Journal of Investigative Medicine最新文献

Advances in human immunodeficiency virus (HIV) treatment, including combination antiretroviral therapy (cART), have transformed HIV into a chronic condition. Kidney diseases cause morbidity and mortality in patients living with HIV (PLWH), though cART has permitted kidney transplants with acceptable post-transplant graft and patient survival. Risk of allograft rejection remains high, which may be related to interactions between cART, specifically protease inhibitors (PI), and immunosuppressants prescribed post-transplant. This systematic review evaluates renal transplant outcomes in PLWH treated with PI- vs non-PI-based cART. A search strategy was generated with terms related to renal transplant, HIV, and cART and run on PubMed, Embase, Scopus, and Cochrane. Studies were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines on Covidence by two reviewers and then evaluated for bias. Of 803 studies, 9 were included. Included papers were prospective or retrospective cohort studies or chart reviews of adult patients. Outcome measures included acute graft rejection, graft survival, and patient survival. One study had significant results demonstrating that PI-based therapy was correlated with increased graft rejection rates. Two studies demonstrated significant graft survival benefit to non-PI-based therapy, while one demonstrated significant benefit to PI-based therapy. Two studies found significant patient survival benefit to non-PI-based therapy. For each outcome measure, remaining data suggested improved outcomes with non-PI-based therapies without achieving statistical significance. The results demonstrate superior outcomes in PLWH taking non-PI-based cART, though the paucity of significant results suggests that PLWH who require PI-based cART for virological control may continue their regimen safely post-kidney transplant.

Point-of-care tools to assess advanced liver fibrosis, including the NFS, BARD, FIB-4, and APRI, are of major interest due to their noninvasive nature. However, these tools have not been investigated extensively in the Latina population. Given that the highest rate of NAFLD in Latinos and the most severe presentation of non-alcoholic fatty liver disease (NAFLD) is more common in women, we hypothesize that ethnicity may play a role in predicting liver fibrosis, particularly in women. We determined whether ethnicity alone or in association with other parameters can predict the severity of fibrosis in women with NAFLD when included in four tools. We retrospectively included 562 Latina and 133 White Caucasian women with a history of NAFLD. Associations between ethnicity and liver fibrosis severity using the four fibrosis predictor models were studied using backward selection multinomial logistic regression. Latina women compared to White showed lower body mass index (p < 0.001), higher HbA1c (p < 0.001), lower prevalence of bariatric surgery (p < 0.001), lower likelihood to smoke (p = 0.003), and higher prevalence of chronic kidney disease stages 3-5 (p = 0.01). Some clinical variables were associated with fibrosis but not univocally in each tool. We did not find differences in the outcome of the four models when holding all other factors and examining ethnicity alone between Latina and White women. Although we did not include data on liver histology, this is the first study examining the role of ethnicity in predicting the severity of fibrosis using established noninvasive scores and documenting no association between Latina ethnicity and the severity of fibrosis in women with NAFLD.

Acinetobacter baumannii, a notable drug-resistant bacterium, often induces severe infections in healthcare settings, prompting a deeper exploration of treatment alternatives due to escalating carbapenem resistance. This study meticulously examined clinical, microbiological, and molecular aspects related to in-hospital mortality in patients with carbapenem-resistant A. baumannii (CRAB) bloodstream infections (BSIs). From 292 isolates, 153 cases were scrutinized, reidentified through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), and evaluated for antimicrobial susceptibility and carbapenemase genes via multiplex polymerase chain reaction (PCR). Utilizing supervised machine learning, the study constructed models to predict 14- and 30-day mortality rates, revealing the Naïve Bayes model's superior specificity (0.75) and area under the curve (0.822) for 14-day mortality, and the Random Forest model's impressive recall (0.85) for 30-day mortality. These models delineated eight and nine significant features for 14- and 30-day mortality predictions, respectively, with "septic shock" as a pivotal variable. Additional variables such as neutropenia with neutropenic days prior to sepsis, mechanical ventilator support, chronic kidney disease, and heart failure were also identified as ranking features. However, empirical antibiotic therapy appropriateness and specific microbiological data had minimal predictive efficacy. This research offers foundational data for assessing mortality risks associated with CRAB BSI and underscores the importance of stringent infection control practices in the wake of the scarcity of new effective antibiotics against resistant strains. The advanced models and insights generated in this study serve as significant resources for managing the repercussions of A. baumannii infections, contributing substantially to the clinical understanding and management of such infections in healthcare environments.

Patients with heart failure with reduced ejection fraction (HFrEF) are at risk for chronic kidney disease (CKD). Elevated levels of circulating biomarkers soluble urokinase plasminogen activator receptor (suPAR), galectin-3, soluble suppression of tumorigenicity 2 (ST2), and N-terminal prohormone B-type natriuretic peptide (NT-proBNP) are associated with CKD progression and mortality. The predictive value of these biomarkers in a population with HFrEF and kidney disease is relatively unknown. We sought to determine whether these biomarkers were associated with longitudinal trajectory of estimated glomerular filtration rate (eGFR) in HFrEF and assess their association with mortality using a joint model to account for competing risks of ventricular assist device (VAD) implantation and heart transplantation. We included participants from the Registry Evaluation of Vital Information for Ventricular Assist Devices in Ambulatory Life with repeated eGFR measures over 2 years. Of 309 participants, mean age was 59 years, median eGFR 60 ml/min/1.73 m², 45 participants died, 33 received VAD, and 25 received orthotopic heart transplantation. Higher baseline serum standardized suPAR (β coefficient = -0.36 √(ml/min/1.73 m²), 95% confidence interval (-0.48 to -0.24), p < 0.001), standardized galectin-3 (-0.14 √(ml/min/1.73 m²) (-0.27 to -0.02), p = 0.02), and log NT-proBNP (-0.23 √(ml/min/1.73 m²) (-0.31 to -0.15), p < 0.001) were associated with eGFR decline. ST2 and log NT-proBNP were associated with mortality. Higher baseline suPAR, galectin-3, and NT-proBNP are associated with eGFR decline in patients with HFrEF. Only ST2 and NT-proBNP are associated with greater mortality after controlling for other factors including change in eGFR. These biomarkers may provide prognostic value for kidney disease progression in HFrEF and inform candidacy for advanced heart failure therapies.

Cardiac amyloidosis (CA) is an infiltrative restrictive cardiomyopathy caused by the deposition of amyloid fibrils in the myocardium. It manifests in two primary subtypes: transthyretin cardiac amyloidosis (ATTR) and immunoglobulin light chain cardiac amyloidosis (AL). ATTR is further classified into wild-type and hereditary based on transthyretin gene mutation. Advances in diagnostics and therapeutics have transformed CA from a rare and untreatable condition to a more prevalent and manageable disease. Noninvasive diagnostic tools such as electrocardiography, echocardiography, and cardiac magnetic resonance can raise suspicion for CA; bone scintigraphy can non-invasively confirm ATTR, while AL necessitates histological confirmation. The severity of ATTR and AL can be assessed through serum biomarker-based staging. Treatment approaches differ, ranging from silencing or stabilizing transthyretin and degrading amyloid fibrils in ATTR to employing anti-plasma cell therapies and autologous stem cell transplantation in AL.

Non-Hodgkin lymphoma (NHL) is one of the most common hematological cancers in the United States. The mortality rate of NHL in the United States is the sixth highest among all cancers. Our cross-sectional study aims to examine the trends and disparity in NHL mortality. We analyzed death certificate data from the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) United States to determine the NHL mortality trends among the U.S. population aged ≥15 years. NHL (ICD-10 C82-85) was listed as the underlying cause of death. Age-adjusted mortality rates (AAMRs) per 100,000 individuals and joinpoint trend analysis were performed to determine the average annual percent change (AAPC) in AAMR trends. From 1999 to 2020, NHL accounted for 457,143 deaths in the United States, of which 54% are men and 46% are women. The NHL AAMR decreased significantly from 10.59 to 6.21 per 100,000 individuals with an AAPC of -2.55. Men had a higher AAMR than women (10.10 vs 6.29 per 100,000 individuals). Whites recorded the highest AAMR (8.43 per 100,000 individuals), followed by Hispanics (6.32 per 100,000 individuals), Blacks (5.71 per 100,000 individuals), American Indians (5.31 per 100,000 individuals), and Asians (5.10 per 100,000 individuals). Those who lived in the Midwest and the rural areas had the highest AAMR at 8.60 and 8.35 per 100,000 individuals respectively. Despite the declining NHL mortality rate, this study calls for targeted intervention to improve outcomes for susceptible individuals affected by NHL.

Generative AI (GenAI) is a disruptive technology likely to generate a major impact on faculty and learners in medical education. This work aims to measure the perception of GenAI among medical educators and to gain insights into its major advantages and concerns in medical education. A survey invitation was distributed to medical education faculty of colleges of allopathic and osteopathic medicine within a single university during the fall of 2023. The survey comprised 12 items, among those assessing the role of GenAI for students and educators, the need to modify teaching approaches, GenAI's perceived advantages, applications of GenAI in the educational context, and the concerns, challenges, and trustworthiness associated with GenAI. Responses were obtained from 48 faculty. They showed a positive attitude toward GenAI and disagreed on GenAI having a very negative effect on either the students' or faculty's educational experience. Eighty-five percent of our medical schools' faculty responded to had heard about GenAI, while 42% had not used it at all. Generating text (33%), automating repetitive tasks (19%), and creating multimedia content (17%) were some of the common utilizations of GenAI by school faculty. The majority agreed that GenAI is likely to change its role as an educator. A perceived advantage of GenAI in conducting more effective background research was reported by 54% of faculty. The greatest perceived strengths of GenAI were the ability to conduct more efficient research, task automation, and increased content accessibility. The faculty's major concerns were cheating in home assignments in assessment (97%), tendency for blunder and false information (95%), lack of context (86%), and removal of human interaction in important feedback processes (83%). The majority of the faculty agrees on the lack of guidelines for safe use of GenAI from both a governmental and an institutional policy. The main perceived challenges were cheating, the tendency of GenAI to make errors, and privacy concerns.The faculty recognized the potential impact of GenAI in medical education. Careful deliberation of the pros and cons of GenAI is needed for its effective integration into medical education. There is general agreement that plagiarism and lack of regulations are two major areas of concern. Consensus-based guidelines at the institutional and/or national level need to start to be implemented to govern the appropriate use of GenAI while maintaining ethics and transparency. Faculty responses reflect an optimistic and favorable outlook on GenAI's impact on student learning.

Multidisciplinary pulmonary embolism response teams (PERTs) have shown that timely triage expedites treatment. The use of artificial intelligence (AI) may help improve pulmonary embolism (PE) management with early CT pulmonary angiogram (CTPA) screening and accelerate PERT coordination. This study aimed to test the clinical validity of an FDA-approved PE AI algorithm. CTPA scan data of 200 patients referred due to automated AI detection of suspected PE were retrospectively reviewed. In our institution, all patients suspected of PE received a CTPA. The AI app was then used to analyze CTPA for the presence of PE and calculate the right-ventricle/left-ventricle (RV/LV) ratio. We compared the AI's output with the radiologists' report. Inclusion criteria included segmental PE with and without RV dysfunction and high-risk PE. The primary endpoint was false positive rate. Secondary end points included clinical outcomes according to the therapy selected, including catheter-directed interventions, systemic thrombolytics, and anticoagulation. Fifty-seven of 200 exams (28.5%) were correctly identified as positive for PE by the algorithm. A total of 143 exams (71.5%) were incorrectly reported as positive. In 8% of cases, PERT was consulted. Four patients (7%) received systemic thrombolytics without any complications. There were six patients (10.5%) who developed high-risk PE and underwent thrombectomy, one of whom died. Among 46 patients with acute PE without right heart strain, 44 (95%) survived. The false positive rate of our AI algorithm was 71.5%, higher than what was reported in the AI's prior clinical validity study (91% sensitivity, 100% specificity). A high rate of discordant AI auto-detection of suspected PE raises concerns about its diagnostic accuracy. This can lead to increased workloads for PERT consultants, alarm/notification fatigue, and automation bias. The AI direct notification process to the PERT team did not improve PERT triage efficacy.

The study aimed to investigate the changes in the levels of serum bone turnover markers (BTMs) and bone mineral density (BMD) Z-score in pediatric patients with osteogenesis imperfecta (OI) after intravenous bisphosphonate therapy and their association with age and estimated glomerular filtration rate (eGFR). This retrospective study analyzed data from 10 pediatric OI patients treated with intravenous zoledronic acid for over 1 year. Patients' clinical data were collected. The levels of BTMs and BMD Z-score before and after zoledronic acid treatment were analyzed. Significant improvement in BMD Z-score was observed after 6 and 12 months of treatment compared to baseline (all p < 0.05). The N-terminal propeptide of type I procollagen (PINP) levels decreased over time (all p < 0.05), indicating that zoledronic acid treatment decreased bone turnover. The levels of beta-C-terminal telopeptide of type I collagen remained stable after treatment. No correlation was found between PINP level and age, eGFR, or BMD (all p > 0.05). Bisphosphonate treatment can improve BMD and decrease bone turnover (indicated by decreased levels of PINP) in pediatric OI patients. PINP may serve as an independent indicator for monitoring the efficacy of bisphosphonate treatment in pediatric OI patients, particularly in those under the age of 6, where standardized BMD Z-score criteria are lacking.

Increasing evidence suggests that endoplasmic reticulum stress (ER stress) and neuroinflammation are involved in the complex pathological process of traumatic brain injury (TBI). However, the pathological mechanisms of their interactions in TBI remain incompletely elucidated. Therefore, investigating and ameliorating neuroinflammation and ER stress post-TBI may represent effective strategies for treating secondary brain injury. Astragaloside IV (AS-IV) has been reported as a potential neuroprotective and anti-inflammatory agent in neurological diseases. This study utilized a mouse TBI model to investigate the pathological mechanisms and crosstalk of ER stress, neuroinflammation, and microglial cell morphology in TBI, as well as the mechanisms and potential of AS-IV in improving TBI. The research revealed that post-TBI, inflammatory factors IL-6, IL-1β, and TNF-α increased, microglial cells were activated, and the specific inhibitor of PERK phosphorylation, GSK2656157, intervened to alleviate neuroinflammation and inhibit microglial cell activation. Post-TBI, levels of ER stress-related proteins (p-PERK, p-eIF2a, ATF4, ATF6, and p-IRE1a) increased. Following AS-IV treatment, neurological dysfunction in TBI mice improved. Levels of p-PERK, p-eIF2a, and ATF4 decreased, along with reductions in inflammatory factors IL-6, IL-1β, and TNF-α. Changes in microglial/macrophage M1/M2 polarization were observed. Additionally, the PERK activator CCT020312 intervention eliminated the impact of AS-IV on post-TBI inflammation and ER stress-related proteins p-PERK, p-eIF2a, and ATF4. These results indicate that AS-IV alleviates neuroinflammation and brain damage post-TBI through the PERK pathway, offering new directions and theoretical insights for TBI treatment.