Search Results (6,899)

Objectives: Patients in cardiogenic shock (CS) may be successfully bridged using intravascular micro-axial left ventricular assist devices (M-LVADs) for recovery or determination of definitive therapy. Methods: One hundred and seven CS patients implanted with M-LVADs from January 2020 to May 2024 were divided into four groups; group-1: 34 patients (transplant); group-2: 25 patients (LVAD); group-3: 42 patients (postcardiotomy CS (PCCS)); group-4: 6 patients (decision/recovery but excluded from analysis). Multivariable logistic regression and Multivariable Coxregression models identified predictors of early -hospital and late mortality, and Odds ratios (ORs) and hazard ratios (HRs) with p < 0.05, respectively, were considered statistically significant. SPSS 29.0 and Python 3.11.1. were used for analyses. Results: Complications included device-malfunction (6%), gastrointestinal bleed (9%), long-term hemodialysis (21%), axillary hematoma requiring re-exploration (10%), heparin-induced thrombocytopenia (4%) requiring heparin therapy cessation/initiation of argatroban infusion, and non-fatal stroke (11%). Early hospital mortality included 13 patients: 2 in group-1, 1 in group-2, 10 in group-3 (p = 0.02). In the Logistic-Regression model, category of CS requiring an M-LVAD was significant (OR = 4.7, p = 0.05). Patients were followed for 4.5 years (mean follow-up was 23 ± 17 months), and 23 deaths occurred; group-1: 3 patients, group-2: 5 patients, and group-3: 15 patients (p = 0.019). At 4.5 years, actuarial survival was 90.7 ± 5.1% in group-1, 79.2 ± 8.3% in group-2, 62.8 ± 7.7% in group-3 (p = 0.01). In the Cox-Regression model, M-LVAD category (HR = 3.63, p = 0.04), and long-term postoperative dialysis (HR = 3.9, p = 0.002) emerged as predictors of long-term mortality. Conclusions: In cardiogenic shock, mid-term outcomes demonstrate good survival with M-LVADs as bridge to transplant/durable LVADs and reasonable survival with M-LVADs as a bridge to recovery following cardiotomy, accompanied by reduced ECMO usage, and early ambulation/rehabilitation. Full article

Central nervous system (CNS) cancers are responsible for high rates of morbidity and mortality worldwide. Malignant CNS tumors such as adult Glioblastoma (GBM) and pediatric embryonal CNS tumors such as medulloblastoma (MED) and atypical teratoid rhabdoid tumors (ATRT) present relevant therapeutic challenges due to the lack of response to classic treatment regimens with radio and chemotherapy. Recent findings on the Zika virus’ (ZIKV) ability to infect and kill CNS neoplastic cells draw attention to the virus’ oncolytic potential. Studies demonstrating the safety of using ZIKV for treating malignant CNS tumors, enabling the translation of this approach to clinical trials, are scarce in the literature. Here we developed a co-culture model of mature human cerebral organoids assembled with GBM, MED or ATRT tumor cells and used these assembloids to test ZIKV oncolytic effect, replication potential and preferential targeting between normal and cancer cells. Our hybrid co-culture models allowed the tracking of tumor cell growth and invasion in cerebral organoids. ZIKV replication and ensuing accumulation in the culture medium was higher in organoids co-cultured with tumor cells than in isolated control organoids without tumor cells. ZIKV infection led to a significant reduction in tumor cell proportion in organoids with GBM and MED cells, but not with ATRT. Tumoroids (3D cultures of tumor cells alone) were efficiently infected by ZIKV. Interestingly, ZIKV rapidly replicated in GBM, MED, and ATRT tumoroids reaching significantly higher viral RNA accumulation levels than co-cultures. Moreover, ZIKV infection reduced viable cells number in MED and ATRT tumoroids but not in GBM tumoroids. Altogether, our findings indicate that ZIKV has greater replication rates in aggressive CNS tumor cells than in normal human cells comprising cerebral organoids. However, such higher ZIKV replication in tumor cells does not necessarily parallels oncolytic effects, suggesting cellular intrinsic and extrinsic factors mediating tumor cell death by ZIKV. Full article

Background: Air pollution contributes to up to 60% of premature mortality worldwide by worsening cardiovascular conditions. Ultrafine particles (UFPs) may negatively affect cardiovascular outcomes, and epidemiological studies have linked them to short- and long-term blood pressure (BP) imbalance. Methods: We conducted a systematic review and meta-analysis of the short- and long-term effects of UFP exposure on systolic (SBP) and diastolic (DBP) blood pressure. Eligibility criteria were established using the Population, Exposure, Comparator, Outcome, and Study Design (PECOS) model, and literature searches were conducted in Web of Science, PubMed, Embase, and Scopus for studies published between 1 January 2013 and 9 October 2024. Risk of Bias (RoB) was assessed following World Health Organization (WHO) instructions. Separate meta-analyses were performed for the short- and long-term effects of UFP exposure on SBP and DBP. Additionally, we analyzed SBP and DBP imbalances across different timespans following short-term exposure. Results: The results showed an increase in BP during short-term UFP exposure, which returned to baseline values after a few hours. Changes in SBP were greater than in DBP following both short- and long-term exposure. Prolonged exposure to UFPs is associated with increased SBP and concurrently low DBP values. Chronic exposure to UFPs may lead to a persistent increase in SBP, even without a concurrent increase in DBP. Conclusions: The findings presented here highlight that UFPs may contribute to worsening cardiovascular outcomes in vulnerable populations living in air-polluted areas. Full article

Background: Infective endocarditis (IE) poses significant challenges in cardiovascular medicine, often necessitating valvular surgery to manage severe complications. Postoperative acute kidney injury (AKI) is a notable complication affecting patient outcomes. While clinical and procedural factors have been well studied, the role of radiological renal artery parameters in AKI risk remains underexplored. Methods: This retrospective study analyzed 80 patients with IE who underwent valvular surgery from 2013 to 2021, focusing on postoperative AKI as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Radiological parameters, including renal artery calcification, renal ostial calcification, the presence of renal infarctions, and additional arteries, were assessed using preoperative computed tomography (CT). Statistical analyses included binary logistic and linear regression models, Kaplan–Meier survival curves, and Cox proportional hazard regression to explore associations between these parameters and AKI incidence, creatinine levels, and mortality. Results: Out of 80 patients, 31 (38.8%) developed AKI. No significant differences were found in baseline characteristics or radiological parameters between the AKI+ and AKI− groups. Binary logistic and linear regression analyses revealed no substantial relationship between anatomical factors and AKI risk or creatinine levels. However, Cox regression identified “additional renal artery” as a significant predictor of 1-month mortality (HR: 1.747, 95% CI: 1.024–2.979, p = 0.041) but not for 6- or 12-month mortality. Conclusions: Radiological anatomical factors, including calcifications and additional arteries, did not significantly impact AKI risk in IE patients undergoing valvular surgery. However, the presence of additional arteries was associated with increased short-term mortality. These findings suggest the need for further research to elucidate factors contributing to AKI and mortality in this context. Full article

Despite the observed clinical benefits of nirmatrelvir/ritonavir (NMV/r), it is uncertain whether Taiwan will continue covering NMV/r for high-risk individuals with mild-to-moderate coronavirus disease 2019 (COVID-19). This analysis assessed the impact of sustained utilization of NMV/r on COVID-19-associated healthcare resource utilization (HCRU) and mortality from the Taiwanese health authority perspective (THAP). A decision tree model estimated the incremental number of clinical events associated with NMV/r utilization over a 30-day period. Model results compared (1) a base case using current rates of NMV/r from the THAP, and (2) a hypothetical scenario assuming the current supply of NMV/r is not extended in Taiwan. NMV/r utilization rates included 80% and 0% in the base case and hypothetical scenario, respectively. Outcomes included the number of hospitalizations involving a general ward (GW) stay, intensive care unit (ICU) stay, and mechanical ventilation (MV) use, as well as the number of bed days, symptom days, and hospitalization deaths. Based on epidemiologic data, 150,255 patients with COVID-19 were eligible for treatment from the THAP. In the hypothetical scenario, HCRU increased by 175% compared to the base case, including increases in hospitalizations involving GW, ICU, and MV use (differences: 2067; 623; 591, respectively), bed days (difference: 51,521), symptom days (difference: 51,714), and deaths (difference: 480). Findings indicate that sustained utilization of NMV/r from the THAP reduces the clinical burden of mild-to-moderate COVID-19 through the reduced incidence of COVID-19-related HCRU and deaths. Full article

The impact of uncertainty in information systems is difficult to assess, especially when drawing conclusions from human observation records. In this study, we investigate survival variation in a population experiencing infectious disease as a proxy to investigate uncertainty problems. Using Centers for Medicare and Medicaid Services claims, we discovered 1,543,041 HIV+ persons, 363,425 of whom were observed dying from all-cause mortality. Once aggregated by HIV status, year of birth and year of death, Age-Period-Cohort disambiguation and regression models were constructed to produce explanations of variance in survival. We used Age-Period-Cohort as an alternative method to work around under-observed features of uncertainty like infection transmission, receiver host dynamics or comorbidity noise impacting survival variation. We detected ages that have a consistent, disproportionate share of deaths independent of study year or year of birth. Variation in seasonality of mortality appeared stable in regression models; in turn, HIV cases in the United States do not have a survival gain when uncertainty is uncontrolled for. Given the information complexity issues under observed exposure and transmission, studies of infectious diseases should either include robust decedent cases, observe transmission physics or avoid drawing conclusions about survival from human observation records. Full article

Background/Objectives: Breast cancer is the most common cancer in women worldwide, requiring strategic efforts to reduce its mortality. This study aimed to develop a predictive classification model for breast cancer mortality using real-world data, including various clinical features. Methods: A total of 11,286 patients with breast cancer from the National Cancer Center were included in this study. The mortality rate of the total sample was approximately 6.2%. Propensity score matching was used to reduce bias. Several machine learning models, including extreme gradient boosting, were applied to 31 clinical features. To enhance model interpretability, we used the SHapley Additive exPlanations method. ML analyses were also performed on the samples, excluding patients who developed other cancers after breast cancer. Results: Among the ML models, the XGB model exhibited the highest discriminatory power, with an area under the curve of 0.8722 and a specificity of 0.9472. Key predictors of the mortality classification model included occurrence in other organs, age at diagnosis, N stage, T stage, curative radiation treatment, and Ki-67(%). Even after excluding patients who developed other cancers after breast cancer, the XGB model remained the best-performing, with an AUC of 0.8518 and a specificity of 0.9766. Additionally, the top predictors from SHAP were similar to the results for the overall sample. Conclusions: Our models provided excellent predictions of breast cancer mortality using real-world data from South Korea. Explainable artificial intelligence, such as SHAP, validated the clinical applicability and interpretability of these models. Full article

Background/Objectives: Patient positioning during surgery can influence intra- and postoperative complications. Therefore, we assessed the impact of the sitting and park-bench positions on anesthetic parameters and complications in neurosurgical patients. Methods and Patients: For this retrospective study, 314 adults who underwent neurosurgical procedures for posterior fossa pathologies were divided into two groups: sitting (n = 231) and park-bench (n = 83). The following data were collected, monitored, recorded, and compared: age, sex, tumor type, surgical approach, cardiovascular and respiratory complications, and postoperative surgical complications. The association of hypotension with the position was further investigated through multivariate logistic regression models by adjusting for CO₂ decrease, desaturation, and documented gas embolism. Results: The average age was significantly lower in the sitting group (55 years, interquartile range (IQR) = 43–63; female proportion = 59.74%) than in the park-bench group (62 years, IQR = 45–74; female proportion = 57.83%) (p < 0.001). Cerebellopontine angle tumors were detected in 37.23% of the patients who underwent an operation in the sitting position and in 7.26% who underwent an operation in the park-bench position (p < 0.001). Patients in the sitting position had significantly greater anesthetic complication (91.77% vs. 71.08%, p < 0.001), hypotension (61.9% vs. 16.87%), and >2 mmHg CO₂ decrease (35.06% vs. 15.66%, p < 0.001) incidences. Hypoxemia and death occurred more frequently in the park-bench group (8.43% vs. 1.73% and 6.03% vs. 1.3%, respectively). Conclusions: Compared with the park-bench position, the sitting position was associated with a greater specific anesthetic complication incidence and lower postoperative mortality rate, indicating a need for careful risk-benefit assessment when selecting each individual patient’s surgical position. Full article

Fetal growth restriction, or intrauterine growth restriction, is a common gestational condition characterized by reduced intrauterine growth. However, severe periviable fetal growth restriction is still associated with elevated perinatal mortality and morbidity. The current literature advises delivery once it is deemed that fetal compromise is evident. As uteroplacental insufficiency is the most common etiology of this condition, we hypothesize that the use of artificial ex utero systems to provide adequate nutrition and recreate the uterine environment may be a viable treatment option in this situation, even with the possibility of treating severe fetal growth restriction and prevent sequelae. There are promising experimental studies in sheep models investigating the artificial ex utero system for potential prenatal conditions, but future additional investigation is needed before translating to clinical trials in humans. Full article

Background: Osteoporosis is a metabolic bone disease with a high mortality rate due to non-traumatic fractures. The risk of osteoporosis is increasing globally due to an increasing aging population. Current therapies are limited to delaying disease progression. Recently, the need to discover foods with osteogenic activity for the prevention and treatment of osteoporosis has been emphasized. We focused on bone formation via osteoblast differentiation, considering bone formation and resorption during bone homeostasis. Rubus tozawae Nakai ex J. Y. Yang (RL, Geoje raspberry) is a deciduous subshrub that has been traditionally eaten for its fruit. Methods and Results: We identified the third subfraction of n-hexane fraction (RL-Hex-NF3) of RL, an endemic Korean plant with osteogenic activity, which increased bone density in ovariectomized mice, a representative animal model of osteoporosis, via the depletion of female hormones, which resulted from the increase in the osteoblast population. RL-Hex-NF3 induced osteoblast differentiation and the expression of osteogenic markers in MC3T3-E1 pre-osteoblasts. Seven compounds were identified from RL-Hex-NF3 using NMR spectroscopy. Of these, three compounds, namely, 3β-hydroxy-18α,19α-urs-20-en-28-oic acid, betulinic acid, and (1S,6R,7S)-muurola-4,10(14)-diene-15-ol, showed strong osteogenic activity. Conclusions: RL-Hex-NF3 and its compounds suppress bone loss via their osteogenic properties, suggesting that they could be a potent candidate to treat osteoporosis. Full article

DNA double-strand breaks (DSBs) represent one of the most severe forms of genetic damage in organisms, yet vertebrate models capable of monitoring DSBs in real-time remain scarce. BRCA1/BRCA2-containing complex subunit 3 (BRCC3), also known as BRCC36, functions within various multiprotein complexes to mediate diverse biological processes. However, the physiological role of BRCC3 in vertebrates, as well as the underlying mechanisms that govern its activity, are not well understood. To explore these questions, we generated brcc3-knockout zebrafish using CRISPR/Cas9 gene-editing technology. While brcc3 mutant zebrafish appear phenotypically normal and remain fertile, they exhibit significantly increased rates of mortality and deformity following exposure to DNA damage. Furthermore, embryos lacking Brcc3 display heightened p53 signaling, elevated γ-H2AX levels, and increased apoptosis in response to DNA-damaging agents such as ultraviolet (UV) light and Etoposide (ETO). Notably, genetic inactivation of p53 or pharmacological inhibition of Ataxia-telangiectasia mutated (ATM) activity rescues the hypersensitivity to UV and ETO observed in Brcc3-deficient embryos. These findings suggest that Brcc3 plays a critical role in DNA damage response (DDR), promoting cell survival during embryogenesis. Additionally, brcc3-null mutant zebrafish offer a promising vertebrate model for real-time monitoring of DSBs. Full article

Stroke stands as a prominent global health issue, causing considerable mortality and debilitation. It arises when cerebral blood flow is compromised, leading to irreversible brain cell damage or death. Leveraging the power of machine learning, this paper presents a systematic approach to predict stroke-patient survival based on a comprehensive set of factors. These factors include demographic attributes, medical history, lifestyle elements, and physiological metrics. An effective random sampling method is proposed to handle the highly biased data on strokes. Stroke prediction using optimized boosting machine-learning algorithms is supported with explainable AI using LIME and SHAP. This enables the models to discern intricate data patterns and establish correlations between selected features and patient survival. Through this approach, the study seeks to uncover actionable insights to guide healthcare practitioners in devising personalized treatment strategies for stroke patients. Full article

Background/Objectives: Pediatric patients with autism spectrum disorder (ASD) face unique challenges, especially amongst individuals from historically minoritized racial groups. ASD has also been associated with an increased mortality from COVID-19. This study aims to explore the differences in sociodemographic factors and health outcomes (as measured by length of stay) amongst hospitalized pediatric patients with COVID-19 infections and a diagnosis of ASD compared to individuals with a COVID-19 infection alone; Methods: We performed a retrospective cohort study examining pediatric patients (ages birth to 21) who were hospitalized with a diagnosis of ASD and COVID-19 compared to patients with a diagnosis of COVID-19 alone between January 2019 and June 2023 using Epic Systems Corporation’s Cosmos, a de-identified dataset aggregated from electronic health record data. We examined differences in demographic factors and length of stay (LOS) between groups by utilizing chi-square and Wilcoxon rank sum tests. Multiple logistic regression models were utilized to assess the association between length of stay and diagnosis; Results: A total of 21,708 distinct pediatric patients with a diagnosis of ASD and COVID-19 or COVID-19 alone were included in the analytical dataset. Patients with ASD and COVID-19, compared to patients with COVID-19 alone, had a higher proportion of individuals identifying as male and White. Patients with COVID-19 alone, compared to individuals with ASD and COVID-19, had higher proportions of individuals identifying as Black or African American. Higher proportions of individuals with ASD and COVID-19 had public insurance, compared to individuals with COVID-19 alone. Having a diagnosis of ASD and COVID, after controlling for covariates, was associated with higher odds of having a length of stay greater than the three days (cutoff value determined by the median LOS of three days) compared to having a diagnosis of COVID alone (aOR 1.19, 95% CI 1.04–1.35); Conclusions: Our study highlights the health disparities experienced during hospitalizations by pediatric patients with ASD and COVID-19. Further studies should address barriers and support health outcomes for pediatric patients with ASD. Full article

Background/Objectives: Alcohol can directly damage the liver, causing steatosis, steatohepatitis, cirrhosis, and hepatocellular cancer. The aim of this study was to examine 28-day survival in hospitalized patients with alcohol-related liver disease (ALD) cirrhosis, as well as to develop and validate a new survival prediction model. Methods: A total of 145 patients with ALD cirrhosis were included; 107 were diagnosed with acute decompensation (AD) and 38 with acute-on-chronic liver failure (ACLF). The new liver mortality inpatients (LIV-IN) score was calculated using the following variables: hepatic encephalopathy (HE), hepatorenal syndrome (HRS), ascites, systemic inflammatory response syndrome (SIRS), community-acquired infection (CAI), and fibrinogen. The diagnostic accuracy of the LIV-IN score was tested, along with the model for end-stage liver disease (MELD), model for end-stage liver disease-sodium (MELD-Na), albumin-bilirubin (ALBI), neutrophil-to-lymphocyte ratio (NLR), chronic liver failure consortium-C acute decompensation (CLIF-C AD), and chronic liver failure consortium-acute-on-chronic liver failure (CLIF-C ACLF). Results: Lethal outcome occurred in 46 (31.7%) patients. The mortality rate was higher in the ACLF group (n = 22, 57.9%) compared to the AD group (n = 24, 22.4%) (p < 0.01). The highest predictive power for short-term mortality was observed for the LIV-IN score (AUC 73.4%, p < 0.01). In patients with AD, the diagnostic accuracy of the CLIF-C AD score was better than for the LIV-IN score (AUC 0.699; p = 0.004, AUC 0.686; p = 0.007, respectively). In patients with ACLF, only the LIV-IN score had statistically significant discriminative power in predicting 28-day survival. Conclusions: The liver mortality inpatients prognostic score is a new, reliable prognostic model in predicting 28-day mortality. Full article

Ozone concentrations have increased in recent decades, and several studies have reported that long-term exposure to ozone increases the mortality risk induced by respiratory conditions. However, research on cause-specific mortality related to ozone exposure and respiratory diseases remains scarce. We constructed a retrospective cohort of 5,360,032 adults aged ≥ 65 years from the National Health Insurance Service of Republic of Korea, and death certificates were obtained from Statistics Republic of Korea to determine the cause of death between 2010 and 2019. The daily maximum 8 h average levels of ozone during the warm season annually (May–September) and other air pollutants were determined for the residential district. We analyzed the data using a time-varying Cox proportional hazards model with individual- and district-level covariates, incorporating a competing risk framework to address deaths from causes other than chronic obstructive pulmonary disease (COPD) and asthma. In our single-pollutant model with a 3-year moving average, a 1 ppb increase in ozone exposure was associated with a hazard ratio (HR) of 1.011 (95% confidence interval [CI]: 1.008–1.013) for COPD mortality and an HR of 1.016 (95% CI: 1.011–1.022) for asthma mortality. In our model adjusted for the presence of underlying diseases and district-level variables, the HRs were 1.009 (95% CI: 1.008–1.014) for COPD and 1.017 (95% CI: 1.011–1.023) for asthma, respectively. These associations remained robust in our two-pollutant model, except for NO₂ and COPD. A linear concentration–response relationship was identified between ozone concentration, COPD, and asthma mortality. In this large nationwide cohort study, long-term exposure to ozone was associated with an increased risk of death from COPD and asthma in older Korean adults. Full article