Citations

Background/Objective: To externally validate our previously published machine learning model for identifying hospitalized patients with community-acquired pneumonia (CAP) at low risk of respiratory deterioration or death using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Methods: This is a retrospective cohort study of adult patients (≥18 years) who were admitted with CAP and acute hypoxemic respiratory failure using the publicly available MIMIC-IV critical care dataset (Beth Israel Deaconess Medical Center, Boston, MA). We conducted an external validation study of a previously developed gradient boosting machine (GBM) model without recalibration using data available within the first 6 h of hospital admission. Results: For the primary composite outcome (need for advanced respiratory support [high flow nasal cannula (HFNC), non-invasive mechanical ventilation (NIMV), invasive mechanical ventilation (IMV)] or in-hospital death), the gradient boosting model demonstrated comparable performance in the derivation and external validation cohorts. The area under the receiver operating characteristic curve (AUC) was 0.713 in the Mayo cohort (n = 4379) and 0.689 in the MIMIC-IV cohort. Accuracy was 0.612 (95% confidence interval [CI], 0.595–0.628) versus 0.606 (95% CI 0.600–0.611), specificity 0.574 versus 0.523, sensitivity 0.723 versus 0.754, NPV 0.860 versus 0.842, and PPV 0.364 versus 0.401, respectively. For secondary outcomes, model discrimination was comparable between cohorts. The AUC for in-hospital mortality was 0.727 in the Mayo Cohort versus 0.733 in MIMIC-IV; for IMV, 0.736 versus 0.724; and for NIMV, 0.732 versus 0.708. Conclusions: Our machine learning algorithm demonstrated good discrimination and a high negative predictive value for identifying low-risk hospitalized CAP patients for respiratory deterioration or death in the external MIMIC-IV dataset, supporting its potential utility for prognostic enrichment in pneumonia clinical trials.

Background: Rural communities face worsening surgical access because of hospital closures and workforce shortages. Although osteopathic physicians have historically practiced in rural settings, their contribution to the contemporary rural surgical workforce remains poorly defined. Study Design: Cross-sectional analysis of 74,404 US attending surgeons across seven specialties using the 2023 Centers for Medicare & Medicaid Services Doctors and Clinicians database. Practice addresses were linked to 2020 Rural-Urban Commuting Area codes, Area Deprivation Index quintiles, and census tract population density. Rural practice (mean Rural-Urban Commuting Area score ≥4) was modeled using multivariable logistic regression adjusted for specialty, graduation cohort, sex, Census division, and state urbanization, with state-clustered standard errors. Results: Rural practice was more common among DO than MD surgeons (18.3% vs 9.7%; risk difference, 8.6 percentage points; 95% CI, 7.6–9.6). Across all specialties, DO surgeons practiced in more socioeconomically deprived communities. After adjustment, DO surgeons had twice the odds of rural practice compared with MD surgeons (OR, 2.05; 95% CI, 1.85–2.28). Rural areas had 13.8 surgeons per 100,000 residents versus 23.6 per 100,000 in metropolitan areas. Surgeons graduating in 2010 or later had approximately half the odds of rural practice compared with those graduating in 1979 or earlier (adjusted OR, 0.48; 95% CI, 0.42–0.56). Conclusions: Osteopathic surgeons disproportionately practice in rural and socioeconomically disadvantaged communities, identifying an important workforce component for maintaining rural surgical access. The declining likelihood of rural practice among more recent training cohorts raises concerns regarding the future rural surgical workforce.

ABSTRACT Despite the annual increase in liver transplants, a persistent disparity between suitable donors and recipients continues to challenge the transplant community. The introduction of machine perfusion emerged as a novel approach to organ preservation. This technique, which utilizes extended criteria donor grafts, is expected to reduce rejection rates and expand the donor pool. Its principle, like that of any ex vivo machine perfusion, is based on the continuous supply of nutrients and oxygen to maintain cellular metabolism while interrupting anaerobic processes. This helps prevent conditions such as ischemia-reperfusion injury, early graft dysfunction, and ischemic cholangiopathy, which can lead to graft loss and the need for retransplantation. There are two main modes of ex vivo machine perfusion: hypothermic and normothermic, differentiated by the operating temperature. Utilizing ex situ perfusion machines presents a promising opportunity to increase liver graft usage and reduce waitlist times. However, it is crucial to evaluate how much this technology would raise the overall cost of transplants. In Brazil, implementing a machine perfusion program may encounter unique challenges not seen in other countries. These challenges include limited access to the healthcare system for high-risk liver transplant candidates, long waiting lists, inadequate support for organ donors, reliance solely on deceased brain-dead donors, since donation after cardiac death is not ethically accepted, and geographical barriers.

Spontaneous coronary artery dissection (SCAD) and Takotsubo syndrome (TTS) are two conditions presenting as acute coronary syndromes that predominantly affect women and are frequently triggered by emotional or physical stress. While traditionally considered distinct entities, emerging evidence suggests that these conditions may coexist more frequently than previously recognized, sharing common pathophysiological mechanisms centered on catecholamine-mediated pathways, vascular vulnerability, and hormonal influences. Their overlapping presentations create significant diagnostic challenges that may lead to misdiagnosis and suboptimal management. This narrative review examines the pathophysiological convergence between SCAD and TTS, addresses the diagnostic complexity arising when these entities coexist, and proposes a novel stepwise diagnostic algorithm integrating clinical risk stratification, coronary angiography, intracoronary imaging, and cardiac magnetic resonance imaging. The review also provides scenario-dependent management guidance and outlines priorities for future research.

Abstract Understanding how immune checkpoint inhibitors (ICIs) reshape human T-cell responses requires models that move beyond static transcriptomic snapshots and discrete cell-state classifications. Here, we present an integrative AI-enabled virtual cell framework that represents human CD8⁺ T-cell responses as dynamic and computable systems during ICI therapy. By integrating single-cell RNA sequencing with paired T-cell receptor sequencing within the C2S-scale foundation model, we construct a virtual representation of individual T cells, in which each cell is encoded by a unique functional identity that captures its transcriptional, signaling, and clonal characteristics. Using this framework, we identify a previously unrecognized dynamic latent effector state of CD8⁺ T cells characterized by intermediate expression of effector genes, distinct signaling activity, and ongoing clonal expansion. Across independent patient cohorts, the virtual cell model consistently indicates that ICI therapy mainly acts by unmasking pre-existing effector potential rather than inducing de novo effector differentiation. Notably, this latent effector population remains transcriptionally restrained despite active signaling and clonal expansion, revealing a hidden reservoir of antitumor immune capacity. More broadly, our study demonstrates how AI-enabled virtual cell modeling can reconstruct latent cellular states and their dynamic transitions from multidimensional single-cell data. By incorporating functional identity into virtual cell model, this framework uncovers biologically meaningful yet non-obvious T-cell effector program during cancer immunotherapy and provides a generalizable approach for studying immune dynamics in human disease.

Abstract Age‐associated muscle weakness and atrophy of limb muscles, termed sarcopenia, is a major factor in the morbidity of the elderly. It is becoming increasingly recognized that a substantial contribution to the sarcopenic phenotype arises from motor neuron (MN) death in old age and subsequent muscle denervation. In human and rodent models, mitochondrial dysfunction is a leading culprit in both muscle and MN deterioration with age. In other motor pools within the Fischer 344 (F344) aging rat model, we showed that sarcopenia is selective to type IIx/b muscle fibers. We also showed a loss of larger MNs and denervation of the IIx/b fibers, which together comprise more fatigable fast (type FF) motor units. This selective vulnerability of larger MNs and type IIx/b muscle fibers to sarcopenia is further reflected by reductions in oxidative capacity of IIx/b fibers, as assayed by determining the maximum velocity of the succinate dehydrogenase reaction (SDHmax). Here, we hypothesize similar changes will occur in F344 tibialis anterior (TA) muscle from young (6‐months) and old (24‐months) groups. We also predict lumbar MN death in young and old F344 rats. We found selective atrophy of type IIx/b fibers in the TA from old rats. In old age, SDHmax was reduced but only in IIx/b TA fibers. These muscle observations were concomitant with the death of larger lumbar MNs in old age. This study indicates the remarkable selectivity of type FF TA motor units to age‐associated perturbations and sarcopenia.

Abstract INTRODUCTION Sex differences in dementia‐related neuropathology are understudied in diverse populations. METHODS We analyzed sex differences in neuropathological and cognitive data from the Brazilian Biobank for Aging Studies. Cognitive performance was evaluated with the Clinical Dementia Rating–Sum of Boxes (CDR‐SOB). Linear and logistic regression models were conducted, including interaction terms for age, race, and education. RESULTS In 2229 participants (50.7% female, mean age ± SD 75.4 ± 12.3 years, 62.1% White), female sex was associated with a higher odds of AD pathology (Braak: odds ratio [OR] = 1.42, 95% confidence interval [CI] = 1.17–1.72; Consortium to Establish a Registry for Alzheimer's Disease (CERAD): OR = 1.58, 95% CI = 1.27–1.98), and trans‐activation response (TAR) DNA‐binding protein 43 (TDP‐43) (OR = 1.77, IC 95% = 1.22–2.59), and lower odds of Lewy body disease (OR = 0.69, 95% CI = 0.51–0.95). Female participant had worse cognitive performance ( β = 1.56, 95% CI = 1.03–2.10). Sex modified associations of Braak, CERAD, TDP‐43, and cerebral amyloid angiopathy with cognition. Age also interacted with sex and pathology on CDR‐SOB. DISCUSSION Sex differences in the associations between sex and neuropathology suggest the need for sex‐informed dementia research.

Multimodality imaging plays a pivotal role in ventricular tachycardia (VT) ablation by providing critical insights into arrhythmogenic substrates and guiding procedural strategies. This updated review explores the integration of various imaging techniques, including echocardiography, cardiac magnetic resonance (CMR), multidetector computed tomography (MDCT), electroanatomical mapping (EAM), and nuclear imaging, to optimize VT ablation outcomes. Echocardiography, particularly transthoracic echocardiography (TTE), is an essential first-line tool for evaluating structural heart disease and left ventricular function. Moreover, echocardiography aids in risk stratification and procedural planning by detecting regional wall motion abnormalities and thrombus formation. Meanwhile, intracardiac echocardiography (ICE) enhances ablation precision by providing real-time catheter visualization, improving procedural success, and reducing complications such as cardiac tamponade. Nonetheless, CMR is the gold standard for myocardial tissue characterization, enabling the identification of scar burden and conduction channels critical for VT pathogenesis. Late gadolinium enhancement (LGE) facilitates preprocedural planning by localizing arrhythmogenic substrates, predicting VT recurrence risk, and informing ablation strategies. Additionally, T1- and T2-mapping techniques refine the assessment of myocardial fibrosis and inflammation, further improving patient selection and outcomes. MDCT complements CMR by offering high-resolution anatomical visualization and aids in delineating scar distribution, epicardial fat, and vascular structures, informing safe and effective ablation approaches. The integration of these imaging modalities significantly enhances VT ablation precision, reduces recurrence rates, and improves patient outcomes.