Sex Differences in Long-Term Outcomes in Patients With Chronic Coronary Syndrome After Percutaneous Coronary Intervention　- Insights From a Japanese Real-World Database Using a Storage System.

BACKGROUND: Several studies have reported some sex differences in patients with coronary artery diseases. However, the results regarding long-term outcomes in patients with chronic coronary syndrome (CCS) are inconsistent. Therefore, the present study investigated sex differences in long-term outcomes in patients with CCS after percutaneous coronary intervention (PCI).Methods and Results: This was a retrospective, multicenter cohort study. We enrolled patients with CCS who underwent PCI between April 2013 and March 2019 using the Clinical Deep Data Accumulation System (CLIDAS) database. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, or hospitalization for heart failure. In all, 5,555 patients with CCS after PCI were included in the analysis (4,354 (78.4%) men, 1,201 (21.6%) women). The median follow-up duration was 917 days (interquartile range 312-1,508 days). The incidence of MACE was not significantly different between the 2 groups (hazard ratio [HR] 1.20; 95% confidential interval [CI] 0.97-1.47; log-rank P=0.087). After performing multivariable Cox regression analyses on 4 different models, there were still no differences in the incidence of MACE between women and men. CONCLUSIONS: There were no significant sex differences in MACE in patients with CCS who underwent PCI and underwent multidisciplinary treatments.

Wearable Sensor Data Classification for Identifying Missing Transmission Sequence Using Tree Learning.

Wearable Sensor (WS) data accumulation and transmission are vital in analyzing the health status of patients and elderly people remotely. Through specific time intervals, the continuous observation sequences provide a precise diagnosis result. This sequence is however interrupted due to abnormal events or sensor or communicating device failures or even overlapping sensing intervals. Therefore, considering the significance of continuous data gathering and transmission sequence for WS, this article introduces a Concerted Sensor Data Transmission Scheme (CSDTS). This scheme endorses aggregation and transmission that aims at generating continuous data sequences. The aggregation is performed considering the overlapping and non-overlapping intervals from the WS sensing process. Such concerted data aggregation generates fewer chances of missing data. In the transmission process, allocated first-come-first-serve-based sequential communication is pursued. In the transmission scheme, a pre-verification of continuous or discrete (missing) transmission sequences is performed using classification tree learning. In the learning process, the accumulation and transmission interval synchronization and sensor data density are matched for preventing pre-transmission losses. The discrete classified sequences are thwarted from the communication sequence and are transmitted post the alternate WS data accumulation. This transmission type prevents sensor data loss and reduces prolonged wait times.