUNEL). Positively stained cells were counted and analyzed statistically to determine potential relationship between survivin, caspase-3 and cell apoptosis., Results: The expression of survivin was faint or negative in normal epithelial cells. The average positive rate of survivin was (1.05 ± 1.21)% in control group and (21.89 ± 10.45)% in OSCC. Caspase-3 was expressed in all the normal mucosa,but it obviously down-regulated in dysplasia and OSCC. The apoptosis index (AI) decreased from (0.89 ± 0.46)% in normal mucosa to (0.21 ± 0.12)% in OSCC., Conclusions: Both survivin and caspase-3 are associated with carcinogenesis of the oral mucosa. Survivin may restrain cell apoptosis by inhibiting caspase-3.

The paper is aimed to establish an artificial neural network (ANN) for predicting mycophenolic acid (MPA) area under the plasma concentration-time curve (AUC) in renal transplantation recipients. 64 Chinese renal transplantation recipients receiving mycophenolate mofetil (MMF) were investigated. 10 timed samples were drawn at different days after transplantation. Plasma MPA concentration was determined by HPLC method and area under curve over the period of 0 to 12 h (AUC(0-12 h)) was calculated using the linear trapezoidal rule. ANN was established after network parameters were optimized using momentum method in combination with genetic algorithm. Furthermore, the predictive performance of ANN was compared with that of multiple linear regression (MLR). When using plasma MPA concentration of 0, 0.5, 2 h after MMF administration to predict MPA AUC(0-12 h), mean prediction error and mean absolute prediction error were -1.53% and 9.12%, respectively. Accuracy and precision of prediction by ANN were superior to that of MLR prediction, and similar results could be found when using plasma MPA concentration of 0, 0.5 h to predict MPA AUC(0-12h). The accuracy and precision of ANN prediction were superior to that of MLR prediction, and ANN can be used to predict MPA AUC(0-12 h).

The study was aimed to investigate the curative effects and adverse effects of amifostine in the treatment of patients with myelodysplastic syndrome (MDS). Amifostine (AMF) was used alone (4/12) or combined with recombinant human erythropoietin (rh-EPO) (8/12) in 12 MDS patients. The therapeutic regimen was adopted with AMF 0.4 g/day for 5 days, then took a break of 2 days and then went on for 3 weeks consecutively, that was reputed as one treatment cycle. rh-EPO 6 000 U was used for 3 days per week. The results showed that 12 patients all attained hematological improvement in peripheral blood. 11 cases showed major effective response rate (91.7%), while 1 case showed minor response rate (8.3%). The effective response rate of hemoglobin, leukocytes and platelets was 100%, 75% and 58.3% respectively. The intervals of red cell transfusions (RCT) in 2 cases living on red cell transfusion before AMF treatment were prolonged after AMF treatments, and the amount of each RCT was decreased obviously. The side effect was usually discomfort of digestive system, but all patients can endure. In conclusion, Amifostine is a potential drug in the treatment of MDS patients with safety especially to those elder patients who often suffered from other multiple organ disfunctions, and the curative effect will be improved by more treatment cycles.

Background: Cerebral ischemia is a significant clinical problem, and cerebral ischemia usually causes neuron injury such as apoptosis in various brain areas, including hippocampus. Cysteinyl aspartate-specific protease (Caspases) are fundamental factors of apoptotic mechanism. Caspase-3 inhibitors show effect in attenuating brain injury after ischemia. But all the results were from animal models in research laboratories. This study aimed at investigating the correlation between the change of ischemic neuronal injury and Caspase-3 post-ischemia in human hippocampus., Methods: We selected and systematized 48 post-mortem specimens from 48 patients, who died of cerebral infarction. Morphological change was firstly analyzed by observing hematoxyline/eosin-staining hippocampal sections. The expression of Caspase-3 was investigated using the methods of in situ hybridization and immunohistochemistry. Terminal deoxynucleotidyl transferase-mediated 2'-deoxyuridine 5'-triphosphate-biotin nick-end labeling (TUNEL) method was used to clarify the involvement of Caspase-3 in neuron death. The loss of MAP 2 (MAP-2) was applied to judging the damaged area and degree of neuronal injury caused by ischemia., Results: In the CA1 sector of hippocampus, Caspase-3 immunostaining modestly increased at 8 hours [8.05/high-power field (hpf)], dramatically increased at 24 hours (24.85/hpf), decreased somewhat after 72 hours. Caspase-3 mRNA was detectable at 4 hours (6.75/hpf), reached a maximum at 16 hours (17.60/hpf), faded at 72 hours. TUNEL-positive cells were detectable at 24 hours (10.76/hpf), markedly increased at 48 - 72 hours. The loss of MAP-2 was obviously detected at 4 hours, progressed significantly between 24 and 72 hours; MAP-2 immunoreactivity was barely detectable at 72 hours. Before 72 hours, the Caspase-3 evolution was related with the upregulation of TUNEL and the loss of MAP-2. The positive correlation between Caspase-3 mRNA and TUNEL was significant at the 0.05 level (correlation coefficient was 0.721); the negative correlation between Caspase-3 mRNA and MAP-2 was significant at the 0.05 level (correlation coefficient is 0.857). In the early stage (before 72 hours), the staining of Caspase-3 mRNA and immunohistochemistry was predominantly present in cytoplasm; the staining of TUNEL was predominantly localized in nucleus. At 4 - 16 hours, most neurons in hippocampal CA1 areas had relatively normal morphology; at 24 - 48 hours, neurons showed apoptotic morphology; at 72 hours, most cells showed significantly pathological morphology., Conclusions: There exist a time-dependent evolution of neuronal damage after hippocampal ischemia in human brain, which was characterized by its close correspondence to Caspase-3.

Objective: To study the expression of Ki-67 and the changes of MVD and apoptosis in benign lymphoadenosis of oral mucosa (BLOM)., Methods: The expression of Ki-67, CD34 and apoptosis were evaluated by SP immunohistochemical staining in 15 BLOM, 9 BLOM with dysplasia, 15 oral squamous cell carcinoma (OSCC)., Results: The expression of Ki-67 in BOLM with dysplasia and OSCC was significantly higher than that of BLOM without dysplasia and normal oral mucosa (P < 0.05). The MVD in all BLOM and OSCC was significantly higher than that in normal mucosa (P < 0.05). Apoptosis in BLOM was higher than in normal mucosa and OSCC (P < 0.05)., Conclusions: The expression of Ki-67 and MVD in BLOM with dysplasia were between normal oral mucosa and oral carcinoma. The occurrence of apoptosis in BLOM was significantly higher than in normal oral mucosa. The results suggest that BLOM had the potentiality of malignant transformation.

Previous investigations have shown that approximately 35% of the 90 tumors analyzed to date contain mutations within the DNA polymerasebeta (pol beta) gene. The existence of pol beta mutations in a substantial fraction of human tumors studied suggests a link between DNA pol beta and cancer. A DNA pol beta variant, in which Lys-289 has been altered to Met, was identified previously in a colorectal carcinoma. The K289M protein was expressed in mouse L cells containing the lambda cII mutational target. The lambda DNA was packaged and used to infect bacterial cells to obtain the spontaneous mutation frequency. We found that expression of K289M in the mouse cells resulted in a 2.5-fold increase in the mutation frequency. What was most interesting was that expression of K289M in these cells resulted in a 16-fold increase in the frequency of C to G or G to C base substitutions at a specific site within the cII target. By using this cII target sequence, kinetic analysis of the purified K289M protein revealed that it was able to misincorporate dCTP opposite template C and dGTP opposite template G with significantly higher efficiency than the wild-type pol beta protein. We provide evidence that misincorporation of nucleotides by K289M results from altered positioning of the DNA within the active site of the enzyme. Our data are consistent with the interpretation that misincorporation of nucleotides resulting from altered DNA positioning by the K289M protein has the potential to result in tumorigenesis or neoplastic progression.

Three proteins secreted from Mycobacterium tuberculosis, Ag85B, ESAT-6 and MPT63 were selected as antigens for making combined DNA vaccine by immunizing mice. The immune response induced by the vaccine and its protective efficacy were studied. It was demonstrated that when mice were immunized with the combined DNA vaccine, the titer of antibody for Ag85B in serum increased to more than 10(5), but the titers of ESAT-6 and MPT63 specific antibodies were undetectable. After the final immunization, the level of gamma specific for Ag85B, ESAT-6 and MPT63 reached (17.0+/-7.0) u/ml, (6.0+/-0.8) u/ml and (11.9+/-8.0) u/ml, respectively. Mice, that were inoculated with the empty eukaryotic expression vector pJW4303 DNA, produced negligible amounts of antigen-specific INF-gamma. The combined DNA vaccine resulted also in significantly reduced amount of bacteria in the lungs of experimental mice. Microphotographs showed clearly that these lungs were better protected against Mycobacterium tuberculosis challenge than control mice. The combined DNA vaccine reported in this work shed new lights on the prophylactic protection against tuberculosis.