Gender Differences in Hospital Outcomes among COVID-19 Hospitalizations.

OBJECTIVES: Many epidemiological studies have shown that coronavirus disease 2019 (COVID-19) disproportionately affects males, compared with females, although other studies show that there were no such differences. The aim of the present study was to assess differences in the prevalence of hospitalizations and in-hospital outcomes between the sexes, using a larger administrative database. METHODS: We used the 2020 California State Inpatient Database for this retrospective analysis. International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis code U07.1 was used to identify COVID-19 hospitalizations. These hospitalizations were subsequently stratified by male and female sex. Diagnosis and procedures were identified using the International Classification of Diseases, Tenth Revision, Clinical Modification codes. The primary outcome of the study was hospitalization rate, and secondary outcomes were in-hospital mortality, prolonged length of stay, vasopressor use, mechanical ventilation, and intensive care unit (ICU) admission. RESULTS: There were 95,180 COVID-19 hospitalizations among patients 18 years and older, 52,465 (55.1%) of which were among men and 42,715 (44.9%) were among women. In-hospital mortality (12.4% vs 10.1%), prolonged length of hospital stays (30.6% vs 25.8%), vasopressor use (2.6% vs 1.6%), mechanical ventilation (11.8% vs 8.0%), and ICU admission rates (11.4% versus 7.8%) were significantly higher among male compared with female hospitalizations. Conditional logistic regression analysis showed that the odds of mortality (odds ratio [OR] 1.38, 95% confidence interval [CI] 1.38-1.44), hospital lengths of stay (OR 1.35, 95% CI 1.31-1.39), vasopressor use (OR 1.59, 95% CI 1.51-1.66), mechanical ventilation (OR 1.62, 95% CI 1.47-1.78), and ICU admission rates (OR 1.58, 95% CI 1.51-1.66) were significantly higher among male hospitalizations. CONCLUSION: Our findings show that male sex is an independent and strong risk factor associated with COVID-19 severity.

Wearable Alcohol Monitoring Device for the Data-Driven Transcutaneous Alcohol Diffusion Model.

Wearable alcohol monitoring devices demand noninvasive, real-time measurement of blood alcohol content (BAC) reliably and continuously. A few commercial devices are available to determine BAC noninvasively by detecting transcutaneous diffused alcohol. However, they suffer from a lack of accuracy and reliability in the determination of BAC in real time due to the complex scenario of the human skin for transcutaneous alcohol diffusion and numerous factors (e.g., skin thickness, kinetics of alcohol, body weight, age, sex, metabolism rate, etc.). In this work, a transcutaneous alcohol diffusion model has been developed from real-time captured data from human wrists to better understand the kinetics of diffused alcohol from blood to different skin epidermis layers. Such a model will be a footprint to determine a base computational model in larger studies. Eight anonymous volunteers participated in this pilot study. A laboratory-built wearable blood alcohol content (BAC) monitoring device collected all the data to develop this diffusion model. The proton exchange membrane fuel cell (PEMFC) sensor was fabricated and integrated with an nRF51822 microcontroller, LMP91000 miniaturized potentiostat, 2.4 GHz transceiver supporting Bluetooth low energy (BLE), and all the necessary electronic components to build this wearable BAC monitoring device. The %BAC data in real time were collected using this device from these volunteers' wrists and stored in the end device (e.g., smartphone). From the captured data, we demonstrate how the volatile alcohol concentration on the skin varies over time by comparing the alcohol concentration in the initial stage (= 10 min) and later time (= 100 min). We also compare the experimental results with the outputs of three different input profiles: piecewise linear, exponential linear, and Hoerl, to optimize the developed diffusion model. Our results demonstrate that the exponential linear function best fits the experimental data compared to the piecewise linear and Hoerl functions. Moreover, we have studied the impact of skin epidermis thickness within ±20% and demonstrate that a 20% decrease in this thickness results in faster dynamics compared to thicker skin. The model clearly shows how the diffusion front changes within a skin epidermis layer with time. We further verified that 60 min was roughly the time to reach the maximum concentration, Cmax, in the stratum corneum from the transient analysis. Lastly, we found that a more significant time difference between BACmax and Cmax was due to greater alcohol consumption for a fixed absorption time.

Prevalence and effects of acute myocardial infarction on hospital outcomes among COVID-19 patients.

BACKGROUND: Acute myocardial infarction (AMI) is one of the most lethal complications of COVID-19 hospitalization. In this study, we looked for the occurrence of AMI and its effects on hospital outcomes among COVID-19 patients. METHODS: Data from the 2020 California State Inpatient Database was used retrospectively. All COVID-19 hospitalizations with age ≥ 18 years were included in the analyses. Adverse hospital outcomes included in-hospital mortality, prolonged length of stay (LOS), vasopressor use, mechanical ventilation, and ICU admission. Prolonged LOS was defined as any hospital LOS ≥ 75th percentile. Multivariate logistic regression analyses were used to understand the strength of associations after adjusting for cofactors. RESULTS: Our analysis had 94 114 COVID-19 hospitalizations, and 1548 (1.6%) had AMI. Mortality (43.2% vs. 10.8%, P  < 0.001), prolonged LOS (39.9% vs. 28.2%, P  < 0.001), vasopressor use (7.8% vs. 2.1%, P  < 0.001), mechanical ventilation (35.0% vs. 9.7%, P  < 0.001), and ICU admission (33.0% vs. 9.4%, P  < 0.001) were significantly higher among COVID-19 hospitalizations with AMI. The odds of adverse outcomes such as mortality (aOR 3.90, 95% CI: 3.48-4.36), prolonged LOS (aOR 1.23, 95% CI: 1.10-1.37), vasopressor use (aOR 3.71, 95% CI: 3.30-4.17), mechanical ventilation (aOR 2.71, 95% CI: 2.21-3.32), and ICU admission (aOR 3.51, 95% CI: 3.12-3.96) were significantly more among COVID-19 hospitalizations with AMI. CONCLUSION: Despite the very low prevalence of AMI among COVID-19 hospitalizations, the study showed a substantially greater risk of adverse hospital outcomes and mortality. COVID-19 patients with AMI should be aggressively treated to improve hospital outcomes.