Tag: pubmed

Ren Fail. 2025 Dec;47(1):2522327. doi: 10.1080/0886022X.2025.2522327. Epub 2025 Jun 25.

ABSTRACT

BACKGROUND: Albumin is widely used for volume replacement therapy during cardiopulmonary bypass (CPB) including priming fluid, despite significant controversy over its benefits. This study aimed to examine how 20% exogenous albumin affects kidney function in patients with varying preoperative albumin levels.

METHODS: We conducted this single-center, retrospective study in 28,298 adult patients undergoing on-pump cardiac surgery between 2018 and 2023. Patients were stratified according to preoperative albumin values (g/L): ≤35 (N = 1,525), 35.1-37.5 (N = 4,115), 37.6-40 (N = 7,894), and >40 (N = 14,764). Multivariate logistic regression, propensity score matching (PSM), and an inverse probability-weighting (IPW) model were applied to evaluated the impact of 20% albumin infusion on cardiac surgery-associated acute kidney injury (CSA-AKI).

RESULTS: A total of 2,541 pairs were created after PSM: ≤ 35 g/L (307 pairs), 35.1-37.5 g/L (518 pairs), 37.6-40 g/L (743 pairs), and > 40 g/L (973 pairs). Patients with intraoperative 20% albumin infusion had a statistically higher risk of CSA-AKI in the group with preoperative albumin above 40 g/L (OR, 1.29; 95% CI, 1.07-1.57; p = 0.007) in the PSM model. This result remained significant after adjusting for the effects of potential confounding variables (OR, 1.38; 95% CI, 1.19-1.61; p < 0.001 for multivariate logistic regression; OR, 1.63; 95% CI, 1.55-1.72; p < 0.001 for IPW model). However, there was no significant association with Stage 2 and 3 CSA-AKI both for multivariable logistic regression and PSM.

CONCLUSIONS: This analysis highlights that 20% albumin infusion during on-pump cardiac surgery may increase the risk of all stages CSA-AKI in patients with preoperative albumin above 40 g/L.

PMID:40563079 | DOI:10.1080/0886022X.2025.2522327

Obes Surg. 2025 Jun 26. doi: 10.1007/s11695-025-07928-z. Online ahead of print.

ABSTRACT

BACKGROUND: Cardiovascular hemodynamics, electrophysiological characteristics, and heart anatomy are all negatively impacted by obesity. The aim of this study is to compare the impact of sleeve gastrectomy versus single anastomosis sleeve ileal bypass on cardiac functions and rhythm disturbance.

METHODS: The current study included 78 patients who were allocated into two equal groups. Group A (n = 39) underwent laparoscopic sleeve gastrectomy (LSG), while group B (n = 39) underwent single anastomosis sleeve ileal bypass (SASI). Follow-up was designed for 6 and 12 months for cardiac functions and rhythm disturbance.

RESULTS: The patients’ mean age in the current study was 41.6 ± 6.88 and 43.2 ± 7.54 in groups A and B, respectively. There was a statistically significant longer operative time in patients who underwent SASI in comparison with those who underwent LSG (P < 0.001*). The %EWL was significantly higher in the SASI group at 6 and 12 months follow-up (P < 0.001*) QTC m sec and QT dispersion were significantly decreased within and between both groups after 6 and 12 months. There was a statistically significant improvement in the rhythm disturbance in both groups, mainly in group B, reported as a decrease in the overall AF with its subtypes in both groups. There was a statistically significant increase in the E/A ratio in both groups after 6 and 12 months follow-up, with no significant difference between both groups. There was an increase in LVEF in both groups, but it did not reach a significant value.

CONCLUSIONS: LSG and SASI seem to be effective techniques in improving cardiac functions and overall AF in obese patients.

PMID:40563072 | DOI:10.1007/s11695-025-07928-z

Eur J Pediatr. 2025 Jun 26;184(7):448. doi: 10.1007/s00431-025-06260-z.

ABSTRACT

The practice of breastfeeding is universally recommended because of its beneficial short and long-term impact on maternal and child health. UNICEF and WHO are promoting a global call to action to reach the goal of 50% exclusive breastfeeding by 2025. This study aims to show the global epidemiological picture of suboptimal breastfeeding over the years and its impact on health due to diarrhea and lower respiratory tract infections. We explored non-exclusive and discontinued breastfeeding data from the Global Burden of Diseases study 2019. We compared risk-weighted prevalence (summary exposure values) and outcome measures for diarrheal diseases and lower respiratory infections (years lived with disability and years of life lost) across countries and macroareas and over time. In 2019, North America had the highest risk-weighted prevalence for non-exclusive breastfeeding (25.3 SEV) and discontinued breastfeeding (25.3 SEV). By contrast, YLDs were highest in the Middle East and North Africa (37.8 per 100,000) and YLLs in Sub-Saharan Africa (4693.2 per 100,000) due to non-exclusive breastfeeding. From 1990 to 2019, YLLs due to suboptimal breastfeeding in children under 5 years of age decreased by 70%, and the gap between high- and low-income countries also decreased (by 48% for diarrheal diseases and 13% for lower respiratory infections, comparing North America and sub-Saharan Africa). Conclusion: Policymakers around the world should recognize the gap that persists between expectations and goals and work to meet international recommendations and improve child and maternal health. What is Known: • Exclusive and prolonged breastfeeding reduces infant mortality, improves nutrition, and has lasting positive effects on health • Health policies such as the International Code of Marketing of Breastmilk Substitutes and the Baby-Friendly Hospital Initiative have not fully fostered breastfeeding practices What is New: • Over the past 30 years, progress has been made in reducing mortality and disability associated with suboptimal breastfeeding • Suboptimal breastfeeding remains widespread globally and affects high-income countries as much or more than low-income countries.

PMID:40563068 | DOI:10.1007/s00431-025-06260-z

J Neurooncol. 2025 Jun 25. doi: 10.1007/s11060-025-05140-8. Online ahead of print.

ABSTRACT

PURPOSE: Heritable genetic contributions to familial and sporadic pituitary tumorigenesis are poorly understood. There is emerging evidence that germline variants in classical cancer susceptibility genes may increase the risk of pituitary tumour development. We aimed to identify and assess the rate of pathogenic germline variants in breast and colorectal cancer susceptibility genes that may promote pituitary tumorigenesis.

METHODS: Using a next-generation sequencing panel, we analysed 26 cancer susceptibility genes in 136 patients with suspected familial or sporadic pituitary tumours. Rates of pathogenic germline variation were compared against the gnomAD database.

RESULTS: We identified nine pathogenic or likely pathogenic germline variants in eight patients, within ATM, BRCA2, CHEK2, MUTYH, MLH1 and APC. We also detected three pathogenic somatic variants in TP53 and MSH6 in two patients. Compared to the general population, more pathogenic germline variants in cancer predisposition genes were found in patients with pituitary tumours (relative rate 1.44, p = 0.46), particularly in mismatch repair genes, albeit not statistically significant. We additionally identified a trend of a larger burden of pathogenic cancer susceptibility gene variants in individuals with classical pituitary tumour predisposition pathogenic variants, compared to those without (29% vs. 4.7%, p = 0.057).

CONCLUSION: Our study provides a basis for ongoing research into the potential role of cancer susceptibility genes in driving pituitary tumorigenesis.

PMID:40563065 | DOI:10.1007/s11060-025-05140-8

J Racial Ethn Health Disparities. 2025 Jun 25. doi: 10.1007/s40615-025-02512-8. Online ahead of print.

ABSTRACT

OBJECTIVE: The objective of this study was to analyze the characteristics and utilization patterns of palliative care at the end of life among deceased gastric cancer patients, using a large-scale, representative population-based sample from US hospitals.

METHODS: A retrospective analysis was conducted on hospitalization data from the National Inpatient Sample (NIS) covering January 2016 to December 2019. The study population was identified and classified using ICD-10 codes. The objective was to examine the characteristics and disparities related to the provision of palliative care to deceased gastric cancer patients and to assess its impact on healthcare utilization, particularly total hospital charges and length of stay (LOS). Multivariate linear and logistic regression analyses were performed, with the data stratified by age, race, Charlson Comorbidity Index, insurance status, median household income, and hospital characteristics. A P-value of < 0.05 was considered statistically significant.

RESULTS: We identified 33,525 hospitalizations involving patients with gastric cancer. Among these, we identified 2475 gastric cancer patients who died in-patient, of whom 58.38% (n = 1445) received palliative care during their hospital stay at the end of their life. Multivariate linear regression analysis showed that the group receiving palliative care had significantly lower total charges ($108,144 vs. $151,425), with a mean decrease of $43,652 (95% CI – $61,441 to – $25,863, P < 0.001) compared to the group not receiving palliative care. However, there was no statistically significant difference in the adjusted length of stay between patients who received palliative care and those who did not (coefficient = – 1.00 days, 95% CI – 2.10 to 0.98, P = 0.074). Multivariate logistic regression analysis indicated that patients of Black race had lower odds of receiving palliative care compared to White patients. Patients with private insurance had higher odds of receiving palliative care compared to those with Medicare. There was no statistically significant difference in receiving palliative care based on hospital size, teaching status, or median household income.

CONCLUSION: This study reveals a significant impact and disparities in the provision of palliative care among deceased gastric cancer patients. Those who received palliative care had notably lower total hospital charges, though there was no significant difference in length of stay. Black patients and those with Medicare were less likely to receive palliative care. These findings emphasize the need for targeted interventions to ensure equitable access to palliative care. Future research should investigate the root causes of these disparities and develop strategies to enhance palliative care delivery across diverse patient populations.

PMID:40563062 | DOI:10.1007/s40615-025-02512-8

Eur Radiol. 2025 Jun 25. doi: 10.1007/s00330-025-11733-8. Online ahead of print.

ABSTRACT

OBJECTIVES: To assess whether the diagnostic performance of a commercial artificial intelligence (AI) algorithm for mammography differs between breast-level and lesion-level interpretations and to compare performance to a large population of specialised human readers.

MATERIALS AND METHODS: We retrospectively analysed 1200 mammograms from the NHS breast cancer screening programme using a commercial AI algorithm and assessments from 1258 trained human readers from the Personal Performance in Mammographic Screening (PERFORMS) external quality assurance programme. For breasts containing pathologically confirmed malignancies, a breast and lesion-level analysis was performed. The latter considered the locations of marked regions of interest for AI and humans. The highest score per lesion was recorded. For non-malignant breasts, a breast-level analysis recorded the highest score per breast. Area under the curve (AUC), sensitivity and specificity were calculated at the developer’s recommended threshold for recall. The study was designed to detect a medium-sized effect (odds ratio 3.5 or 0.29) for sensitivity.

RESULTS: The test set contained 882 non-malignant (73%) and 318 malignant breasts (27%), with 328 cancer lesions. The AI AUC was 0.942 at breast level and 0.929 at lesion level (difference -0.013, p < 0.01). The mean human AUC was 0.878 at breast level and 0.851 at lesion level (difference -0.027, p < 0.01). AI outperformed human readers at the breast and lesion level (ps < 0.01, respectively) according to the AUC.

CONCLUSION: AI’s diagnostic performance significantly decreased at the lesion level, indicating reduced accuracy in localising malignancies. However, its overall performance exceeded that of human readers.

KEY POINTS: Question AI often recalls mammography cases not recalled by humans; to understand why, we as humans must consider the regions of interest it has marked as cancerous. Findings Evaluations of AI typically occur at the breast level, but performance decreases when AI is evaluated on a lesion level. This also occurs for humans. Clinical relevance To improve human-AI collaboration, AI should be assessed at the lesion level; poor accuracy here may lead to automation bias and unnecessary patient procedures.

PMID:40563050 | DOI:10.1007/s00330-025-11733-8

J Imaging Inform Med. 2025 Jun 25. doi: 10.1007/s10278-025-01582-8. Online ahead of print.

ABSTRACT

Contemporary surgical pathology workflows often prioritize slide examination based on case registry order rather than patient risk level. As a result, high-risk cases, especially those involving malignant lesions, may be unintentionally delayed, potentially affecting patient outcomes. In this study, we present an artificial intelligence (AI)-based framework designed to efficiently screen and prioritize malignant cases by analyzing hematoxylin and eosin (H&E)-stained, low-resolution thumbnail whole-slide images (TWSIs). The proposed approach includes three key components. First, image preprocessing is performed to reduce artifacts and identify the initial tissue region. Next, a multi-task deep learning network conducts both tissue segmentation and benign-versus-malignant classification. Finally, multi-dimensional feature reconstruction is utilized to improve classification accuracy. We evaluated the performance of our framework on 334 TWSI images (746 × 1632 pixels), comprising 100 benign and 234 malignant cases. The system achieved an average inference time of 2.33 ± 0.31 s per image, along with an accuracy of 91.91%, a sensitivity of 93.59%, a specificity of 88.00%, a positive predictive value of 94.84%, and a negative predictive value of 85.56%. These results correspond to a 6.41% false negative rate. The findings suggest that applying AI-driven analysis to TWSIs can effectively expedite case triage, thereby enhancing the sorting and prioritization of surgical pathology specimens and potentially improving clinical decision-making.

PMID:40563041 | DOI:10.1007/s10278-025-01582-8

J Imaging Inform Med. 2025 Jun 25. doi: 10.1007/s10278-025-01570-y. Online ahead of print.

ABSTRACT

Brain extraction is essential in neuroimaging studies for patient privacy and optimizing computational analyses. Manual creation of 3D brain masks is labor-intensive, prompting the development of automatic computational methods. Robust quality control (QC) is hence necessary for the effective use of these methods in large-scale studies. However, previous automated QC methods have been limited in flexibility regarding algorithmic architecture and data adaptability. We introduce a novel approach inspired by a statistical outlier detection paradigm to efficiently identify potentially erroneous data. Our QC method is unsupervised, resource-efficient, and requires minimal parameter tuning. We quantitatively evaluated its performance using morphological features of brain masks generated from three automated brain extraction tools across multi-institutional pre- and post-operative brain glioblastoma MRI scans. We achieved an accuracy of 0.9 for pre- and 0.87 for post-operative scans, thus demonstrating the effectiveness of our proposed QC tool for brain extraction. Additionally, the method shows potential for other tasks where a user-defined feature space can be defined. Our novel QC approach offers significant improvements in flexibility and efficiency over previous methods. It is a valuable tool, targeting reassurance of brain masks in neuroimaging and can be adapted for other applications requiring robust QC mechanisms.

PMID:40563038 | DOI:10.1007/s10278-025-01570-y

Ann Surg Oncol. 2025 Jun 25. doi: 10.1245/s10434-025-17691-1. Online ahead of print.

NO ABSTRACT

PMID:40563032 | DOI:10.1245/s10434-025-17691-1

World J Urol. 2025 Jun 25;43(1):392. doi: 10.1007/s00345-025-05764-5.

ABSTRACT

OBJECTIVE: To investigate why retractions in academic literature have risen substantially, leading to rising concerns about research reliability and integrity. While retraction trends have been explored across disciplines, urology-specific factors remain underexamined. This study investigates 292 retracted urological publications from 2014 to 2024, focusing on open-access journals to analyze how publishing models influence retraction trends.

METHODS: A retrospective analysis of retracted urological publications was conducted using the PubMed database. The study employed 84 MeSH search terms to identify articles and categorize them by research type, journal impact factor, citation count, geographical distribution, and retraction reasons. Statistical analyses were performed to assess associations between retraction characteristics.

RESULTS: The most common reason for retraction (90.4%) was discrepancies in data availability or research description, with systematic publication manipulation accounting for 5.1%. The majority of retractions (84.5%) originated from China. Journals with higher impact factors exhibited longer recall times for retractions but no significant difference in citation count at recall.

CONCLUSION: This study highlights the increasing frequency of retractions in urology and identifies key factors influencing these trends. Geographic disparities, open-access models, and journal impact factors play significant roles. Addressing research integrity requires improved editorial oversight, standardized reporting guidelines, and enhanced detection of publication misconduct.

PMID:40563020 | DOI:10.1007/s00345-025-05764-5