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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.

This cohort study examines mortality data from Texas, a racially and ethnically diverse state, to better understand excess mortality among adults aged 25 to 44 years during early months of the COVID-19 pandemic.

ImportanceCOVID-19 case fatality and hospitalization rates, calculated using the number of confirmed cases of COVID-19, have been described widely in the literature. However, the number of infections confirmed by testing underestimates the total infections as it is biased based on the availability of testing and because asymptomatic individuals may remain untested. The infection fatality rate (IFR) and infection hospitalization rate (IHR), calculated using the estimated total infections based on a representative sample of a population, is a better metric to assess the actual toll of the disease.ObjectiveTo determine the IHR and IFR for COVID-19 using the statewide SARS-CoV-2 seroprevalence estimates for the non-congregate population in Connecticut.DesignCross-sectional.SettingAdults residing in a non-congregate setting in Connecticut between March 1 and June 1, 2020.ParticipantsIndividuals aged 18 years or above.ExposureEstimated number of adults with SARS-CoV-2 antibodies.Main Outcome and MeasuresCOVID-19-related hospitalizations and deaths among adults residing in a non-congregate setting in Connecticut between March 1 and June 1, 2020.ResultsOf the 2.8 million individuals residing in the non-congregate settings in Connecticut through June 2020, 113,515 (90% CI 56,758–170,273) individuals had SARS-CoV-2 antibodies. There were a total of 9425 COVID-19-related hospitalizations and 4071 COVID-19-related deaths in Connecticut between March 1 and June 1, 2020, of which 7792 hospitalizations and 1079 deaths occurred among the non-congregate population. The overall COVID-19 IHR and IFR was 6.86% (90% CI, 4.58%–13.72%) and 0.95% (90% CI, 0.63%–1.90%) among the non-congregate population. Older individuals, men, non-Hispanic Black individuals and those belonging to New Haven and Litchfield counties had a higher burden of hospitalization and deaths, compared with younger individuals, women, non-Hispanic White or Hispanic individuals, and those belonging to New London county, respectively.Conclusion and RelevanceUsing representative seroprevalence estimates, the overall COVID-19 IHR and IFR were estimated to be 6.86% and 0.95% among the non-congregate population in Connecticut. Accurate estimation of IHR and IFR among community residents is important to guide public health strategies during an infectious disease outbreak.

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.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.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.A wide range of demographic, clinical, and psychosocial risk factors.Odds ratios (ORs) and population attributable fractions (PAF) for first AMI associated with demographic, clinical, and psychosocial risk factors.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.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.

Importance: A seroprevalence study can estimate the percentage of people with SARS-CoV-2 antibodies in the general population. Most existing reports have used a convenience sample, which may bias their estimates. Objective: To estimate the seroprevalence of antibodies against SARS-CoV-2 based on a random sample of adults living in Connecticut between March 1 and June 1, 2020. Design: Cross-sectional. Setting: We sought a representative sample of Connecticut residents who completed a survey between June 4 and June 23, 2020 and underwent serology testing for SARS-CoV-2-specific IgG antibodies between June 10 and July 6, 2020. Participants: 505 respondents, aged ≥18 years, residing in non-congregate settings who completed both the survey and the serology test. Main outcomes and measures: We estimated the seroprevalence of SARS-CoV-2-specific IgG antibodies among the overall population and across pre-specified subgroups. We also assessed the prevalence of symptomatic illness, risk factors for virus exposure, and self-reported adherence to risk mitigation behaviors among this population. Results: Of the 505 respondents (mean age 50 [±17] years; 54% women; 76% non-Hispanic White individuals) included, 32% reported having at least 1 symptom suggestive of COVID-19 since March 1, 2020. Overall, 18 respondents had SARS-CoV-2-specific antibodies, resulting in the state-level weighted seroprevalence of 3.1 (90% CI 1.4-4.8). Individuals who were asymptomatic had significantly lower seroprevalence (0.6% [90% CI 0.0-1.5]) compared with the overall state estimate, while those who reported having had ≥1 and ≥2 symptoms had a seroprevalence of 8.0% (90% CI 3.1-12.9) and 13.0% (90% CI 3.5-22.5), respectively. All 9 of the respondents who reported previously having a positive coronavirus test were positive for SARS-CoV-2-specific IgG antibodies. Nearly two-third of respondents reported having avoided public places (74%) and small gatherings of family or friends (75%), and 97% reported wearing a mask outside their home, at least part of the time. Conclusions and relevance: These estimates indicate that most people in Connecticut do not have detectable levels of antibodies against SARS-CoV-2. There is a need for continued adherence to risk mitigation behaviors among Connecticut residents, to prevent resurgence of COVID-19 in this region.

Background: Although increased age is associated with higher systolic blood pressure (SBP) in general, there may be variation across individuals in how SBP changes over time. The goal of this paper is to identify heterogeneity in SBP trajectories among young adults with similar initial values and identify personal characteristics associated with different trajectory patterns. This may have important implications for prevention and prognosis. Methods: A cohort of 12,468 individuals aged 18–35 years in the Qingdao Port Cardiovascular Health Study in China was followed yearly during 2000–2011. Individuals were categorized into three strata according to their baseline SBP: ≤110 mmHg, 111–130 mmHg, and >130 mmHg. Within each stratum, group-based trajectory analyses were conducted to identify distinct SBP trajectory patterns, and their association with sociodemographic and baseline health characteristics was assessed by ordinal logistic regression. Results: Five distinct groups of individuals exhibiting divergent patterns of increasing, stable or decreasing SBP trends were identified within each stratum. This is a first report to identify a subgroup with decreasing trend in SBP. Individuals with more advanced age, having less than high school education, family history of cardiovascular diseases, greater body mass index, greater waist circumference, and hyperlipidemia at baseline were more likely to experience trajectories of higher SBP within each stratum. Conclusions: The diverging trajectories among young adults with similar initial SBP highlight the need for prevention and feasibility of effective blood pressure control, while the identified risk factors may inform targeted interventions.

Background Measurement of cancer-related fatigue and nutrition in the same colorectal cancer patient group using fast-track surgery has never been examined previously. The association between fatigue and nutritional status in the same patient group is thus worthwhile to be investigated. Objective The aim of this study was to evaluate the relationship between fatigue and nutrition risk factors in colorectal cancer patients with fast-track surgery. Methods This is a single-arm, observational study. Seventy eligible postoperative patients with colorectal cancer fast-track surgery were enrolled in this study. Patients completed the Cancer Fatigue Scale and the Patient-Generated Subjective Global Assessment (PG-SGA) besides routine perioperative laboratory examination. Results In this study, all patients were found to have cancer-related fatigue; 20% of the patients had severe fatigue. Furthermore, 94.29% of the patients were malnourished according to the PG-SGA score; the average was 15.585.18. Fatigue severity was significantly, positively correlated with nutrition status. White blood cells and serum calcium were significantly, positively related to both Cancer Fatigue Scale and PG-SGA scores. Conclusion Fatigue and malnutrition commonly exist in patients with colorectal cancer experiencing fast-track surgery. Fatigue may reflect the nutritional status in this group of patients. Implications for practice Clinical nursing staff need to evaluate patients' fatigue status and nutritional status to provide the suitable clinical intervention when needed.

This comparative effectiveness research study assesses whether using present on admission codes and single, rather than grouped, diagnostic codes can enhance Centers for Medicare & Medicaid (CMS) models to predict payment for hospitalization for acute myocardial infarction, heart failure, and pneumonia., Key Points Question Does leveraging present on admission codes and using single, rather than grouped, diagnostic codes enhance risk models for acute myocardial infarction, heart failure, and pneumonia payment measures? Findings In this comparative effectiveness research study of risk models on 1 667 983 patients with 1 943 049 Medicare fee-for-service hospitalizations, use of present on admission codes and single diagnosis codes and separation of index admission codes from codes in the previous year improved models predicting payment that were compared with models based on Centers for Medicare & Medicaid Services grouped codes. The patient-level pseudo R2 improved from 0.077 to 0.129 for acute myocardial infarction, from 0.042 to 0.129 for heart failure, and from 0.114 to 0.237 for pneumonia. Meaning Changing candidate variables from the current standard improved models predicting payments, which has implications for research, benchmarking, public reporting, and calculations for population-based programs., 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.

Background: Despite the rapid growth in the incidence of acute myocardial infarction (AMI) in China, there is limited information about patients' experiences after AMI hospitalization, especially on long-term adverse events and patient-reported outcomes (PROs). Methods: The China Patient-centered Evaluative Assessment of Cardiac Events (PEACE)-Prospective AMI Study will enroll 4000 consecutive AMI patients from 53 diverse hospitals across China and follow them longitudinally for 12 months to document their treatment, recovery, and outcomes. Details of patients' medical history, treatment, and in-hospital outcomes are abstracted from medical charts. Comprehensive baseline interviews are being conducted to characterize patient demographics, risk factors, presentation, and healthcare utilization. As part of these interviews, validated instruments are administered to measure PROs, including quality of life, symptoms, mood, cognition, and sexual activity. Follow-up interviews, measuring PROs, medication adherence, risk factor control, and collecting hospitalization events are conducted at 1, 6, and 12 months after discharge. Supporting documents for potential outcomes are collected for adjudication by clinicians at the National Coordinating Center. Blood and urine samples are also obtained at baseline, 1- and 12-month follow-up. In addition, we are conducting a survey of participating hospitals to characterize their organizational characteristics. Conclusion: The China PEACE-Prospective AMI study will be uniquely positioned to generate new information regarding patient's experiences and outcomes after AMI in China and serve as a foundation for quality improvement activities.

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., In a retrospective cohort study, Harlan M. Krumholz and colleagues use machine learning techniques in an effort to improve identification of PCI patients who may benefit from AKI risk-mitigation strategies., Author summary Why was this study done? Accurately estimating the risk of developing acute kidney injury (AKI) is important to determine revascularization strategies and inform peri- and postprocedural care. The current AKI risk prediction model was developed by employing prior clinical knowledge to choose and transform candidate variables and applying regression techniques. It is unknown whether and how machine learning techniques could improve predictive performance from the current AKI risk model. What did the researchers do and find? We used data from 947,091 percutaneous coronary intervention (PCI) procedures from the National Cardiovascular Data Registry (NCDR) CathPCI registry to develop AKI prediction models, the same data from which the current AKI risk model was derived. Temporal validation was performed on a more contemporary cohort of 970,869 PCIs from the NCDR CathPCI registry. We compared the performance of the current AKI risk model with a series of new AKI risk models, which were derived using different regression and machine learning techniques. An AKI risk model derived from machine learning techniques had significantly better discrimination, calibration, and risk stratification than the current AKI risk model in both the internal test set and temporal validation set. What do these findings mean? The demonstrated improvement in predictive power supports the potential of machine learning techniques for improving risk prediction modeling. The improved prediction for AKI suggests great potential of the model to improve targeting of risk-mitigation treatment and quality assessment of cardiovascular care. Future studies need to assess the feasibility of integrating the machine learning model into clinical care and evaluate the benefit of the model for patients at the point of care.

This study sought to determine the use of intravenous fluids in the early care of patients with acute decompensated heart failure (HF) who are treated with loop diuretics.Intravenous fluids are routinely provided to many hospitalized patients.We conducted a retrospective cohort study of patients admitted with HF to 346 hospitals from 2009 to 2010. We assessed the use of intravenous fluids during the first 2 days of hospitalization. We determined the frequency of adverse in-hospital outcomes. We assessed variation in the use of intravenous fluids across hospitals and patient groups.Among 131,430 hospitalizations for HF, 13,806 (11%) were in patients treated with intravenous fluids during the first 2 days. The median volume of administered fluid was 1,000 ml (interquartile range: 1,000 to 2,000 ml), and the most commonly used fluids were normal saline (80%) and half-normal saline (12%). Demographic characteristics and comorbidities were similar in hospitalizations in which patients did and did not receive fluids. Patients who were treated with intravenous fluids had higher rates of subsequent critical care admission (5.7% vs. 3.8%; p 0.0001), intubation (1.4% vs. 1.0%; p = 0.0012), renal replacement therapy (0.6% vs. 0.3%; p 0.0001), and hospital death (3.3% vs. 1.8%; p 0.0001) compared with those who received only diuretics. The proportion of hospitalizations that used fluid treatment varied widely across hospitals (range: 0% to 71%; median: 12.5%).Many patients who are hospitalized with HF and receive diuretics also receive intravenous fluids during their early inpatient care, and the proportion varies among hospitals. Such practice is associated with worse outcomes and warrants further investigation.

Background SPRINT (Systolic Blood Pressure Intervention Trial) and the ACCORD (Action to Control Cardiovascular Risk in Diabetes) blood pressure trial used similar interventions but produced discordant results. We investigated whether differences in systolic blood pressure ( SBP ) response contributed to the discordant trial results. Methods and Results We evaluated the distributions of SBP response during the first year for the intensive and standard treatment groups of SPRINT and ACCORD using growth mixture models. We assessed whether significant differences existed between trials in the distributions of SBP achieved at 1 year and the treatment‐independent relationships of achieved SBP with risks of primary outcomes defined in each trial, heart failure, stroke, and all‐cause death. We examined whether visit‐to‐visit variability was associated with heterogeneous treatment effects. Among the included 9027 SPRINT and 4575 ACCORD participants, the difference in mean SBP achieved between treatment groups was 15.7 mm Hg in SPRINT and 14.2 mm Hg in ACCORD , but SPRINT had significantly less between‐group overlap in the achieved SBP (standard deviations of intensive and standard groups, respectively: 6.7 and 5.9 mm Hg in SPRINT versus 8.8 and 8.2 mm Hg in ACCORD ; P SBP and outcomes was consistent across trials except for stroke and all‐cause death. Higher visit‐to‐visit variability was more common in SPRINT but without treatment‐effect heterogeneity. Conclusions SPRINT and ACCORD had different degrees of separation in achieved SBP between treatment groups, even as they had similar mean differences. The greater between‐group overlap of achieved SBP may have contributed to the discordant trial results.

Randomized trials of hypertension have seldom examined heterogeneity in response to treatments over time and the implications for cardiovascular outcomes. Understanding this heterogeneity, however, is a necessary step toward personalizing antihypertensive therapy. We applied trajectory-based modeling to data on 39 763 study participants of the ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) to identify distinct patterns of systolic blood pressure (SBP) response to randomized medications during the first 6 months of the trial. Two trajectory patterns were identified: immediate responders (85.5%), on average, had a decreasing SBP, whereas nonimmediate responders (14.5%), on average, had an initially increasing SBP followed by a decrease. Compared with those randomized to chlorthalidone, participants randomized to amlodipine (odds ratio, 1.20; 95% confidence interval [CI], 1.10–1.31), lisinopril (odds ratio, 1.88; 95% CI, 1.73–2.03), and doxazosin (odds ratio, 1.65; 95% CI, 1.52–1.78) had higher adjusted odds ratios associated with being a nonimmediate responder (versus immediate responder). After multivariable adjustment, nonimmediate responders had a higher hazard ratio of stroke (hazard ratio, 1.49; 95% CI, 1.21–1.84), combined cardiovascular disease (hazard ratio, 1.21; 95% CI, 1.11–1.31), and heart failure (hazard ratio, 1.48; 95% CI, 1.24–1.78) during follow-up between 6 months and 2 years. The SBP response trajectories provided superior discrimination for predicting downstream adverse cardiovascular events than classification based on difference in SBP between the first 2 measurements, SBP at 6 months, and average SBP during the first 6 months. Our findings demonstrate heterogeneity in response to antihypertensive therapies and show that chlorthalidone is associated with more favorable initial response than the other medications.

Identifying temporal variation in hospitalization rates may provide insights about disease patterns and thereby inform research, policy, and clinical care. However, the majority of medical conditions have not been studied for their potential seasonal variation. The objective of this study was to apply a data-driven approach to characterize temporal variation in condition-specific hospitalizations. Using a dataset of 34 million inpatient discharges gathered from hospitals in New York State from 2008–2011, we grouped all discharges into 263 clinical conditions based on the principal discharge diagnosis using Clinical Classification Software in order to mitigate the limitation that administrative claims data reflect clinical conditions to varying specificity. After applying Seasonal-Trend Decomposition by LOESS, we estimated the periodicity of the seasonal component using spectral analysis and applied harmonic regression to calculate the amplitude and phase of the condition’s seasonal utilization pattern. We also introduced four new indices of temporal variation: mean oscillation width, seasonal coefficient, trend coefficient, and linearity of the trend. Finally, K-means clustering was used to group conditions across these four indices to identify common temporal variation patterns. Of all 263 clinical conditions considered, 164 demonstrated statistically significant seasonality. Notably, we identified conditions for which seasonal variation has not been previously described such as ovarian cancer, tuberculosis, and schizophrenia. Clustering analysis yielded three distinct groups of conditions based on multiple measures of seasonal variation. Our study was limited to New York State and results may not directly apply to other regions with distinct climates and health burden. A substantial proportion of medical conditions, larger than previously described, exhibit seasonal variation in hospital utilization. Moreover, the application of clustering tools yields groups of clinically heterogeneous conditions with similar seasonal phenotypes. Further investigation is necessary to uncover common etiologies underlying these shared seasonal phenotypes.

To investigate the utility of frozen section of uterine curetting in excluding the possibility of ectopic pregnancy (EP).A retrospective analysis of 715 curetting records in the present hospital from July 1999 to May 2009 was obtained. All specimens were processed routinely with frozen section and paraffin section.Of 715 cases, frozen section analyses were discordant in 33 cases (4.6%), including 32 cases under-diagnosed, and one case over-diagnosed, compared with the final diagnoses. Frozen section had a sensitivity of 92.6%, specificity of 99.6%, and frozen section accuracy rate of 95.4%.Frozen section is a useful and rapid method to differentiate EP from intrauterine pregnancy.

Background: Dynamic changes of cancer-related fatigue (CRF) among hospitalized patients with colorectal cancer were determined. Materials and Methods: This longitudinal, descriptive study involved 96 hospitalized patients with colorectal cancer, all recruited from a tertiary general hospital in Guangzhou, China. Patients completed questionnaires three times to assess the degree of fatigue, and measurement points were within one week of admission, at 2 to 3 days after surgery and 3 weeks after surgery. Results: Significant differences among the three measurement points (p

Key Points Question What is the association of contrast volume used during percutaneous coronary intervention with the risk of acute kidney injury? Findings In this prognostic study of nearly 3 million adults undergoing percutaneous coronary intervention, a predictive model for the association of contrast volume with the risk of acute kidney injury was developed and validated. The association was nonlinear along the spectrum of contrast volume and varied according to patient baseline risk. Meaning This model could support personalized approaches that consider the complex association between contrast volume and the risk of acute kidney injury when determining contrast dosing during interventional procedures., This prognostic study quantifies the association of contrast volume during percutaneous coronary intervention with the risk of acute kidney injury, accounting for the possibility of nonlinearity and heterogeneity among different baseline risks., 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

This comparative effectiveness study examines current US Centers for Medicare & Medicaid Services 30-day mortality risk models vs novel risk models for acute myocardial infarction, heart failure, and pneumonia hospitalizations., Key Points Question Could present on admission indicators and ungrouped diagnostic codes enhance risk models for acute myocardial infarction, heart failure, and pneumonia mortality measures and improve discrimination of hospital-level performance? Findings In this comparative effectiveness study including all Medicare fee-for-service beneficiaries hospitalized for acute myocardial infarction, heart failure, or pneumonia at acute care hospitals, incorporating present on admission coding and ungrouped historical and index admission International Classification of Diseases, Ninth Revision, Clinical Modification codes was associated with greater discrimination in patient-level and hospital-level 30-day mortality risk models. Meaning Changes incurring no additional cost could enhance the risk adjustment for mortality and increase discrimination of hospital-level performance., 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.

Importance Studies of public hospitals have reported increasing incidence of emergency department (ED) transfers of uninsured patients for hospitalization, which is perceived to be associated with financial incentives. Objective To examine the differences in risk-adjusted transfer and discharge rates by patient insurance status among hospitals capable of providing critical care. Design, Setting, and Participants A cross-sectional analysis of the 2015 National Emergency Department Sample was conducted, including visits between January 2015 and December 2015. Adult ED visits throughout 2015 (n = 215 028) for the 3 common medical conditions of pneumonia, chronic obstructive pulmonary disease, and asthma, at hospitals with intensive care capabilities were included. Only hospitals with advanced critical care capabilities for pulmonary care were included. Main Outcomes and Measures The primary outcomes were patient-level and hospital-level risk-adjusted ED discharges, ED transfers, and hospital admissions. Adjusted odds of discharge or transfer compared with admission among uninsured patients, Medicaid and Medicare beneficiaries, and privately insured patients are reported. Hospital ownership status was used for the secondary analysis. Results Of the 30 542 691 ED visits to 953 hospitals included in the 2015 National Emergency Department Sample, 215 028 visits (0.7%) were for acute pulmonary diseases to 160 intensive care–capable hospitals. These visits were made by patients with a median (interquartile range [IQR]) age of 55 (40-71) years and who were predominantly female (124 931 [58.1%]). Substantial variation in unadjusted and risk-standardized ED discharge, ED transfer, and hospital admission rates was found across EDs. Compared with privately insured patients, uninsured patients were more likely to be discharged (odds ratio [OR], 1.66; 95% CI, 1.57-1.76) and transferred (adjusted OR [aOR], 2.41; 95% CI, 2.08-2.79). Medicaid beneficiaries had comparable odds of discharge (aOR, 1.00; 95% CI, 0.97-1.04) but higher odds of transfer (aOR, 1.19; 95% CI, 1.05-1.33). Conclusions and Relevance After accounting for hospital critical care capability and patient case mix, the study found that uninsured patients and Medicaid beneficiaries with common medical conditions appeared to have higher odds of interhospital transfer.

This study aimed to investigate the factors associated with the health behavior of hypertensive elderly patients. 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. 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

Objectives To determine how often hospitalized older adults principally diagnosed with pneumonia, chronic obstructive pulmonary disease (COPD), or heart failure (HF) are concurrently treated for two or more of these acute cardiopulmonary conditions. Design Retrospective cohort study. Setting 368 U.S. hospitals in the Premier research database. Participants Individuals aged 65 and older principally hospitalized with pneumonia, COPD, or HF in 2009 or 2010. Measurements Proportion of diagnosed episodes of pneumonia, COPD, or HF concurrently treated for two or more of these acute cardiopulmonary conditions during the first 2 hospital days. Results Of 91,709 diagnosed pneumonia hospitalizations, 32% received treatment for two or more acute cardiopulmonary conditions (18% for HF, 18% for COPD, 4% for both). Of 41,052 diagnosed COPD hospitalizations, 19% received treatment for two or more acute cardiopulmonary conditions (all of which involved additional HF treatment). Of 118,061 diagnosed HF hospitalizations, 38% received treatment for two or more acute cardiopulmonary conditions (34% for pneumonia, 9% for COPD, 5% for both). Conclusion Hospitalized older adults diagnosed with pneumonia, COPD, or HF are frequently treated for two or more acute cardiopulmonary conditions, suggesting that clinical syndromes often fall between traditional diagnostic categories. Research is needed to evaluate the risks and benefits of real-world treatment for the many older adults whose presentations elicit diagnostic uncertainty or concern about coexisting acute conditions.

Background— The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Methods and Results— Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Conclusions— Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates.

The objectives of this study were to examine the magnitude of, and 20-year trends in, age differences in short-term outcomes among men and women hospitalized with acute myocardial infarction (AMI) in central Massachusetts.The study population consisted of 5907 male and 4406 female residents of the Worcester, MA, metropolitan area hospitalized at all greater Worcester medical centers with AMI between 1986 and 2005.Overall, among both men and women, older patients were significantly more likely to have developed atrial fibrillation, heart failure, and to have died during hospitalization and within 30 days after admission compared with patients aged65 years. Among men, age differences in the risk of developing atrial fibrillation have widened over the past 2 decades, while differences in the risk of developing cardiogenic shock have narrowed for men 75 years and older as compared with those aged65 years. Among women, age differences in the risk of developing these major complications of AMI have not changed significantly over time. Age differences in short-term mortality have remained relatively unchanged over the past 20 years in both sexes, although individuals of all ages have experienced decreases in short-term death rates over this period.Elderly men and women are more likely to experience adverse short-term outcomes after AMI, and age differences in short-term mortality rates have remained relatively unchanged in both sexes over the past 20 years. More targeted treatment approaches during hospitalization for AMI and thereafter are needed for older patients to improve their prognosis.

Personalized cancer therapy is likely to be one of the next big advances in our search for a cure for cancer. To be able to treat people in an individualized manner, researchers need to know a great deal about their genetic constitution and the DNA repair status of their tumors. Specific knowledge is required regarding the polymorphisms individuals carry and how these polymorphisms influence responses to therapy. Researchers are actively engaged in biomarker discovery and validation for this purpose. In addition, the design of clinical trials must be reassessed to include new information on biomarkers and drug responses. In this review, we focus on personalized breast cancer therapy. The hypothesis we focus upon in this review is that there is connection between the DNA repair profile of individuals, their breast tumor subtypes, and their responses to cancer therapy. We first briefly review cellular DNA repair pathways that are likely to be impacted by breast cancer therapies. Next, we review the phenotypes of breast tumor subtypes with an emphasis on how a DNA repair deficiency might result in tumorigenesis itself and lead to the chemotherapeutic responses that are observed. Specific examples of breast tumor subtypes and their responses to cancer therapy are given, and we discuss possible DNA repair mechanisms that underlie the responses of tumors to various chemotherapeutic agents. Much is known about breast cancer subtypes and the way each of these subtypes responds to chemotherapy. In addition, we discuss novel design of clinical trials that incorporates rapidly emerging information on biomarkers.

To investigate the clinicopathologic significance and predictive value of Bmi-1 expression in patients with colon cancer. 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). 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

Insulin-like growth factor-II mRNA-binding protein 3 (IMP3) plays a vital role in carcinogenesis; however, its significance and prognostic value in colon cancer remain unclear.In this study, a tissue microarray (TMA) containing 203 samples of primary colon cancer was assessed for IMP3 expression by immunohistochemistry. The TMA included 66 lymph node metastasis (LNM) samples. The mRNA and protein expression levels of IMP3 were evaluated by reverse transcription-PCR and Western blot analysis, respectively.Cytoplasmic immunoreactivity of IMP3 was significantly higher in LNM (93%) than in primary colon cancer (65%) or normal mucosa (3.9%). Increased IMP3 levels were significantly correlated with higher clinical stage, T classification, LNM, presence of distant metastasis, and Ki-67 positivity. IMP3 was up-regulated in colon cancer compared with paired normal colonic mucosa. IMP3 expression was associated with an 11-fold increased risk of distant metastases (hazard ratio (HR) 10.7; 95% confidence interval (CI) 3.3-34.5; P0.0001). Patients with IMP3-positive localized tumors had lower 5-year disease-free survival (DFS) (HR 2.87; 95% CI 1.65-4.98; P0.0001) and overall survival (OS) (HR 4.2; 95% CI 2.51-10.17; P0.0001) than those with IMP3-negative tumors. Multivariate survival analysis showed that IMP3 was an independent prognostic marker for DFS (HR 1.92; 95% CI 1.06-3.47; P = 0.03) and OS (HR 2.37; 95% CI 1.2-4.7; P = 0.014).IMP3 may play an important role in colon cancer progression and could serve as a prognostic biomarker to identify patients at risk of developing metastasis or recurrence after colonectomy.

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

Background During a myocardial infarction, no single best approach of systemic anticoagulation is recommended, likely due to a lack of comparative effectiveness studies and trade‐offs between treatments. Methods and Results We investigated the patterns of use and site‐level variability in anticoagulant strategies (unfractionated heparin [ UFH ] only, low‐molecular‐weight heparin [ LMWH ] only, UFH + LMWH , any bivalirudin) of 63 796 patients with a principal diagnosis of myocardial infarction treated with an early invasive strategy with percutaneous coronary intervention at 257 hospitals. About half (47%) of patients received UFH only, 6% UFH + LMWH , 7% LMWH only, and 40% bivalirudin. Compared with UFH , the median odds ratio was 2.90 for LMWH + UFH , 4.70 for LMWH only, and 3.09 for bivalirudin, indicating that 2 “identical” patients would have a 3‐ to 4‐fold greater likelihood of being treated with anticoagulants other than UFH at one hospital compared with another. We then categorized hospitals as low‐ or high‐users of LMWH and bivalirudin. Using hierarchical, multivariate regression models, we found that low bivalirudin‐using hospitals had higher unadjusted bleeding rates, but the risk‐adjusted and anticoagulant‐adjusted bleeding rates did not differ across the hospital anticoagulation phenotypes. Risk‐standardized mortality and risk‐standardized length of stay also did not differ across hospital phenotypes. Conclusions We found substantial site‐level variability in the choice of anticoagulants for invasively managed acute myocardial infarction patients, even after accounting for patient factors. No single hospital‐use pattern was found to be clinically superior. More studies are needed to determine which patients would derive the greatest benefit from various anticoagulants and to support consistent treatment of patients with the optimal anticoagulant strategy.

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.

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. Electronic supplementary material The online version of this article (doi:10.1007/s11606-014-2862-5) contains supplementary material, which is available to authorized users.

Background— The intensive practice style of hospitals with high procedure rates may result in higher costs of care for medically managed patients. We sought to determine how costs for patients with heart failure (HF) not receiving procedures compare between hospital groups defined by their overall use of procedures. Methods and Results— We identified all 2009 to 2010 adult HF hospitalizations in hospitals capable of performing invasive procedures that had at least 25 HF hospitalizations in the Perspective database from Premier, Inc. We divided hospitals into 2 groups by the proportion of patients with HF receiving invasive percutaneous or surgical procedures: low (>0%–10%) and high (≥10%). The standard costs of hospitalizations at each hospital were risk adjusted using patient demographics and comorbidities. We used the Wilcoxon rank sum test to assess cost, length of stay, and mortality outcome differences between the 2 groups. Median risk-standardized costs among low-procedural HF hospitalizations were $5259 (interquartile range, $4683–$6814) versus $6965 (interquartile range, $5981–$8235) for hospitals with high procedure use ( P P =0.009). We did not identify any single service area that explained the difference in costs between hospital groups, but these hospitals had higher costs for most service areas. Conclusion— Among patients who do not receive invasive procedures, the cost of HF hospitalization is higher in more procedure-intense hospitals compared with hospitals that perform fewer procedures.

To investigate the clinicopathological characteristics, histological diagnosis, immunohistochemistry and prognosis of cervical glassy cell carcinoma (GCC).The clinical characteristics, cytology, histology and immunohistochemistry were analyzed in 5 cases of GCC.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.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 evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design: Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results: Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions: Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation.

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.

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.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.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.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.

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 Heart failure as recognized and treated in typical practice may represent a complex condition that defies discrete categorizations. To illuminate this complexity, we examined treatment strategies for patients hospitalized and treated for decompensated heart failure. We focused on the receipt of medications appropriate for other acute conditions associated with shortness of breath including acute asthma, pneumonia, and exacerbated chronic obstructive pulmonary disease. Methods and Results Using Premier Perspective®, we studied adults hospitalized with a principal discharge diagnosis of heart failure and evidence of acute heart failure treatment from 2009-2010 at 370 US hospitals. We determined treatment with acute respiratory therapies during the initial 2 days of hospitalization and daily during hospital days 3-5. We also calculated adjusted odds of in-hospital death, admission to the intensive care unit, and late intubation (intubation after hospital day 2). Among 164,494 heart failure hospitalizations, 53% received acute respiratory therapies during the first 2 hospital days: 37% received short-acting inhaled bronchodilators, 33% received antibiotics, and 10% received high-dose corticosteroids. Of these 87,319 hospitalizations, over 60% continued receiving respiratory therapies after hospital day 2. Respiratory treatment was more frequent among the 60,690 hospitalizations with chronic lung disease. Treatment with acute respiratory therapy during the first 2 hospital days was associated with higher adjusted odds of all adverse outcomes. Conclusions Acute respiratory therapy is administered to more than half of patients hospitalized with and treated for decompensated heart failure. Heart failure is therefore regularly treated as a broader cardiopulmonary syndrome rather than as a singular cardiac condition.