Tag: pubmed

Heart Lung. 2026 Jan 8;78:102715. doi: 10.1016/j.hrtlng.2025.102715. Online ahead of print.

ABSTRACT

BACKGROUND: Despite advancements in diagnostic and therapeutic strategies, infective endocarditis (IE) remains associated with high morbidity and mortality rates. Recent studies have highlighted significant sex-related differences in the clinical presentation, management, and outcomes of IE, reporting conflicting results.

OBJECTIVES: identifying the sex-related differences of patients with IE in clinical presentation and predictors of all-cause mortality.

METHODS: We conducted a retrospective study at a high-volume surgical centre, examining 687 new cases of non-device-related IE admitted between January 2013 and November 2023. Data were collected from anonymized electronic hospital records, including demographic, clinical, echocardiographic, and microbiologic characteristics. Statistical analyses were performed to identify sex-related differences in clinical presentation and predictors of all-cause mortality.

RESULTS: Female patients represented 34% of the cohort and were significantly older than males (69.6 vs. 63.9 years, p < 0.001). Females had higher prevalence of diabetes (24.8% vs. 18.1%, p = 0.039) and hypertension (65.8% vs. 57%, p = 0.025). Mitral valve IE was more common in females (46.6% vs. 36%, p = 0.023), while males had higher incidence of spondylodiscitis (10.2% vs. 3.4%, p = 0.002). Overall mortality was higher in females, but sex was not an independent predictor of mortality at multivariable analysis.

CONCLUSION: Our study highlights important sex-based differences in IE, emphasizing the need for sex-specific approaches to diagnosis, treatment, and management. Recognizing and addressing these differences can improve outcomes for both male and female patients with IE.

PMID:41512348 | DOI:10.1016/j.hrtlng.2025.102715

Heart Lung. 2026 Jan 8;78:102701. doi: 10.1016/j.hrtlng.2025.102701. Online ahead of print.

ABSTRACT

BACKGROUND: As survival improves for people with cystic fibrosis (PwCF) in the era of CFTR modulators, cardiovascular (CV) diseases are emerging as clinically important comorbidities. Beyond age-related risks, mechanistic pathways such as systemic inflammation, chronic hypoxia, CF-related diabetes, and CFTR-related endothelial dysfunction may contribute to CV injury. However, national-level data on CV outcomes in PwCF remain limited.

OBJECTIVES: We hypothesized that primary cardiac admissions in PwCF are increasing over time and associated with worse in-hospital outcomes compared to non-cardiac admissions.

METHODS: We retrospectively analyzed adult (≥18 years) PwCF hospitalizations in the U.S. National Inpatient Sample (2016-2022). Primary cardiac admissions were defined by a principal diagnosis of atrial fibrillation (AF), heart failure (HF), or myocardial infarction (MI) using ICD-10 codes. Outcomes included in-hospital mortality, length of stay (LOS), charges, and discharge disposition. Temporal trends in cardiac admissions were modeled using negative binomial regression with an offset for total CF hospitalizations; Joinpoint regression was performed as a complementary method. Descriptive statistics and multivariable regression models adjusted for age, sex, and race were used. A p-value <0.05 was considered statistically significant.

RESULTS: Among 121,290 PwCF hospitalizations, 520 (0.43%) were for cardiac causes. PwCF with cardiac admissions were older (median 62 vs. 29 years, p < 0.001) and had more traditional CV comorbidities. Cardiac admission rates increased by 16.4% per year from 2016 to 2022 (IRR 1.16 [1.04-1.29], p = 0.009) in negative binomial regression. Joinpoint regression detected no significant inflection points and estimated a non-significant APC of 16.4% per year (95% CI 10.9-57.4, p = 0.214). Unadjusted mortality was higher for cardiac vs. non-cardiac admissions (OR 3.70, 95% CI 1.61-8.53, p = 0.002), but not significant after adjustment (OR 1.36, 95% CI 0.55-3.34, p = 0.468).

CONCLUSION: Our findings indicated higher in-hospital mortality among PwCF admitted for cardiac causes, and more discharge to nursing facilities among PwCF admitted for cardiac causes. There is a need for greater CV screening, and geriatric care in PwCF.

PMID:41512346 | DOI:10.1016/j.hrtlng.2025.102701

JMIR Aging. 2026 Jan 9;9:e73213. doi: 10.2196/73213.

ABSTRACT

BACKGROUND: The COVID-19 pandemic highlighted how restrictions on in-person interactions within long-term care homes (LTCHs) severely compromised social connectedness among older adults and their families. Post pandemic, despite policy changes supporting greater in-person family engagement, frequent outbreaks continue to disrupt face-to-face interactions, and factors such as geography, life circumstances, and health can constrain family members’ ability to make regular in-person visits. Research suggests that web-based videoconferencing technology (WVT) may be a practical solution to help older adults within LTCHs to maintain social connection in the absence of physical gathering. However, increased understanding of end user experience is lacking, and more information on LTCHs’ readiness to support and sustain WVT will be needed if this modality is to be successfully and widely implemented.

OBJECTIVE: This study aimed to understand how older adults living in LTCHs, their families, and LTCH staff members perceived the use and ease of use of WVT devices for facilitating social connectedness.

METHODS: Using a qualitative description approach, in-depth semistructured interviews were conducted with 7 older adults, 22 family members, and 10 staff across 3 LTCHs via Zoom (Zoom Communications, Inc), Microsoft Teams, or phone calls. Data were analyzed using a directed content analysis informed by the technology acceptance model.

RESULTS: Findings were structured into 3 main themes: actual system use, perceived usefulness of WVT, and perceived ease of use of WVT. Participants described using a range of WVT hardware and software to promote social connection between older adults and family members. Videoconferencing had a crucial role in supporting older adults and their family members’ positive emotional state while also enabling them to maintain life and social roles such as participating in family functions. Despite the perceived use of these tools, participants were concerned about the decline in offering videoconferencing services across LTCHs post pandemic. Some participants noted shifting funding priorities toward supporting in-person recreational activities rather than diversifying web-based social connection options. In addition, factors pertaining to WVT ease of use and integration included limited staff to support older adults with different physical and cognitive needs, variability in digital literacy including knowledge about accessibility features to enhance the ease of use, and families’ lack of awareness about the availability of WVT for social connectedness.

CONCLUSIONS: Web-based videoconferencing technology has the potential to be a meaningful tool to reduce social isolation and promote a sense of social connectedness among older adults and their families and friends. Future research should explore how WVT could be integrated into care planning for this population, particularly in situations where older adults may be at heightened risk for social isolation. Resource allocation toward equipment, infrastructure, and family and staff training would be well-placed to increase engagement with WVT within LTCHs.

PMID:41512315 | DOI:10.2196/73213

JMIR Form Res. 2026 Jan 9;10:e78484. doi: 10.2196/78484.

ABSTRACT

BACKGROUND: Cardiac arrest (CA), characterized by an extremely high mortality rate, remains one of the most pressing global public health challenges. It not only causes a substantial strain on health care systems but also severely impacts individual health outcomes. Clinical evidence demonstrates that early identification of CA significantly reduced the mortality rate. However, the developed CA prediction models exhibit limitations such as low sensitivity and high false alarm rates. Moreover, issues with model generalization remain insufficiently addressed.

OBJECTIVE: The aim of this study was to develop a real-time prediction method based on clinical vital signs, using patient vital sign data from the past 2 hours to predict whether CA would occur within the next 1 hour at 5-minute intervals, thereby enabling timely and accurate prediction of CA events. Additionally, the eICU-CRD dataset was used for external validation to assess the model’s generalization capability.

METHODS: We reviewed and analyzed 4063 patients from the MIMIC-III waveform database, extracting 6 features to develop a deep learning-based CA prediction model named TrGRU. To further enhance performance, statistical features based on a sliding window were also constructed. The TrGRU model was developed using a combination of transformer and gated recurrent unit architectures. The primary evaluation metrics for the model included accuracy, sensitivity, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC), with generalization capability validated using the eICU-CRD dataset.

RESULTS: The proposed model yielded an accuracy of 0.904, sensitivity of 0.859, AUROC of 0.957, and AUPRC of 0.949. The results showed that the predictive performance of TrGRU was superior to that of the models reported in previous studies. External validation using the eICU-CRD achieved a sensitivity of 0.813, an AUROC of 0.920, and an AUPRC of 0.848, indicating excellent generalization capability.

CONCLUSIONS: The proposed model demonstrates high sensitivity and a low false-alarm rate, enabling clinical health care providers to predict CA events in a more timely and accurate manner. The adopted meta-learning approach effectively enhances the model’s generalization capability, showcasing its promising clinical application.

PMID:41512300 | DOI:10.2196/78484

Bioinformatics. 2026 Jan 9:btag005. doi: 10.1093/bioinformatics/btag005. Online ahead of print.

ABSTRACT

MOTIVATION: The presence or absence of some genes in a genome can influence whether other genes are likely to be present or absent. Understanding these gene co-occurrence and avoidance patterns reveals fundamental principles of genome organisation, with applications ranging from evolutionary reconstruction to rational design of synthetic genomes.

IMPLEMENTATIONS: PanForest, presented here, uses random forest classifiers to predict the presence and absence of genes in genomes from the set of other genes present. Performance statistics output by PanForest reveal how predictable each gene’s presence or absence is, based on the presence or absence of other genes in the genome. Further, PanForest produces statistics indicating the importance of each gene in predicting the presence or absence of each other gene. The PanForest software can run serially or in parallel, thereby facilitating the analysis of pangenomes at Network of Life scale.

RESULTS: A pangenome of 12,741 accessory genes in 1,000 Escherichia coli genomes was analysed in around 5 hours using 8 processors. To demonstrate PanForest’s utility, we present a case study and show that certain genes associated with resistance to antimicrobial drugs reliably predict the presence or absence of other genes associated with resistance to the same drug. Further, we highlight several associations between those genes and others not known to be associated with antimicrobial resistance (AMR), or associated with resistance to other drugs. We envisage PanForest’s use in studies from multiple disciplines concerning the dynamics of gene distributions in pangenomes ranging from biomedical science and synthetic biology to molecular ecology.

AVAILABILITY: The software if freely available with a full manual and can be found with at www.github.com/alanbeavan/PanForest DOI: https://doi.org/10.5281/zenodo.17865482.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:41512299 | DOI:10.1093/bioinformatics/btag005

Bioinformatics. 2026 Jan 9:btag004. doi: 10.1093/bioinformatics/btag004. Online ahead of print.

ABSTRACT

SUMMARY: Sediment DNA–the ability to extract DNA from archaeological sediments– is an exciting new frontier in ancient DNA research, offering the potential to study individuals at a given archaeological site without destructive sampling. In recent years, several studies have demonstrated the promise of this approach by recovering hominin DNA from prehistoric sediments, including those dating back to the Middle or Late Pleistocene. However, a lack of open-source workflows for analysis of hominin sediment DNA samples poses a challenge for data processing and reproducibility of findings across studies. Here we introduce a snakemake workflow, sedimix, for processing genomic sequences from archaeological sediment DNA samples to identify hominin sequences and generate relevant summary statistics to assess the reliability of the pipeline. By performing simulations and comparing our results to two published studies with human DNA from ∼25,000 years ago (including shotgun data from a sediment sample and capture data from touch DNA recovered from a deer tooth pendant) we demonstrate that sedimix yields accurate and reliable inferences. sedimix offers a reliable and adaptable framework to aid in the analysis of sediment DNA datasets and improve reproducibility across studies.

AVAILABILITY AND IMPLEMENTATION: sedimix is available as an open-source software with the associated code, example data, and user manual with installation instructions available at https://github.com/jierui-cell/sedimix.A permanent archived version of this release is available via Zenodo: https://doi.org/10.5281/zenodo.17244854.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:41512286 | DOI:10.1093/bioinformatics/btag004

Interdiscip Cardiovasc Thorac Surg. 2026 Jan 8:ivag005. doi: 10.1093/icvts/ivag005. Online ahead of print.

ABSTRACT

OBJECTIVES: Large-scale comparative data on the perioperative safety of robotic-assisted thoracoscopic surgery and video-assisted thoracoscopic surgery in Asia are limited. We compared the perioperative outcomes of these two approaches for lung cancer.

METHODS: This retrospective study used data from the Diagnostic Procedure Combination database in Japan. We included 47,541 patients who underwent lobectomy or segmentectomy for lung cancer from 2018 to 2021 and performed multivariable analyses.

RESULTS: Among 47,541 patients, 2,835 underwent robotic-assisted thoracoscopic surgery. Perioperative mortality did not differ significantly between groups (incidence rate ratio, 1.71; 95% confidence interval, [0.88-3.33]). Robotic-assisted surgery was associated with longer anaesthesia time and a higher incidence of mechanical ventilation postoperatively (incidence rate ratio, 1.96; 95% confidence interval, [1.36-2.81]), although the absolute difference was small (Marginal risk difference, +0.52 percentage points; 95% confidence interval, +0.14 to + 0.91). No significant differences were observed in other major complications, reoperation, or hospital stay.

CONCLUSIONS: In this large, real-world Japanese cohort including the early experience with robotic surgery, overall perioperative safety was comparable between robotic-assisted and video-assisted thoracoscopic surgery, although a statistically significant but small absolute increase in postoperative ventilation was observed with the robotic approach. This association remained robust across a series of sensitivity analyses. However, it is likely influenced by unmeasured confounding. Future prospective studies should investigate specific procedural factors, including anaesthetic management, and patient selection to optimize outcomes.

PMID:41512284 | DOI:10.1093/icvts/ivag005

Int Endod J. 2026 Jan 9. doi: 10.1111/iej.70095. Online ahead of print.

ABSTRACT

OBJECTIVE: Photon-counting computed tomography (PCCT) represents a major innovation in X-ray detection technology, offering improved signal efficiency and reduced electronic noise compared with cone-beam computed tomography (CBCT), which can enhance image quality. This study aimed to evaluate the diagnostic performance of PCCT in detecting vertical root fractures (VRF), in comparison with four CBCT devices.

METHODOLOGY: Eighteen single-rooted teeth were endodontically treated, and VRF was induced in eight of them. Each tooth was individually placed into the mandibular first premolar empty socket of an anthropomorphic phantom and scanned under three conditions: without a metal post, with a nickel-chromium metal post (Ni-Cr), and with a cobalt-chromium metal post (Co-Cr) in five CT devices: the NAEOTOM Alpha PCCT (Siemens Healthineers) device and four CBCT devices (3D Accuitomo 170-Morita, Veraview X800-Morita, NewTom VGi evo-NewTom, and Carestream 9600-Carestream). The highest-resolution protocol available on each device was used, resulting in a total of 270 scans. Five experienced dentomaxillofacial radiologists independently and blindly evaluated the scans using a five-point confidence scale. Diagnostic accuracy was assessed by calculating the area under the ROC curve (AUC), sensitivity, and specificity, with results compared by two-way ANOVA with post hoc Tukey’s test (α = 0.05).

RESULTS: NewTom VGi and PCCT devices showed significantly higher AUC values than the Veraview X800, regardless of the metal post material (p < 0.05). CS9600 and PCCT devices exhibited significantly higher sensitivity values in diagnosing with Ni-Cr posts than the Accuitomo 3D and Veraview X800 devices (p < 0.05). With the Co-Cr metal post, the NewTom VGi, CS9600, and PCCT devices showed significantly higher sensitivity values compared to the Veraview X800 device (p < 0.05). There were no statistically significant differences in specificity, regardless of the CT device or metal post material (p > 0.05).

CONCLUSIONS: The NEAOTOM Alpha PCCT showed high diagnostic accuracy for VRF detection in an ex vivo model, comparable to high-resolution CBCT devices, highlighting its diagnostic performance under controlled ex vivo conditions.

PMID:41510664 | DOI:10.1111/iej.70095

Int J Gynaecol Obstet. 2026 Jan 9. doi: 10.1002/ijgo.70789. Online ahead of print.

ABSTRACT

BACKGROUND: The WHO recommends that all pregnant women receive an ultrasound (US) scan prior to 24 weeks gestation to encourage early identification of various conditions, such as fetal anomalies, multiple gestation, and placental abnormalities; however, global access to US remains limited. This has prompted many research groups to develop artificial intelligence (AI) approaches for obstetric US.

OBJECTIVE: The aim of this study was to update and synthesize current literature regarding the development of AI algorithms for obstetric US.

SEARCH STRATEGY: Methods were modified from Horgan et al. scoping review on the progress of AI algorithms for obstetric US. Our search, which encompassed papers published between 1991 and May 2022, adapted Horgan’s search strategy by replicating the search strings across PubMed, Cochrane Library, and clinicaltrials.gov databases, while also snowballing additional references.

SELECTION CRITERIA: Studies included both AI and obstetric US with a focus on one or more maternal and/or fetal conditions between January 2022 and January 2024. After removing duplicates, publications were screened for inclusion criteria based on their mention of both AI and obstetric US and a main objective assessing maternal and/or fetal conditions. Studies were excluded if they failed to mention the use of AI or obstetric ultrasound, discussed AI algorithm development, or consisted of expert opinions, reviews, and abstracts.

DATA COLLECTION AND ANALYSIS: We used Zotero to manage references and extracted data onto an Excel template. The remaining publications were reviewed for data extraction including-authors, dates, objectives, settings, and funding sources. Publications were categorized into seven main areas based on Horgan’s framework, with additional subcategories for emerging topics. Descriptive statistics summarized the data, with graphical visualizations depicting the geographic distribution of studies.

MAIN RESULTS: A total of 96 articles were included in the final results, revealing the rapid increase in the number of publications related to AI in obstetrics. The greatest proportion of studies were categorized as fetal biometry (25%) and anatomical evaluation of the fetus (20%). Studies took place across multiple regions with the greatest number in Asia (41%) and Europe (27%). A total of 22% were conducted in low- or middle-income countries (LMICs).

CONCLUSION: This scoping review demonstrates the growth and development of AI-enabled obstetric US applications. There is a wide variety of innovative applications on the horizon and implementation approaches and implications should be explored as these technologies become clinically available. We encourage development of algorithms that focus on parameters that identify conditions linked to the global burden of maternal and neonatal mortality and morbidity, such as gestational age and placental location.

PMID:41510613 | DOI:10.1002/ijgo.70789

Asia Pac J Clin Oncol. 2026 Jan 9. doi: 10.1111/ajco.70062. Online ahead of print.

ABSTRACT

BACKGROUND: Sentinel lymph node biopsy (SLNB) reduces morbidity in breast cancer (BC) surgery compared to axillary lymph node dissection. Standard tracers such as vital blue dye (VBD), methylene blue (MB), and radioisotopes (RIs) are effective but costly and logistically challenging. Gentian violet (GV), a low-cost alternative, offers a potential solution for resource-constrained settings.

METHODS: We conducted a single-center retrospective study at Cancer Foundation Hospital, analyzing 40 BC patients who underwent SLNB using GV and RI (January-December 2024). Sentinel lymph node (SLN) detection rates, concordance between GV and RI, and safety profiles were assessed. Detection was compared across tumor grade, histopathology, receptors, and chemotherapy status.

RESULTS: The median patient age was 52 years, with most patients having a BMI between 21 and 30 (72.5%). T2 tumors were the most common (60%), followed by T3 (17.5%). Stage II disease predominated (75%), and invasive ductal carcinoma (IDC) was the most frequent histological subtype (70%). Among the cohort, 60% were estrogen/progesterone receptor-positive, 22.5% were triple-positive, and 10% were triple-negative. GV dye successfully identified SLNs in 97.5% of cases, with GV detecting more nodes than RI in 32.5% of patients, while both methods identified the same number in 50% of cases. The false-negative rate for GV was 2.5%. Detection rates were consistent across tumor subtypes, grades, and receptor statuses, with no statistically significant differences (p > 0.05). Neoadjuvant chemotherapy (NACT) did not impact SLN detection (p = 0.803). GV dye exhibited a favorable safety profile, with no intraoperative or postoperative complications reported at Days 0, 3-7, and 30. No cases of staining-related reactions, dermatitis, tattooing, or skin necrosis were observed.

CONCLUSIONS: Gentian violet is a safe, effective, and affordable alternative to MB for SLNB in BC. It demonstrates high detection rates and excellent safety, particularly suitable for resource-limited settings. Larger studies are warranted to validate these findings and support broader clinical adoption.

PMID:41510595 | DOI:10.1111/ajco.70062