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Malnutrition is a common co-morbidity among candidates for transcatheter aortic valve implantation (TAVI). This study aimed to investigate the association between nutritional status determined by objective nutritional indices and outcomes of patients who underwent TAVI. We systematically searched PubMed, Embase, Web of Science, Scopus, and Cochrane Library from inception until April 18, 2022 to identify studies examining the association of preprocedural nutritional status with post-TAVI outcomes. Malnutrition was defined by objective nutritional indices—controlling nutritional index, nutritional risk index, geriatric nutritional risk index (GNRI), and prognostic nutritional index (PNI). The primary end point was 1-year all-cause mortality. The review included 13 observational studies and 6,785 patients who underwent TAVI. Malnutrition was associated with a higher risk of 1-year all-cause mortality, as defined by either the controlling nutritional index (hazard ratio [HR] 2.70, 95% confidence interval [CI] 1.21 to 6.03, p = 0.015), GNRI (HR 1.79, 95% CI 1.09 to 2.93, p = 0.021), or PNI (HR 1.17, 95% CI 1.11 to 1.23, p <0.001). In the meta-analysis of adjusted results, lower GNRI was independently associated with higher 1-year mortality (HR 1.70, 95% CI 1.16 to 2.50, p = 0.006). Lower GNRI was associated with increased risk of acute kidney injury (relative risk [RR] 2.21, 95% CI 1.63 to 2.99, p <0.001) and 1-year cardiovascular mortality (RR 2.50, 95% CI 1.66 to 3.78, p <0.001). Lower PNI was associated with a higher risk of major vascular complications (RR 2.99, 95% CI 1.38 to 6.51, p = 0.006). In conclusion, baseline malnutrition, as assessed by objective indices, is associated with worse outcomes after TAVI. Future studies should focus on the value of nutritional assessment and interventions to improve nutritional status in patients who underwent TAVI.

Background The screening process for systematic reviews and meta-analyses in medical research is a labor-intensive and time-consuming task. While machine learning and deep learning have been applied to facilitate this process, these methods often require training data and user annotation. This study aims to assess the efficacy of ChatGPT, a large language model based on the Generative Pretrained Transformers (GPT) architecture, in automating the screening process for systematic reviews in radiology without the need for training data. Methods A prospective simulation study was conducted between May 2nd and 24th, 2023, comparing ChatGPT’s performance in screening abstracts against that of general physicians (GPs). A total of 1198 abstracts across three subfields of radiology were evaluated. Metrics such as sensitivity, specificity, positive and negative predictive values (PPV and NPV), workload saving, and others were employed. Statistical analyses included the Kappa coefficient for inter-rater agreement, ROC curve plotting, AUC calculation, and bootstrapping for p-values and confidence intervals. Results ChatGPT completed the screening process within an hour, while GPs took an average of 7–10 days. The AI model achieved a sensitivity of 95% and an NPV of 99%, slightly outperforming the GPs’ sensitive consensus (i.e., including records if at least one person includes them). It also exhibited remarkably low false negative counts and high workload savings, ranging from 40 to 83%. However, ChatGPT had lower specificity and PPV compared to human raters. The average Kappa agreement between ChatGPT and other raters was 0.27. Conclusions ChatGPT shows promise in automating the article screening phase of systematic reviews, achieving high sensitivity and workload savings. While not entirely replacing human expertise, it could serve as an efficient first-line screening tool, particularly in reducing the burden on human resources. Further studies are needed to fine-tune its capabilities and validate its utility across different medical subfields.

Background A few studies compared the characteristics and outcomes of COVID-19 patients during the first and second surges of the disease. We aimed to describe the clinical features and outcomes of COVID-19 patients across the first, second, and third surges of the disease in Tehran, Iran. Method We conducted a retrospective cohort study of patients with COVID-19 admitted to Sina hospital in Tehran, Iran, during three surges of COVID-19 from February 16 to October 28, 2020. Result Surge 1 patients were younger with more prevalence of hypertension. They also presented with significantly higher oxygen saturation, systolic blood pressure, and respiratory rate on admission. Patients had higher levels of neutrophil to lymphocyte ratio, Urea, CRP, and ESR, in surge 2. The incidence of dyspnea, chest pain, and neurological manifestations followed a significant increasing trend from surge 1 to surge 3. There was no difference in severity and in-hospital mortality between the surges. However, the length of hospital stays and acute cardiac injury (ACI) was less in surge 1 and acute respiratory distress syndrome (ARDS) in surge 2 than in other surges. Conclusion Patients did not significantly differ in disease severity, ICU admission, and mortality between surges; however, length of hospital stay and ACI increased during surges, and the number of patients developing ARDS was significantly less in surge 2 compared to other peaks.

Background and Aims Takotsubo syndrome (TTS), also known as stress cardiomyopathy, is characterized by acute and transient left ventricular dysfunction and has increased during the COVID‐19 pandemic. Herein, we aim to review studies on TTS that were associated with COVID‐19 infection, vaccine, and other COVID‐19‐related etiologies including psychosocial stressors. Methods We systematically searched PubMed, EMBASE, and Scopus up to May 12, 2022. We included case reports, case series, and original articles that reported at least one TTS case associated with COVID‐19, or TTS cases after receiving COVID‐19 vaccines, or TTS cases secondary to psychological stress due to the COVID‐19 pandemic. The quality assessment was conducted using the Joanna Briggs Institute checklist. Results Sixty‐seven articles including 102 cases were included. Hypertension was the most frequently accompanying comorbidity (N = 67 [65.6%]) and the mean left ventricular ejection fraction was 36.5%. Among COVID‐19 patients, the in‐hospital mortality rate was 33.3%. On the other hand, only one COVID‐19‐negative individual expired (2.3%). The most common presenting clinical symptom was dyspnea in 42 (73.6%) patients. the mean time interval from the first symptom to admission was 7.2 days. The most common chest imaging finding was ground‐glass opacity which was reported in 14 (31.1%) participants. The most common abnormalities were T‐wave inversion in 35 (43.2%) and ST‐segment elevation in 30 (37%). Brain natriuretic peptide and troponin were elevated in 94.7% and 95.9% of participants, respectively. Conclusion The TTS in patients with COVID‐19 is almost rare, whereas it could lead to a great mortality and morbidity. An individual with COVID‐19, especially an elderly woman, presented with dyspnea in addition to a rise in brain natriuretic peptide and troponin should be evaluated for TTS.

Introduction: Kidney involvement, ranging from mild hematuria and proteinuria to acute kidney injury (AKI) in patients with coronavirus disease-2019 (COVID-19), is a recent finding with various incidence rates reported among hospitalized patients with COVID-19. Given the various AKI rates and their associated risk factors, lack of AKI recovery in the majority of patients hospitalized with COVID-19, and limited data regarding AKI in patients with COVID-19 in Iran, we aim to investigate the potential risk factors for AKI development and its incidence in patients hospitalized with COVID-19. Methods: In this retrospective cohort study, we enrolled adult patients referred to the Sina Hospital, Iran, from February 20 to May 14, 2020, with either a positive PCR test or a highly susceptible chest computed tomography features consistent with COVID-19 diagnosis. AKI was defined according to the kidney disease improving global outcomes criteria, and patients were stratified based on their AKI staging. We evaluated the risk indicators associated with AKI during hospitalization besides in-hospital outcomes and recovery rate at the time of discharge. Results: We evaluated 516 patients with a mean age of 57.6 ± 16.1 years and a male-to-female ratio of 1.69 who were admitted with the COVID-19 diagnosis. AKI development was observed among 194 (37.6%) patients, comprising 61.9% patients in stage 1, 18.0% in stage 2, and 20.1% in stage 3. Out of all patients, AKI occurred in 58 (11.2%) patients during the hospital course, and 136 (26.3%) patients arrived with AKI upon admission. AKI development was positively associated with all of the in-hospital outcomes, including intensive care unit admissions, need for invasive ventilation, acute respiratory distress syndrome (ARDS), acute cardiac injury, acute liver injury, multiorgan damage, and mortality. Patients with stage 3 AKI showed a significantly higher mortality rate, ARDS, and need for invasive ventilation than other stages. After multivariable analysis, male sex (odds ratio [OR]: 11.27), chronic kidney disease (CKD) (OR: 6.89), history of hypertension (OR: 1.69), disease severity (OR: 2.27), and high urea levels (OR: 1.04) on admission were independent risk indicators of AKI development. Among 117 (28.1%) patients who experienced AKI and survived, only 33 (28.2%) patients made a recovery from the AKI, and 84 (71.8%) patients did not exhibit full recovery at the time of discharge. Discussion/Conclusion: We found that male sex, history of CKD, hypertension, disease severity, and high serum urea were independent risk factors associated with AKI in patients with COVID-19. Also, higher stages of AKI were associated with increased risk of mortality and in-hospital complications. Our results indicate a necessity for more precise care and monitoring for AKI during hospitalization in patients with COVID-19, and lack of AKI recovery at the time of discharge is a common complication in such patients.

The COVID-19 pandemic restrictions may have significant implications for patients with multiple sclerosis (MS). The objective of this study is to explore the impact of the pandemic on physical activity levels and health outcomes among MS patients, as well as to examine potential associations between these factors. In this cross-sectional study, 197 patients with confirmed MS diagnosis were included. Physical activity and health status were assessed using international physical activity questionnaire-long form (IPAQ-LF) and short form 36 health survey questionnaire (SF-36) during the period of restrictions. The relationship between clinical characteristics, physical activity levels and health status parameters were examined. A total of 45 participants (22.8%) scored low, 73 (37.1%) scored moderate, and 79 (49.1%) achieved a high level of physical activity during the COVID-19 pandemic. We observed no significant association between total physical activity and any domains of SF-36 health status, except for pain. However, correlations were found between IPAQ and SF-36 domains. Specifically, walking showed positive correlations with physical functioning, physical limitation, general health, and physical component summary score. Vigorous activity demonstrated a negative correlation with social functioning, while moderate activity displayed a positive correlation with energy levels. Despite the challenges of home isolation and quarantine, most of our participants managed to achieve a moderate to high level of physical activity, while their overall health status was found to be moderate. Additionally, significant correlations were identified between the domains of health status and different types of physical activity, particularly walking. Further studies are warranted to optimize the care and support provided to patients with MS.

Background Most premature and very low birthweight infants cannot tolerate breast milk feeding in the first few days of life and are deprived of its benefits. This study evaluates the clinical outcomes of administering breast milk cell fractions to neonates with a birthweight of ≤1800 g. Methods We conducted a randomized controlled trial on 156 infants in the neonatal intensive care unit of Mahdieh Maternity Hospital in Tehran, Iran, from May 2019 to April 2020. All neonates with a birthweight ≤1800 g were enrolled and divided into intervention and control groups using stratified block randomization. Neonates in the intervention group received the extracted breast milk cell fractions (BMCFs) of their own mother’s milk after being centrifuged in the first 6 to 12 h after birth. The control group received routine care, and breastfeeding was started as soon as tolerated in both groups. Study outcomes were necrotizing enterocolitis (NEC), death, and in-hospital complications. Results We divided participants into two groups: 75 neonates in the intervention group and 81 neonates in the control group. The mean birthweight of neonates was 1390.1 ± 314.4 g, and 19 (12.2%) neonates deceased during their in-hospital stay. The incidence of NEC was similar in both groups. After adjustment for possible confounders in the multivariable model, receiving BMCFs were independently associated with lower in-hospital mortality (5 [26.3%] vs. 70 (51.1%]; odds ratio (OR): 0.24; 95% confidence interval [CI] 0.07, 0.86). Also, in a subgroup analysis of neonates with birthweight less than 1500 g, in-hospital mortality was significantly lower in the intervention group (4 [9.5%] vs. 13 [30.2%]; OR: 0.24; 95% CI 0.07, 0.82). There were no differences in major complications such as bronchopulmonary dysplasia and retinopathy of prematurity between the two groups. No adverse effects occurred. Conclusions Our research demonstrated a significantly lower mortality rate in neonates (with a birthweight of ≤1800 g) who received breast milk cell fractions on the first day of life. Since this is a novel method with minimal intervention, we are looking forward to developing and evaluating this method in larger studies. Trial registration IIranian Registry of Clinical Trials. Registered 25 May 2019, IRCT20190228042868N1 .

Introduction: Since the coronavirus disease 2019 (COVID-19) pandemic, the use of angiotensin II receptor blockers (ARBs) in hypertensive patients with COVID-19 has been controversial. Following our previous study, after one year, we intended to extend our sample size and results to investigate the effects of ARBs with both in-hospital outcomes and 7-month follow-up results in patients with COVID-19. Methods: Patients with a diagnosis of COVID-19 who were admitted to Sina Hospital, Tehran, Iran, from February to October 2020 participated in this follow-up cohort study. The COVID-19 diagnosis was based on a positive polymerase chain reaction test or chest computed tomography scan according to guidelines. Patients were followed for disease severity, incurring in-hospital mortality, complications, and 7-month all-cause mortality. Results: We evaluated 1413 patients with COVID-19 in this study. After excluding 124 patients, 1289 including 561(43.5%) hypertensive patients, entered the analysis. During the study, 875(67.9%) severe disease, 227(17.6%) in-hospital mortality, and 307(23.8%) 7-month all-cause mortality were observed. After adjusting for possible confounders, ARB was not associated with severity, in-hospital and 7-month all-cause mortality, and in-hospital complications except for acute kidney injury. Discontinuation of ARBs was significantly associated with higher in-hospital mortality and 7-month all-cause mortality (both P values<0.006). We observed a better 7-month outcome in those who continued their ARBs after discharge. Conclusion: The results of this study, along with the previous studies, provide reassurance that taking ARBs is not associated with the risk of mortality, complications, and poorer outcomes in hypertensive COVID-19 patients after adjustment for possible confounders.

Background/Objectives: Transcatheter aortic valve replacement (TAVR) has been introduced as an optimal treatment for patients with severe aortic stenosis, offering a minimally invasive alternative to surgical aortic valve replacement. Predicting these outcomes following TAVR is crucial. Artificial intelligence (AI) has emerged as a promising tool for improving post-TAVR outcome prediction. In this systematic review and meta-analysis, we aim to summarize the current evidence on utilizing AI in predicting post-TAVR outcomes. Methods: A comprehensive search was conducted to evaluate the studies focused on TAVR that applied AI methods for risk stratification. We assessed various ML algorithms, including random forests, neural networks, extreme gradient boosting, and support vector machines. Model performance metrics—recall, area under the curve (AUC), and accuracy—were collected with 95% confidence intervals (CIs). A random-effects meta-analysis was conducted to pool effect estimates. Results: We included 43 studies evaluating 366,269 patients (mean age 80 ± 8.25; 52.9% men) following TAVR. Meta-analyses for AI model performances demonstrated the following results: all-cause mortality (AUC = 0.78 (0.74–0.82), accuracy = 0.81 (0.69–0.89), and recall = 0.90 (0.70–0.97); permanent pacemaker implantation or new left bundle branch block (AUC = 0.75 (0.68–0.82), accuracy = 0.73 (0.59–0.84), and recall = 0.87 (0.50–0.98)); valve-related dysfunction (AUC = 0.73 (0.62–0.84), accuracy = 0.79 (0.57–0.91), and recall = 0.54 (0.26–0.80)); and major adverse cardiovascular events (AUC = 0.79 (0.67–0.92)). Subgroup analyses based on the model development approaches indicated that models incorporating baseline clinical data, imaging, and biomarker information enhanced predictive performance. Conclusions: AI-based risk prediction for TAVR complications has demonstrated promising performance. However, it is necessary to evaluate the efficiency of the aforementioned models in external validation datasets.