Johnson, Patrick W.

The Omicron variant of SARS-CoV-2 is associated with milder symptoms and lower hospitalization and mortality rates than Delta variants, although the impact of Omicron on immunocompromised patients, especially solid organ transplant (SOT) recipients, is still unclear. This study compares the hospitalization rate and outcomes between immunocompromised, immunocompetent, and SOT patients during the Delta and Omicron periods. We included adult patients who tested positive for SARS-CoV-2 on PCR or nasopharyngeal antigen test between 26 June 2021 to 8 September 2022, at our institution. A total of 12,401 COVID-19 patients were included, of which 11,055 were immunocompetent, and 1346 were immunocompromised (375 SOT recipients). Throughout the Delta and Omicron outbreaks, immunocompromised patients exhibited higher comorbidities and 30-day hospitalizations, but rates of mechanical ventilation and ICU-level care were like immunocompetent patients. During the Omicron wave, immunocompromised patients had higher unadjusted relative risk estimates (RR = 2.37, 95% CI 1.96–2.87, p < 0.05) than Delta (RR = 1.58, 95% CI 1.24–2.01, p < 0.05), with higher adjusted relative risk for hospitalization in Omicron (RR = 1.50, 95% CI 1.10–2.03, p = 0.01). Analyses show increased hospitalization risk in immunocompromised during the Omicron wave compared to the Delta wave, with no significant difference in hospitalization outcomes. The relative risk of hospitalization for SOT patients was higher in both waves.

Background Ketamine has demonstrated efficacy in treatment-resistant depression, primarily in psychiatric or outpatient populations. Its use in ICU patients remains underexplored, with limited data beyond case reports and small series. This study evaluated the association between subanesthetic ketamine infusions and improvement in depressive symptoms and hemodynamic changes in ICU patients. Methods We conducted a retrospective study of adults admitted to the ICU who received IV ketamine (0.3-0.75 mg/kg over 40 min on three consecutive days) for depressive symptoms. Changes in depressive symptoms were assessed using routine clinical documentation by physicians, nurses, and occupational and physical therapists. Hemodynamic parameters (blood pressure and heart rate) were recorded before and up to 120 min after infusion. The primary outcome was to evaluate depressive symptoms while the secondary outcome was to assess hemodynamic changes post transfusion. Results Thirty-four patients met criteria, including 18 solid organ transplant recipients. Median age was 59 years; 61.8% were male. Ketamine was associated with improvement in apparent sadness (90.0% vs 52.2%, P < .05) and reported sadness (95.0% vs 59.1%, P < .05). In transplant recipients, improvement in apparent sadness remained significant (80.0% vs 41.7%, P < .05). Hemodynamic parameters remained stable; heart rate increased transiently at 15-30 min post-infusion, returning to baseline by 60-90 min. Adverse effects observed were anxiety (12.5%), restlessness and/or agitation (10.4%), and dissociation (8.16%). Conclusion Subanesthetic ketamine improved specific depressive symptoms in critically ill ICU patients without significant hemodynamic instability. These findings support its potential as a rapid-acting antidepressant in the ICU, warranting further prospective trials.

Abstract Background Artificial intelligence enhanced electrocardiograms (AI-ECG) have matured over the past 10 years. More recently, the AI-ECG estimate of biological sex has shown potential as a novel tool for cardiovascular risk stratification among women. Cardiovascular disease is a leading cause of pregnancy-related mortality; however, there have been limited approaches for estimating the physiological demands of pregnancy and its impact of maternal cardiovascular outcomes. Purpose To estimate pregnancy-related changes on AI-ECG-based sex and age estimation in a prospective cohort of otherwise healthy, complication free pregnant women. Methods This secondary analysis of the SPEC-AI Nigeria Clinical Trial identified pregnant women without any pregnancy-related complications (at baseline or during follow-up) who had at least two 12 lead ECGs recorded during the study. The ECGs were analyzed with previously-developed algorithms to predict age and biological sex. To address bias in the AI-ECG age estimate, a reference cohort of 25,144 healthy patients was analyzed using quantile regression to estimate the 75th percentile of the reference distribution as a function of age. The estimate of biological sex was used to determine a sex discordance score with a discordance of 0.2 considered clinically relevant. To simplify the trends in the data, the ECGs were categorized as during pregnancy (&lt;=28 days prior to birth), peripartum (+/- 28 days of birth), and postpartum (28+ days after birth), and mixed effects models with a random intercept were used for analysis. Results A total of 207 females with a median age of 31 years (IQR 28 to 36 years) and normal blood pressures (systolic: 110 (IQR 10 to 120); diastolic: 70 (IQR 60-77); mmHg) were included from 5 clinical sites in Nigeria. The majority (73%, 150/207) of participants were in their second trimester at time of enrollment and the median number of ECGs per participant was 3 (max 7). The sex discordance score was elevated in 38% of the women at baseline and this percentage fell to 23% postpartum; which resulted in a decrease in the mean discordance score of 0.03 (95% CI: -0.06 to 0.0; p=0.028). Conversely, the percentage of patients with elevated age prediction increased from 35% to 41% over the course of pregnancy. This resulted in an increase in the bias-corrected AI-ECG age of 3.0 years (95% CI: 1.5 to 4.6 years; p&lt;0.001). Conclusion This study demonstrates the preliminary utility of serial AI-ECG based assessment as a marker for the biological effects of pregnancy. The increase in sex discordance score during pregnancy may be related to changes in cardiac structure, such as increased ventricular mass and chamber dilation which often reverses postpartum. However, the impact on age estimation appeared to persist in the early postpartum period. Further study is warranted to associate any changes observed with long term maternal or fetal outcomes.Figure

Abstract Background Ischemic heart disease is the leading cause of death among women. Non-obstructive coronary disease (NOCAD), often identified by a positive stress test and negative coronary angiogram result, is linked to adverse outcomes, particularly among women. Purpose This study evaluated the impact of discordant Single Photon Emission Computed Tomography (SPECT) Myocardial Perfusion Imaging (MPI) stress test and coronary angiogram results on repeat invasive angiography and survival, while assessing sex-related differences. Methods Data were extracted from a single health system for patients who underwent a SPECT MPI stress test, and invasive coronary angiography performed within 3 months from September 2002 to July 2018. Discordance was defined as: Profile A – a positive stress test with negative angiography (epicardial coronary vessel stenosis &lt;50%); Profile B – a negative stress test with positive angiography (at least one epicardial coronary vessel stenosis &gt;=50%). To assess the association between discordance and all-cause mortality, Cox-proportional hazards regression was used to analyze the most recent stress/angiogram pair (adjusting for race, age, and number of prior angiograms). For repeat invasive angiography, where mortality was considered a competing event, the Fine-Gray proportional hazards model for the sub-distribution of a competing risk was used to analyze the first stress/angiogram pair (adjusting for race and age). Hazard ratios (HRs), sub-distribution hazard ratios (SHRs), and corresponding 95% confidence intervals (CIs) were reported. Results 5,179 were included in the final analysis, median age was 67.9 years and 32.7% were female. Approximately 15% and 24% were classified as Profile A and B respectively. Patients with a negative stress/negative angiogram were designated as the reference group. Profile A was not significantly associated with mortality or repeat invasive testing in both sexes. Profile B was associated with the highest risk of death (female aHR: 1.58, P&lt;.001; male aHR: 1.54, P&lt;.001) followed by those with a positive stress/positive angiogram (female aHR: 1.39, P=.009; male aHR: 1.25, P=.05) compared to the reference group. Profile B was significantly associated with repeat invasive testing and a stronger association was seen in females (female aSHR: 9.84, P&lt; .001; male aSHR: 3.42, P&lt;.001). A similar pattern was seen for those with a positive stress/positive angiogram. Conclusion Discordant Profile A showed no significant association with mortality or repeat invasive testing. Discordant Profile B was associated with the highest mortality risk in both sexes and showed a stronger association with repeat invasive testing among females. These findings underscore the importance of careful patient selection for stress testing, the need for improved stress testing options (especially in females), and prompt coronary evaluation in patients with a negative stress test and persistent symptoms or high-risk features.

Background: Pulmonary hypertension (PH) is a life-threatening disease affecting up to 1% of the global population. Diagnosis can be challenging and is often delayed due to the need for advanced imaging and invasive procedures. The use of artificial intelligence applied to ECGs (ECG-AI) has been shown to detect subtle patterns in voltage-time data and may be a valuable tool for the early detection of PH. Hypothesis and Purpose: To evaluate the performance of a previously trained, ECG-AI algorithm to detect PH (ECG-AI PH) using real-world data (RWD) collected in a multicenter, validation study. A joint primary hypothesis required sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) to exceed the null values of 76%, 70%, 10% and 90%. Study Design and Methods: This retrospective validation study was conducted at 5 geographically diverse U.S. health systems. Adult subjects were eligible for inclusion if they had a 12-lead ECG paired with an echocardiogram (Echo) in which tricuspid regurgitation velocity (TRV) was recorded, following presentation with dyspnea. Patients were classified according to echocardiographic criteria as either PH (PH+, TRV >3.4 m/s) or controls (PH-, TRV ≤2.8 m/s) to simulate the real-world use of ECG-AI, where a positive result could lead to a follow-up Echo. The study database was locked before processing the digital ECGs with ECG-AI PH. Performance was also estimated in a subset of subjects that later had a right heart catheterization using mPAP ≥ 20mmHg as the definition of PH. Results: A total of 14281 subjects (53% female, 63% aged 50+ years) met the inclusion criteria, including 3019 PH+ cases and 11262 PH- controls (Figure). Sn and Sp were 84.0% (95% CI: 82.6%, 85.3%) and 71.7% (95% CI: 70.9%, 72.6%), respectively. The positive and negative predictive values were 18.9% (95% CI: 18.4%, 19.4%) and 98.3% (95% CI: 98.1%, 98.4%), respectively, at 7.3% prevalence. Each endpoint met pre-defined performance criteria. In the subset of 1683 subjects with a follow up RHC, performance remained robust (Sn 85% (1155/1358); Sp 46% (151/325)). Conclusion: While ECG-AI PH was first developed as an investigational tool to detect PH, continued development as software as a medical device for clinical use demonstrated that the algorithm retained strong performance to detect PH in diverse, non-overlapping clinical settings and patient populations.

INTRODUCTION: The SPEC-AI Nigeria trial (NCT05438576) was designed to use artificial intelligence (AI) to screen for pregnancy-related cardiomyopathy in the peripartum period. Using data from this study, we evaluated the utility of AI-predicted delta age (adjusted AI-predicted age − chronological age) as a surrogate for biological age. METHODS: We included 1,187 pregnant and postpartum women enrolled between August 2022 and September 2023 with follow-up through May 2024. Standard 12-lead electrocardiograms (ECGs) were recorded at study entry to generate AI age predictions. Artificial intelligence-predicted age was adjusted using estimated reference ranges obtained from a community-dwelling cohort of 25,144 individuals with AI-ECG age estimated and documented chronological age. Logistic and Cox-proportional hazards regression were used to examine associations with comorbid cardiovascular conditions and maternal mortality, respectively. RESULTS: Adjusted AI-predicted age was significantly higher among women with any cardiovascular condition, peripartum cardiomyopathy, or who died within 18 months (7, 14, and 23 years older, respectively) compared to those without these conditions who had values similar to the normal reference ranges (adjusted AI-predicted age difference less than 1 year). Artificial intelligence-predicted delta age greater than the 75th percentile was associated with an odds ratio (OR) of 2.06 for any cardiovascular condition, OR of 4.98 for left ventricular systolic dysfunction, and a hazard ratio of 32.81 for all-cause mortality; all values of P<.001. CONCLUSIONS/IMPLICATIONS: Artificial intelligence-ECG-derived biological age appears to be a potentially useful measure of cardiovascular health status and risk among pregnant and postpartum women. However, its role in monitoring maternal health requires further exploration.

AbstractINTRODUCTIONPhosphorylated ubiquitin (p‐S65‐Ub) is generated during PINK1‐PRKN mitophagy as a specific marker of mitochondrial damage. Despite the widespread deposition of p‐S65‐Ub in aged and diseased human brain, the genetic contribution to its accumulation remains unclear.METHODSTo identify novel mitophagy regulators, we performed a genome‐wide association study using p‐S65‐Ub level as a quantitative trait in 1012 autopsy‐confirmed Lewy body disease (LBD) samples.RESULTSWe identified a significant genome‐wide association with p‐S65‐Ub for rs429358 (apolipoprotein E ε4 [APOE4]) and a suggestive association for rs6480922 (ZMIZ1). APOE4 was associated with higher p‐S65‐Ub levels and greater neuropathological burden. Functional validation in mouse and human induced pluripotent stem cell (iPSC) models confirmed APOE4‐mediated mitophagy alterations. Intriguingly, ZMIZ1 rs6480922 was associated with lower p‐S65‐Ub levels, reduced neuropathological load, and increased brain weight, indicating a potential protective role.DISCUSSIONOur findings underscore the importance of mitochondrial quality control in LBD pathogenesis and nominate regulators that may contribute to disease risk or resilience.Highlights p‐S65‐Ub levels were used as a quantitative marker of mitochondrial damage. A GWAS identified two genetic variants that modify mitophagy in LBD autopsy brain. APOE4 was associated with increased p‐S65‐Ub accumulation and neuropathology. APOE4 altered mitophagy via pathology‐dependent and pathology‐independent mechanisms. ZMIZ1 was linked to reduced p‐S65‐Ub and neuropathology indicative of protection.

Abstract Studies assessing genetic associations with neuropathological features in Lewy body disease (LBD) have been limited to candidate gene investigations, and therefore, information is lacking regarding the genetic architecture of the neuropathology of LBD. In the current study, we examined a large series of neuropathologically confirmed LBD cases (n = 980 in the discovery series, n = 503 in the replication series) and performed genome-wide association studies of 11 different neuropathological outcome measures. The 11 neuropathological outcomes included Braak neurofibrillary tangle (NFT) stage, Thal amyloid phase, LBD subtype, Lewy body (LB) counts in five different brain regions, dorsolateral and ventromedial putaminal tyrosine hydroxylase immunoreactivity and neuronal loss in the ventrolateral part of the substantia nigra. Associations between variants and outcomes were assessed using regression models appropriate for the nature of the given neuropathological outcome and that were adjusted for age at death, sex and top principal components of genetic data. In the discovery series, APOE rs429358 (i.e. APOE ε4) was associated with a greater severity of each of Braak NFT stage [odds ratio (OR) = 3.07, P = 2.34 × 10−32], Thal amyloid phase (OR = 3.57, P = 3.28 × 10−29) and LBD subtype (OR = 1.78, P = 9.85 × 10−9), with similar findings observed in the independent replication series (Braak NFT stage, OR = 2.30, P = 2.70 × 10−11; Thal amyloid phase, OR = 3.17, P = 6.39 × 10−18; LBD subtype, OR = 2.68, P = 3.85 × 10−10). In the subgroup of cases with lower levels of Alzheimer's disease pathology (Braak NFT stage ≤ III and Thal amyloid phase ≤2), there was a strong association between APOE rs429358 and LBD subtype even when adjusting for Braak stage and Thal phase in the discovery series (n = 218, OR = 2.47, P = 0.007) and the replication series (n = 141, OR = 3.60, P = 0.006). Although additional genome-wide significant associations were identified in the discovery series between LINC01581/MCTP2 rs547411734 and lower middle frontal LB counts, between TLE3 rs3743309 and lower cingulate LB counts, and between GRIN2A/ATF7IP2 rs1097915 and lower parahippocampal LB counts, these findings were not observed in the replication series. Our results indicate that the APOE ε4 allele is the most prominent genetic determinant of severity of neuropathology in LBD. These findings represent a key step forward in our understanding of genetic drivers of neuropathological features in LBD. Future studies utilizing meta-analytical approaches will be important to more precisely assess other associations that were not quite genome-wide significant in the discovery series.