This study aims to develop and validate prediction models for the number of all heatstroke cases, and heatstrokes of hospital admission and death cases per city per 12 h, using multiple weather information and a population-based database for heatstroke patients in 16 Japanese cities (corresponding to around a 10,000,000 population size). In the testing dataset, mean absolute percentage error of generalized linear models with wet bulb globe temperature as the only predictor and the optimal models, respectively, are 43.0% and 14.8% for spikes in the number of all heatstroke cases, and 37.7% and 10.6% for spikes in the number of heatstrokes of hospital admission and death cases. The optimal models predict the spikes in the number of heatstrokes well by machine learning methods including non-linear multivariable predictors and/or under-sampling and bagging. Here, we develop prediction models whose predictive performances are high enough to be implemented in public health settings.

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OBJECTIVEImproved outcomes in patients with subarachnoid hemorrhage (SAH) treated at high-volume centers have been reported. The authors sought to examine whether hospital case volume and comprehensive stroke center (CSC) capabilities affect outcomes in patients treated with clipping or coiling for SAH.METHODSThe authors conducted a nationwide retrospective cohort study in 27,490 SAH patients who underwent clipping or coiling in 621 institutions between 2010 and 2015 and whose data were collected from the Japanese nationwide J-ASPECT Diagnosis Procedure Combination database. The CSC capabilities of each hospital were assessed by use of a validated scoring system based on answers to a previously reported 25-item questionnaire (CSC score 1–25 points). Hospitals were classified into quartiles based on CSC scores and case volumes of clipping or coiling for SAH.RESULTSOverall, the absolute risk reductions associated with high versus low case volumes and high versus low CSC scores were relatively small. Nevertheless, in patients who underwent clipping, a high case volume (> 14 cases/yr) was significantly associated with reduced in-hospital mortality (Q1 as control, Q4 OR 0.71, 95% CI 0.55–0.90) but not with short-term poor outcome. In patients who underwent coiling, a high case volume (> 9 cases/yr) was associated with reduced in-hospital mortality (Q4 OR 0.69, 95% CI 0.53–0.90) and short-term poor outcomes (Q3 [> 5 cases/yr] OR 0.75, 95% CI 0.59–0.96 vs Q4 OR 0.65, 95% CI 0.51–0.82). A high CSC score (> 19 points) was significantly associated with reduced in-hospital mortality for clipping (OR 0.68, 95% CI 0.54–0.86) but not coiling treatment. There was no association between CSC capabilities and short-term poor outcomes.CONCLUSIONSThe effects of case volume and CSC capabilities on in-hospital mortality and short-term functional outcomes in SAH patients differed between patients undergoing clipping and those undergoing coiling. In the modern endovascular era, better outcomes of clipping may be achieved in facilities with high CSC capabilities.

Aims  To evaluate the prognostic impact of fragmented QRS (fQRS) on idiopathic dilated cardiomyopathy (DCM). Methods and results  We conducted a prospective observational study of 290 consecutive patients with DCM (left ventricular ejection fraction ≤ 40%) and narrow QRS who underwent cardiac magnetic resonance. We defined fQRS as the presence of various RSR′ patterns in ≥2 contiguous leads representing the anterior (V1–V5), inferior (II, III, and aVF), or lateral (I, aVL, and V6) myocardial segments. Multiple fQRS was defined as the presence of fQRS in ≥2 myocardial segments. Patients were divided into three groups: no fQRS, single fQRS, or multiple fQRS. The primary endpoint was a composite of hard cardiac events consisting of heart failure death, sudden cardiac death (SCD), or aborted SCD. The secondary endpoints were all-cause death and arrhythmic event. During a median follow-up of 3.8 years (interquartile range, 1.8–6.2), 31 (11%) patients experienced hard cardiac events. Kaplan–Meier analysis showed that the rates of hard cardiac events and all-cause death were similar in the single-fQRS and no-fQRS groups and higher in the multiple-fQRS group (P = 0.004 and P = 0.017, respectively). Multivariable Cox regression identified that multiple fQRS is a significant predictor of hard cardiac events (hazard ratio, 2.23; 95% confidence interval, 1.07–4.62; P = 0.032). The multiple-fQRS group had the highest prevalence of a diffuse late gadolinium enhancement pattern (no fQRS, 21%; single fQRS, 22%; multiple fQRS, 39%; P < 0.001). Conclusion  Multiple fQRS, but not single fQRS, is associated with future hard cardiac events in patients with DCM.

In-home monitoring systems have been used to detect cognitive decline in older adults by allowing continuous monitoring of routine activities. In this study, we investigated whether unobtrusive in-house power monitoring technologies could be used to predict cognitive impairment. A total of 94 older adults aged ≥65 years were enrolled in this study. Generalized linear mixed models with subject-specific random intercepts were used to evaluate differences in the usage time of home appliances between people with and without cognitive impairment. Three independent power monitoring parameters representing activity behavior were found to be associated with cognitive impairment. Representative values of mean differences between those with cognitive impairment relative to those without were −13.5 min for induction heating in the spring, −1.80 min for microwave oven in the winter, and −0.82 h for air conditioner in the winter. We developed two prediction models for cognitive impairment, one with power monitoring data and the other without, and found that the former had better predictive ability (accuracy, 0.82; sensitivity, 0.48; specificity, 0.96) compared to the latter (accuracy, 0.76; sensitivity, 0.30; specificity, 0.95). In summary, in-house power monitoring technologies can be used to detect cognitive impairment.