Improving 1-Year Mortality Following Intensive Care Unit Admission in Adults with HIV: A 20-Year Observational Study.

BACKGROUND: Despite widespread use of combination antiretroviral therapy, people with HIV (PWH) continue to have an increased risk of admission to and mortality in the intensive care unit (ICU). Mortality risk after hospital discharge is not well described. Using retrospective data on adult PWH (≥18 years) admitted to ICU from 2000-2019 in an HIV-referral centre, we describe trends in 1-year mortality after ICU admission. METHODS: One-year mortality was calculated from index ICU admission to date of death; with follow-up right-censored at day 365 for people remaining alive at 1 year, or day 7 after ICU discharge if lost-to-follow-up after hospital discharge. Cox regression was used to describe the association with calendar year before and after adjustment for patient characteristics (age, sex, Acute Physiology and Chronic Health Evaluation II [APACHE II] score, CD4+ T-cell count, and recent HIV diagnosis) at ICU admission. Analyses were additionally restricted to those discharged alive from ICU using a left-truncated design, with further adjustment for respiratory failure at ICU admission in these analyses. RESULTS: Two hundred and twenty-one PWH were admitted to ICU (72% male, median [interquartile range] age 45 [38-53] years) of whom 108 died within 1-year (cumulative 1-year survival: 50%). Overall, the hazard of 1-year mortality was decreased by 10% per year (crude hazard ratio (HR): 0.90 (95% confidence interval: 0.87-0.93)); the association was reduced to 7% per year (adjusted HR: 0.93 (0.89-0.98)) after adjustment. Conclusions were similar among the subset of 136 patients discharged alive (unadjusted: 0.91 (0.84-0.98); adjusted 0.92 (0.84, 1.02)). CONCLUSIONS: Between 2000 and 2019, 1-year mortality after ICU admission declined at this ICU. Our findings highlight the need for multi-centre studies and the importance of continued engagement in care after hospital discharge among PWH.

Sex Differences in Muscle Morphology between Male and Female Sprinters.

There is a marked difference between males and females in sprint running performance, yet a comprehensive investigation of sex differences in the muscle morphology of sprinters remains to completed. This study compared muscle volumes of 23 individual leg muscles/compartments and five functional muscle groups, assessed with 3T magnetic resonance imaging, between male (n=31) and female (n=22) sprinters, and sub-groups of elite males (EM, n=5), elite females (EF, n=5), and performance matched (to elite females) males (PMMEF, n=6). Differences in muscle volume distribution between EM, EF and unathletic male controls (UM) were also assessed. For the full sprint cohorts, males were more muscular than females, but the differences were non-uniform and anatomically variable, with the largest differences in the hip extensors and flexors. However, amongst elite sprinters the sex differences in the volume of the functional muscle groups were almost uniform (absolute volume +47-53%), and the muscle volume distribution of EM was more similar to EF than UM (P<0.039). For PMMEF relative hip extensor volume, but not stature or percent body fat, differentiated for performance (PMMEF and EF < EM) rather than sex. In conclusion, whilst the full cohorts of sprinters showed a marked sex difference in the amount and distribution of muscle mass, elite sprinters appeared to be selected for a common muscle distribution phenotype that for these elite sub-groups was a stronger effect than that of sex. Relative hip extensor muscle volume appeared to be the primary determinant of the sex difference in performance.

Self-reported exercise activity influences the relationship between coronary computed tomography angiographic finding and mortality.

AIM: Recent studies suggest that the application of exercise activity questionnaires, including the use of a single-item exercise question, can be additive to the prognostic efficacy of imaging findings. This study aims to evaluate the prognostic efficacy of exercise activity in patients undergoing coronary computed tomography angiography (CCTA). METHODS AND RESULTS: We assessed 9772 patients who underwent CCTA at a single center between 2007 and 2020. Patients were divided into 4 groups of physical activity as no exercise (n â€‹= â€‹1643, 17%), mild exercise (n â€‹= â€‹3156, 32%), moderate exercise (n â€‹= â€‹3542, 36%), and high exercise (n â€‹= â€‹1431,15%), based on a single-item self-reported questionnaire. Coronary stenosis was categorized as no (0%), non-obstructive (1-49%), borderline (50-69%), and obstructive (≥70%). During a median follow-up of 4.64 (IQR 1.53-7.89) years, 490 (7.6%) died. There was a stepwise inverse relationship between exercise activity and mortality (p â€‹< â€‹0.001). Compared with the high activity group, the no activity group had a 3-fold higher mortality risk (HR: 3.3, 95%CI (1.94-5.63), p â€‹< â€‹0.001) after adjustment for age, clinical risk factors, symptoms, and statin use. For any level of CCTA stenosis, mortality rates were inversely associated with the degree of patients' exercise activity. The risk of all-cause mortality was similar among the patients with obstructive stenosis with high exercise versus those with no coronary stenosis but no exercise activity (p â€‹= â€‹0.912). CONCLUSION: Physical activity as assessed by a single-item self-reported questionnaire is a strong stepwise inverse predictor of mortality risk among patients undergoing CCTA.

Debamestrocel multimodal effects on biomarker pathways in amyotrophic lateral sclerosis are linked to clinical outcomes.

INTRODUCTION/AIMS: Biomarkers have shown promise in amyotrophic lateral sclerosis (ALS) research, but the quest for reliable biomarkers remains active. This study evaluates the effect of debamestrocel on cerebrospinal fluid (CSF) biomarkers, an exploratory endpoint. METHODS: A total of 196 participants randomly received debamestrocel or placebo. Seven CSF samples were to be collected from all participants. Forty-five biomarkers were analyzed in the overall study and by two subgroups characterized by the ALS Functional Rating Scale-Revised (ALSFRS-R). A prespecified model was employed to predict clinical outcomes leveraging biomarkers and disease characteristics. Causal inference was used to analyze relationships between neurofilament light chain (NfL) and ALSFRS-R. RESULTS: We observed significant changes with debamestrocel in 64% of the biomarkers studied, spanning pathways implicated in ALS pathology (63% neuroinflammation, 50% neurodegeneration, and 89% neuroprotection). Biomarker changes with debamestrocel show biological activity in trial participants, including those with advanced ALS. CSF biomarkers were predictive of clinical outcomes in debamestrocel-treated participants (baseline NfL, baseline latency-associated peptide/transforming growth factor beta1 [LAP/TGFß1], change galectin-1, all p < .01), with baseline NfL and LAP/TGFß1 remaining (p < .05) when disease characteristics (p < .005) were incorporated. Change from baseline to the last measurement showed debamestrocel-driven reductions in NfL were associated with less decline in ALSFRS-R. Debamestrocel significantly reduced NfL from baseline compared with placebo (11% vs. 1.6%, p = .037). DISCUSSION: Following debamestrocel treatment, many biomarkers showed increases (anti-inflammatory/neuroprotective) or decreases (inflammatory/neurodegenerative) suggesting a possible treatment effect. Neuroinflammatory and neuroprotective biomarkers were predictive of clinical response, suggesting a potential multimodal mechanism of action. These results offer preliminary insights that need to be confirmed.

Pulmonary Vascular Disease in Veterans with Post-Deployment Respiratory Syndrome.

Exertional dyspnea has been documented in U.S. military personnel after deployment to Iraq and Afghanistan. We studied whether continued exertional dyspnea in this patient population is associated with pulmonary vascular disease (PVD). We performed detailed histomorphometry of pulmonary vasculature in 52 Veterans with biopsy-proven post-deployment respiratory syndrome (PDRS) and then recruited five of these same Veterans with continued exertional dyspnea to undergo a follow-up clinical evaluation, including symptom questionnaire, pulmonary function testing, surface echocardiography, and right heart catheterization (RHC). Morphometric evaluation of pulmonary arteries showed significantly increased intima and media thicknesses, along with collagen deposition (fibrosis), in Veterans with PDRS compared to non-diseased (ND) controls. In addition, pulmonary veins in PDRS showed increased intima and adventitia thicknesses with prominent collagen deposition compared to controls. Of the five Veterans involved in our clinical follow-up study, three had borderline or overt right ventricle (RV) enlargement by echocardiography and evidence of pulmonary hypertension (PH) on RHC. Together, our studies suggest that PVD with predominant venular fibrosis is common in PDRS and development of pulmonary hypertension may explain exertional dyspnea and exercise limitation in some Veterans with PDRS.

Nebulised pentamidine prophylaxis of pneumocystis pneumonia in adults accessing HIV services at royal free hospital, London.

Receipt of nebulised pentamidine in people with HIV was audited to identify if individuals were appropriately receiving nebulised pentamidine, and whether national guidelines were being followed when prophylaxis was commenced and discontinued. Of 76 people with who received nebulised pentamidine, the main indication for starting nebulised pentamidine was a co-trimoxazole adverse drug reaction. Co-trimoxazole desensitization was not attempted before starting nebulised pentamidine. The main indication for stopping nebulised pentamidine prophylaxis was when immune reconstitution occurred. This single centre audit revealed that national guidelines were being followed in most cases. The lack of information regarding the reason for starting or stopping nebulised pentamidine prophylaxis, or detail of the clinician's concerns about potential poor adherence with oral regimens of prophylaxis as a reason for choosing nebulised pentamidine prophylaxis, identifies a need for improved documentation of clinicians' decision-making. Introduction of pharmacist-led interventions/alerts using patients' electronic records, similar to those used in primary care, would enable the specialist pharmacy team to identify when and if co-trimoxazole desensitization has been offered and discussed/declined before a clinician prescribes nebulised pentamidine as well as enabling identification of those in who pentamidine prophylaxis has been continued, despite "immune reconstitution".

Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography.

Chest computed tomography is one of the most common diagnostic tests, with 15 million scans performed annually in the United States. Coronary calcium can be visualized on these scans, but other measures of cardiac risk such as atrial and ventricular volumes have classically required administration of contrast. Here we show that a fully automated pipeline, incorporating two artificial intelligence models, automatically quantifies coronary calcium, left atrial volume, left ventricular mass, and other cardiac chamber volumes in 29,687 patients from three cohorts. The model processes chamber volumes and coronary artery calcium with an end-to-end time of ~18 s, while failing to segment only 0.1% of cases. Coronary calcium, left atrial volume, and left ventricular mass index are independently associated with all-cause and cardiovascular mortality and significantly improve risk classification compared to identification of abnormalities by a radiologist. This automated approach can be integrated into clinical workflows to improve identification of abnormalities and risk stratification, allowing physicians to improve clinical decision-making.

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and imaging parameters could predict hospitalization for acute HF exacerbation in patients undergoing SPECT/CT myocardial perfusion imaging. Methods: The HF risk prediction model was developed using data from 4,766 patients who underwent SPECT/CT at a single center (internal cohort). The algorithm used clinical risk factors, stress variables, SPECT imaging parameters, and fully automated deep learning-generated calcium scores from attenuation CT scans. The model was trained and validated using repeated hold-out (10-fold cross-validation). External validation was conducted on a separate cohort of 2,912 patients. During a median follow-up of 1.9 y, 297 patients (6%) in the internal cohort were admitted for HF exacerbation. Results: The final model demonstrated a higher area under the receiver-operating-characteristic curve (0.87 ± 0.03) for predicting HF admissions than did stress left ventricular ejection fraction (0.73 ± 0.05, P < 0.0001) or a model developed using only clinical parameters (0.81 ± 0.04, P < 0.0001). These findings were confirmed in the external validation cohort (area under the receiver-operating-characteristic curve: 0.80 ± 0.04 for final model, 0.70 ± 0.06 for stress left ventricular ejection fraction, 0.72 ± 0.05 for clinical model; P < 0.001 for all). Conclusion: Integrating SPECT myocardial perfusion imaging into an artificial intelligence-based risk assessment algorithm improves the prediction of HF hospitalization. The proposed method could enable early interventions to prevent HF hospitalizations, leading to improved patient care and better outcomes.

Artificial Intelligence in Nuclear Cardiology: An Update and Future Trends.

Myocardial perfusion imaging (MPI), using either single photon emission computed tomography (SPECT) or positron emission tomography (PET), is one of the most commonly ordered cardiac imaging tests, with prominent clinical roles for disease diagnosis and risk prediction. Artificial intelligence (AI) could potentially play a role in many steps along the typical MPI workflow, from image acquisition through to clinical reporting and risk estimation. AI can be utilized to improve image quality, reducing radiation exposure and image acquisition times. Once images are acquired, AI can help optimize motion correction and image registration during image reconstruction or provide direct image attenuation correction. Utilizing these image sets, AI can segment a number of anatomic features from associated computed tomographic imaging or even generate synthetic attenuation imaging. Lastly, AI may play an important role in disease diagnosis or risk prediction by combining the large number of potentially important clinical, stress, and imaging-related variables. This review will focus on the most recent developments in the field, providing clinicians and researchers with a timely update on the field. Additionally, it will discuss future trends including applications of AI during multiple points of the typical MPI workflow to maximize clinical utility and methods to maximize the information that can be obtained from hybrid imaging.

AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging.

BACKGROUND: Computed tomography attenuation correction (CTAC) improves perfusion quantification of hybrid myocardial perfusion imaging by correcting for attenuation artifacts. Artificial intelligence (AI) can automatically measure coronary artery calcium (CAC) from CTAC to improve risk prediction but could potentially derive additional anatomic features. OBJECTIVES: The authors evaluated AI-based derivation of cardiac anatomy from CTAC and assessed its added prognostic utility. METHODS: The authors considered consecutive patients without known coronary artery disease who underwent single-photon emission computed tomography/computed tomography (CT) myocardial perfusion imaging at 3 separate centers. Previously validated AI models were used to segment CAC and cardiac structures (left atrium, left ventricle, right atrium, right ventricular volume, and left ventricular [LV] mass) from CTAC. They evaluated associations with major adverse cardiovascular events (MACEs), which included death, myocardial infarction, unstable angina, or revascularization. RESULTS: In total, 7,613 patients were included with a median age of 64 years. During a median follow-up of 2.4 years (IQR: 1.3-3.4 years), MACEs occurred in 1,045 (13.7%) patients. Fully automated AI processing took an average of 6.2 ± 0.2 seconds for CAC and 15.8 ± 3.2 seconds for cardiac volumes and LV mass. Patients in the highest quartile of LV mass and left atrium, LV, right atrium, and right ventricular volume were at significantly increased risk of MACEs compared to patients in the lowest quartile, with HR ranging from 1.46 to 3.31. The addition of all CT-based volumes and CT-based LV mass improved the continuous net reclassification index by 23.1%. CONCLUSIONS: AI can automatically derive LV mass and cardiac chamber volumes from CT attenuation imaging, significantly improving cardiovascular risk assessment for hybrid perfusion imaging.

HIV outcomes during the COVID-19 pandemic in people of Black ethnicities living with HIV in England.

OBJECTIVES: To describe HIV care outcomes in people of Black ethnicities living in England during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; coronavirus disease 2019 [COVID-19]) pandemic. METHODS: This was an observational cohort study of people of self-reported Black ethnicities attending for HIV care at nine HIV clinics across England. The primary outcome was a composite of antiretroviral therapy (ART) interruption and HIV viraemia (HIV RNA ≥200 copies/mL) ascertained via self-completed questionnaires and review of medical records. We used multivariable logistic regression to explore associations between ART interruption/HIV viraemia and demographic factors, pre-pandemic HIV immunovirological control, comorbidity status, and COVID-19 disease and vaccination status. RESULTS: We included 2290 people (median age 49.3 years; 56% female; median CD4 cell count 555 cells/mm3; 92% pre-pandemic HIV RNA <200 copies/mL), of whom 302 (13%) reported one or more ART interruption, 312 (14%) had documented HIV viraemia ≥200 copies/mL, and 401 (18%) experienced the composite endpoint of ART interruption/HIV viraemia. In multivariable analysis, a pre-pandemic HIV RNA <200 copies/mL (odds ratio [OR] 0.21; 95% confidence interval [CI] 0.15-0.30) and being vaccinated against SARS-CoV-2 (OR 0.41; 95% CI 0.30-0.55) were associated with reduced odds of ART interruption/HIV viraemia; pandemic-related disruptions to HIV care were common self-reported additional factors. CONCLUSIONS: During the COVID-19 pandemic, one in six people of Black ethnicities in this HIV cohort experienced an ART interruption/HIV viraemia. Some of these episodes resulted from pandemic-related healthcare disruptions. Associations with suboptimal engagement in HIV care pre-pandemic and not being vaccinated against SARS-CoV-2 suggest that wider health beliefs and/or poor healthcare access may have been contributory factors.

Impact of cardiac size on SPECT myocardial perfusion imaging performance: Insights from the REFINE-SPECT registry.

AIMS: Variation in diagnostic performance of SPECT myocardial perfusion imaging (MPI) has been observed, yet the impact of cardiac size has not been well characterized. We assessed whether low left ventricular volume influences SPECT MPI's ability to detect obstructive coronary artery disease (CAD), and its interaction with age and sex. METHODS AND RESULTS: A total of 2,066 patients without known CAD (67% male, 64.7 ± 11.2 years) across 9 institutions underwent SPECT MPI with solid-state scanners followed by coronary angiography as part of the REgistry of Fast Myocardial Perfusion Imaging with NExt Generation SPECT. Area under receiver-operating characteristic curve (AUC) analyses evaluated performance of quantitative and visual assessments according to cardiac size (end- diastolic volume [EDV]; < 20th vs. ≥ 20th population or sex-specific percentiles), age (<75 vs. ≥ 75 years), and sex. Significantly decreased performance was observed in patients with low EDV compared to those without (AUC: population 0.72 vs. 0.78, p = 0.03; sex-specific 0.72 vs. 0.79, p = 0.01) and elderly patients compared to younger patients (AUC 0.72 vs. 0.78, p = 0.03), whereas males and females demonstrated similar AUC (0.77 vs. 0.76, p = 0.67). The reduction in accuracy attributed to lower volumes was primarily observed in males (sex-specific threshold: EDV 0.69 vs. 0.79, p = 0.01). Accordingly, a significant decrease in AUC, sensitivity, specificity, and negative predictive value for quantitative and visual assessments was noted in patients with at least two characteristics of low EDV, elderly age, or male sex. CONCLUSIONS: Detection of CAD with SPECT MPI is negatively impacted by small cardiac size, most notably in elderly and male patients.

10-year experience of utilizing a stress-first SPECT myocardial perfusion imaging.

BACKGROUND: Despite its potential benefits, the utilization of stress-only protocol in clinical practice has been limited. We report utilizing stress-first single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). METHODS: We assessed 12,472 patients who were referred for SPECT-MPI between 2013 and 2020. The temporal changes in frequency of stress-only imaging were assessed according to risk factors, mode of stress, prior coronary artery disease (CAD) history, left ventricular function, and symptom status. The clinical endpoint was all-cause mortality. RESULTS: In our lab, stress/rest SPECT-MPI in place of rest/stress SPECT-MPI was first introduced in November 2011 and was performed more commonly than rest/stress imaging after 2013. Stress-only SPECT-MPI scanning has been performed in 30-34% of our SPECT-MPI studies since 2013 (i.e.. 31.7% in 2013 and 33.6% in 2020). During the study period, we routinely used two-position imaging (additional prone or upright imaging) to reduce attenuation and motion artifact and introduced SPECT/CT scanner in 2018. The rate of stress-only study remained consistent before and after implementing the SPECT/CT scanner. The frequency of stress-only imaging was 43% among patients without a history of prior CAD and 19% among those with a prior CAD history. Among patients undergoing treadmill exercise, the frequency of stress-only imaging was 48%, while 32% among patients undergoing pharmacologic stress test. In multivariate Cox analysis, there was no significant difference in mortality risk between stress-only and stress/rest protocols in patients with normal SPECT-MPI results (p = 0.271). CONCLUSION: Implementation of a stress-first imaging protocol has consistently resulted in safe cancellation of 30% of rest SPECT-MPI studies.

AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging.

Epicardial adipose tissue (EAT) volume and attenuation are associated with cardiovascular risk, but manual annotation is time-consuming. We evaluated whether automated deep learning-based EAT measurements from ungated computed tomography (CT) are associated with death or myocardial infarction (MI). We included 8781 patients from 4 sites without known coronary artery disease who underwent hybrid myocardial perfusion imaging. Of those, 500 patients from one site were used for model training and validation, with the remaining patients held out for testing (n = 3511 internal testing, n = 4770 external testing). We modified an existing deep learning model to first identify the cardiac silhouette, then automatically segment EAT based on attenuation thresholds. Deep learning EAT measurements were obtained in <2 s compared to 15 min for expert annotations. There was excellent agreement between EAT attenuation (Spearman correlation 0.90 internal, 0.82 external) and volume (Spearman correlation 0.90 internal, 0.91 external) by deep learning and expert segmentation in all 3 sites (Spearman correlation 0.90-0.98). During median follow-up of 2.7 years (IQR 1.6-4.9), 565 patients experienced death or MI. Elevated EAT volume and attenuation were independently associated with an increased risk of death or MI after adjustment for relevant confounders. Deep learning can automatically measure EAT volume and attenuation from low-dose, ungated CT with excellent correlation with expert annotations, but in a fraction of the time. EAT measurements offer additional prognostic insights within the context of hybrid perfusion imaging.

A family of olfactory receptors uniquely expanded in marsupial and monotreme genomes are expressed by a T cell subset also unique to marsupials and monotremes.

Olfactory receptors (OR), expressed on olfactory neurons, mediate the sense of smell. Recently, OR have also been shown to be expressed in non-olfactory tissues, including cells of the immune system. An analysis of single-cell transcriptomes of splenocytes of the grey short-tailed opossum (Monodelphis domestica) found OR are expressed on a subset of T cells, the γµ T cells, that are unique to marsupials and monotremes. A majority of opossum γµ T cells transcriptomes contain OR family 14 transcripts, specifically, from the OR14C subfamily. Amongst the mammals, the OR14 gene family is expanded in the genomes of marsupials and monotremes, and rarer or absent in placental mammals. In summary, here we demonstrate the intriguing correlation that a family of OR genes, abundant in the genomes of marsupials and monotremes, are ectopically expressed in a particular subset of T cells unique to the marsupials and monotremes.

A phenotypic screening platform for identifying chemical modulators of astrocyte reactivity.

Disease, injury and aging induce pathological reactive astrocyte states that contribute to neurodegeneration. Modulating reactive astrocytes therefore represent an attractive therapeutic strategy. Here we describe the development of an astrocyte phenotypic screening platform for identifying chemical modulators of astrocyte reactivity. Leveraging this platform for chemical screening, we identify histone deacetylase 3 (HDAC3) inhibitors as effective suppressors of pathological astrocyte reactivity. We demonstrate that HDAC3 inhibition reduces molecular and functional characteristics of reactive astrocytes in vitro. Transcriptional and chromatin mapping studies show that HDAC3 inhibition disarms pathological astrocyte gene expression and function while promoting the expression of genes associated with beneficial astrocytes. Administration of RGFP966, a small molecule HDAC3 inhibitor, blocks reactive astrocyte formation and promotes neuroprotection in vivo in mice. Collectively, these results establish a platform for discovering modulators of reactive astrocyte states, inform the mechanisms that control astrocyte reactivity and demonstrate the therapeutic benefits of modulating astrocyte reactivity for neurodegenerative diseases.

Pulmonary endemic mycoses.

While rare, the likelihood of encountering a case of a pulmonary endemic mycosis (PEM) in the UK is increasing. Diagnosis may be challenging, often leading to considerable delay to appropriate treatment. Clinical suspicion must be present for respiratory disease, particularly in the immunocompromised or in those not responding to empiric treatment approaches, and an extended travel history should be obtained. This article summarises the epidemiology of PEM, key clinical features, diagnostic strategies and management.