Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review.

Artificial intelligence (AI) and machine learning (ML) have an immense potential to transform healthcare as already demonstrated in various medical specialties. This scoping review focuses on the factors that influence health data poverty, by conducting a literature review, analysis, and appraisal of results. Health data poverty is often an unseen factor which leads to perpetuating or exacerbating health disparities. Improvements or failures in addressing health data poverty will directly impact the effectiveness of AI/ML systems. The potential causes are complex and may enter anywhere along the development process. The initial results highlighted studies with common themes of health disparities (72%), AL/ML bias (28%) and biases in input data (18%). To properly evaluate disparities that exist we recommend a strengthened effort to generate unbiased equitable data, improved understanding of the limitations of AI/ML tools, and rigorous regulation with continuous monitoring of the clinical outcomes of deployed tools.

Critical Bias in Critical Care Devices.

Critical care data contain information about the most physiologically fragile patients in the hospital, who require a significant level of monitoring. However, medical devices used for patient monitoring suffer from measurement biases that have been largely underreported. This article explores sources of bias in commonly used clinical devices, including pulse oximeters, thermometers, and sphygmomanometers. Further, it provides a framework for mitigating these biases and key principles to achieve more equitable health care delivery.

Sex Differences in Cardiovascular Outcomes and Cholesterol-Lowering Efficacy of PCSK9 Inhibitors: Systematic Review and Meta-Analysis.

Background: Guideline-recommended low-density lipoprotein cholesterol (LDL-C) thresholds are often not achieved in women. The proprotein convertase subtilisin/kexin type-9 inhibitor (PCSK9i) monoclonal antibodies can help further reduce LDL-C and major adverse cardiovascular events (MACE) although differences in efficacy by sex and type are less understood. Objectives: The authors sought to determine if there are differences in the efficacy of LDL-C lowering and reduction in the risk of MACE by sex and type of PCSK9i. Methods: A comprehensive literature search was done through October 17, 2022, for published trials comparing PCSK9i vs control. Outcomes assessed were LDL-C reduction and incidence of MACE following the use of PCSK9i vs placebo, stratified by sex and type of PCSK9i used. Results: We identified 16 trials with 54,996 adults, and 15,143 (27.5%) of them were female. PCSK9i significantly reduced MACE compared to placebo in both women (HR: 0.86, 95% CI: 0.74-0.97, P < 0.001) and men (HR: 0.85, 95% CI: 0.79-0.91, P < 0.001) with no significant sex difference (MD -0.01, 95% CI: -0.14 to -0.13, P = 0.930). PCSK9i also significantly reduced LDL-C levels in both sexes at 12 weeks (females: MD -62.57, 95% CI: -70.24 to -54.91, P < 0.001; males: MD -66.19, 95% CI: -72.03 to -60.34, P < 0.001) and 24 weeks (females: MD -47.52, 95% CI: -52.94 to -42.09, P < 0.001; males: MD -54.07, 95% CI: -59.46 to -48.68, P < 0.001). Significant sex difference was seen in the LDL reduction of PCSK9i for both 12 weeks (males vs females: MD -4.55, 95% CI: -7.34 to -1.75, P < 0.01) and 24 weeks (males vs females: MD -7.11, 95% CI: -9.99 to -4.23, P < 0.001). Conclusions: The use of PCSK9i results in significant LDL-C and MACE reduction in both males and females. While there is no significant sex difference in MACE reduction, LDL-C reduction is greater in males than in females. Our data support the equal use of PCSK9i in all eligible patients, regardless of sex.

Brain magnetic resonance imaging in adult survivors of extracorporeal membrane oxygenation.

Despite the common occurrence of neurologic complications in patients with extracorporeal membrane oxygenation (ECMO), data on magnetic resonance imaging (MRI) findings in adult ECMO are limited. We aimed to describe the MRI findings of patients after ECMO cannulation. Records of patients who underwent ECMO from September 2017 to June 2019 were reviewed. MRI studies were performed using multiplanar sequences consisting of T1-, T2-weighted, fluid attenuated inversion recovery (FLAIR), diffusion-weighted imaging (DWI), and susceptibility weighted images (SWI). Of the 78 adult patients who underwent ECMO, 26 (33%) survived. Of 26, eight patients (31%) had MRI studies, with a median age of 47 years (interquartile range [IQR]: 25-57). The median ECMO support time was 8 days (IQR: 4-25) and the median time from decannulation to MRI was 12 days (IQR: 1-34). Five (63%) of eight patients had ischemic infarcts; 4 (50%) had cerebral microhemorrhage; 2 (25%) had intracranial hemorrhage; and 1 (13%) had thoracic cord ischemic infarct. There were no patients with normal MRI. All patients underwent transcranial Doppler (TCD). Four of 8 (50%) showed presence of microemboli with TCD; 3 of 4 (75%) had ischemic infarcts; and 1 of 4 (25%) had presence of multiple cerebral microhemorrhages on MRI. All ischemic infarcts had diffuse pattern of punctate to small lesions for ECMO survivors. The location of cerebral microhemorrhages included lobar (n = 4, 100%), deep (n = 2, 50%), and both (n = 2, 50%). Of the MRI studies, cerebrovascular related lesions were the most frequent, with punctate ischemic infarct being the most common type that may be associated with TCD microemboli. The results of the study suggest that subclinical cerebral lesions are commonly found in patients with ECMO support. Further research is needed to understand long-term effect of these cerebral lesions.