The implication of sepsis-induced cardiomyopathy (SIC) to prognosis is controversial, and its association with mortality at different stages remains unclear. We conducted a systematic review and meta-analysis to understand the association between SIC and mortality in septic patients. We searched and appraised observational studies regarding the mortality related to SIC among septic patients in PubMed and Embase from inception until 8 July 2021. Outcomes comprised in-hospital and 1-month mortality. We adopted the random-effects model to examine the mortality risk ratio in patients with and without SIC. Meta-regression, subgroup, and sensitivity analyses were applied to examine the outcome’s heterogeneity. Our results, including 20 studies and 4,410 septic patients, demonstrated that SIC was non-statistically associated with increased in-hospital mortality, compared to non-SIC (RR 1.28, [0.96–1.71]; p = 0.09), but the association was statistically significant in patients with the hospital stay lengths longer than 10 days (RR 1.40, [1.02–1.93]; p = 0.04). Besides, SIC was significantly associated with a higher risk of 1-month mortality (RR 1.47, [1.17–1.86]; p < 0.01). Among SIC patients, right ventricular dysfunction was significantly associated with increased 1-month mortality (RR 1.72, [1.27–2.34]; p < 0.01), while left ventricular dysfunction was not (RR 1.33, [0.87–2.02]; p = 0.18). With higher in-hospital mortality in those hospitalized longer than 10 days and 1-month mortality, our findings imply that SIC might continue influencing the host’s system even after recovery from cardiomyopathy. Besides, right ventricular dysfunction might play a crucial role in SIC-related mortality, and timely biventricular assessment is vital in managing septic patients.

Background:EMPEROR-Reduced trial provides promising evidence on the efficacy of empagliflozin adding to the standard treatment in patients with heart failure and reduced ejection fraction (HFrEF). This study aimed to investigate the cost-effectiveness of add-on empagliflozin vs. standard therapy alone in HFrEF from the perspective of the Asia-Pacific healthcare systems.Methods:A Markov model was constructed to simulate HFrEF patients and to project the lifetime direct medical costs and quality-adjusted life years (QALY) of both therapies. Transitional probabilities were derived from the EMPEROR-Reduced trial. Country-specific costs and utilities were extracted from published resources. Incremental cost-effectiveness ratio (ICER) against willingness to pay (WTP) threshold was used to examine the cost-effectiveness. A series of sensitivity analyses was performed to ensure the robustness of the results.Results:The ICERs of add-on empagliflozin vs. standard therapy alone in HFrEF were US$20,508, US$24,046, US$8,846, US$53,791, US$21,543, and US$20,982 per QALY gained in Taiwan, Japan, South Korea, Singapore, Thailand, and Australia, respectively. Across these countries, the probabilities of being cost-effective for using add-on empagliflozin under the WTP threshold of 3-times country-specific gross domestic product per capita were 93.7% in Taiwan, 95.6% in Japan, 96.3% in South Korea, 94.2% Singapore, 51.9% in Thailand, and 95.9% in Australia. The probabilities were reduced when shortening the time horizon, assuming the same cardiovascular mortality for both treatments, and setting lower WTP thresholds.Conclusion:Adding empagliflozin to HFrEF treatment is expected to be a cost-effective option among the Asia-Pacific countries. The cost-effectiveness is influenced by the WTP thresholds of different countries.

Background: Atherosclerotic cardiovascular disease (ASCVD) encompasses various phenotypes with elevated risks of major adverse cardiovascular events (MACEs). This study aimed to assess the comparative cardiovascular effectiveness of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium–glucose cotransporter-2 inhibitors (SGLT2is) across diverse ASCVD phenotypes. Methods and results: We conducted a systematic review and meta-analysis of randomized controlled trials evaluating GLP-1 RAs or SGLT2is against placebo or standard care in ASCVD patients. Primary outcomes included MACE, defined as cardiovascular mortality, non-fatal myocardial infarction, and non-fatal stroke. Risk ratios (RRs) with 95% confidence interval (CI) were calculated using a random-effects model. Twenty-six trials (151 789 patients) were included. Both GLP-1 RAs and SGLT2is significantly reduced MACE rates in ASCVD patients (RR 0.85; 95% CI 0.80–0.91 for both). GLP-1 RAs showed significant effectiveness in peripheral artery disease (RR 0.86; 95% CI 0.76–0.98) and post-acute cardiovascular events (RR 0.90; 95% CI 0.83–0.97). In ASCVD with heart failure, both drug classes reduced MACE (GLP-1 RAs: RR 0.73; 95% CI 0.63–0.84; SGLT2is: RR 0.86; 95% CI 0.78–0.95). SGLT2is significantly reduced MACE in ASCVD with chronic kidney disease (RR 0.84; 95% CI 0.72–0.99), particularly in severe albuminuria (RR 0.61; 95% CI 0.37–0.99). Conclusion: GLP-1 RAs and SGLT2is exhibit distinct cardiovascular effectiveness profiles across ASCVD phenotypes. GLP-1 RAs show particular benefits in peripheral artery disease and post-acute cardiovascular events, while SGLT2is demonstrate unique advantages in ASCVD with comorbid chronic kidney disease. Both are effective in heart failure. These findings support tailored treatment strategies for diverse ASCVD participants based on specific comorbidities and risk factors.

Electrocardiography (ECG) is generally deemed the golden standard for diagnosing cardiovascular diseases and photoplethysmography (PPG) is unobtrusive, low-cost, and convenient for continuous monitoring. However, PPG contains insufficient information to diagnose diseases. In this study, we propose a novel method to accurately convert PPG to ECG. The banded kernel ensemble method converts a low-quality source (PPG) to a high-quality destination (ECG). Unlike neural network solutions, our algorithm requires no computation burden in the conversion task after a trained model is obtained. The proposed algorithm is then tested on a publicly available MIMIC III database. Our prediction shows excellent accuracy in the validation dataset. It offers the testing performance of under 0.314 and above 0.55 in rrmse (relative root mean squared error) and KGE (Kling–Gupta efficiency), respectively, under the scenarios of three prevalent heart diseases. The reconstructed ECG can be further used to perform heart disease detection and we obtained an average correctness rate of 81%. Our method can help a large population of high-risk, believed-healthy persons to walk into doctors’ offices before the situation becomes irreversible.

Long-term wiring on a newborn patient could be a disguise scene for parents. Unobtrusive and reliable monitoring without wiring can be a euphoric alternative for newborns and parents in obstetrics and gynecology (OB/GYN) incubation rooms. However, reliable and continuous non-contact surveillance in an incubation room is challenging. Therefore, a novel photoplethysmography imaging (PPGi) is developed specifically for baby skins through predictive adversarial adaptation and risk-sensitive generative synchronizer. Our artificial intelligence approach does not take blind guesses from input-output pairs. We apply an intelligent step to decouple the influence of fluctuated illumination through a generative algorithm of artificial intelligence. To boost skin detection performance, we capture those pixels with periodic variations and maximize the coherence of the extraction algorithm by the generative synchronizer. The periodic variations are matched by a synthesized pulse from the output PPGi signals through the control of a risk-sensitive filter to not over-compensate the illuminate variation. Based on the sensed pulsation, we synthesize the corresponding pulsation signals on the flight to identify the living skin in a spatiotemporal image sequence. We find that our skin classifier in risk-sensitive generative synchronizer effectively improves the quality of the resulting non-contact PPGi signal. Our algorithm produces substantial accuracy in the performance of PPGi reconstruction in the critical environment of newborn care. In the limited illustration of the incubation room, our non-contact PPGi can still achieve an average accuracy of 96.62%.