Citations

Purpose This study aims to explore how hospital leadership manages conflicts arising from the risks and complexities of adopting Health Information Technology (HIT). Design/methodology/approach This qualitative study uses Yin’s (2014) case study methodology, drawing on in-depth interviews with leaders from a research hospital system and a critical access hospital to develop a conceptual model of leadership’s role in managing HIT-related conflicts. Findings This study identifies 30 factors related to HIT-related conflicts. Critical access hospitals face higher risks due to resource constraints, though their impact on stakeholders is lower. Increased complexity, shaped by close-knit cultures and reliance on external networks, is offset by reduced bureaucracy, enabling quicker decision-making. Leadership in both settings uses servant leadership and similar conflict management strategies, including process, content and motivational controls. Furthermore, heightened HIT-related conflicts correlate with adoption and implementation delays, prompting proactive leadership interventions. Originality/value This research fills a gap by examining how hospital leadership mediates conflicts during HIT adoption in a research hospital system and a critical access hospital.

Background: The perioperative management of chronic aspirin therapy in patients undergoing elective brain surgery is challenging due to the risk of bleeding and thromboembolic events. Although aspirin discontinuation reduces the bleeding risk, it can increase thrombotic complications, particularly in patients at high risk of cardiovascular complications. This Delphi study aimed to develop consensus-based guidelines to address these clinical challenges. Methods: A 2-round Delphi survey was conducted among an international panel of 42 experienced anesthesiologists and neurosurgeons. Participants assessed the risks and benefits of perioperative aspirin management, including bleeding risk, thrombotic risk, timing of cessation and resumption, and the utility of platelet function testing. Consensus was defined as ≥80% agreement in round 2. Results: Round 1 highlighted significant variability in practice patterns. In round 2, consensus was reached on several key areas. Most experts (84%) agreed that continuing aspirin increases perioperative bleeding risk in high-risk procedures, with 87% recommending discontinuing aspirin 5 to 7 days before surgery. Nearly all experts (97%) supported continuing low-dose aspirin in high-thrombotic-risk patients. Conversely, for low-thrombotic-risk patients, only 65% agreed on aspirin continuation, reflecting an ongoing debate. No consensus was reached regarding routine platelet function testing. Conclusions: This Delphi study provides experience-based recommendations for managing chronic aspirin therapy in neurosurgical patients. The panel strongly supports aspirin continuation in high-thrombotic-risk patients, with cessation 5 to 7 days before high-bleeding-risk surgeries. Individualized management is advised for low-bleeding-risk procedures and low-thrombotic-risk patients. Future research should further clarify aspirin management in these groups and explore the role of platelet function testing in neurosurgical settings.

Background: The relationship between vegetation characteristics in Staphylococcus aureus infective endocarditis (IE) and blood culture time to positivity (TTP) has not been investigated. This study evaluates the correlation between vegetation length and TTP in patients with S. aureus IE. Methods: A retrospective cohort study was conducted that included 164 definite cases S. aureus IE. Vegetation length was determined by transesophageal echocardiography (TEE), and TTP was measured in hours from the initial time of blood culture incubation to positivity. Correlations between vegetation characteristics and TTP were analyzed using Spearman’s rank correlation coefficient. Results: A modest but statistically significant negative correlation was observed between vegetation length and TTP (Spearman ρ = −0.18, p = 0.020), suggesting that larger vegetations were associated with shorter TTP. No significant correlations were found for other vegetation characteristics (e.g., vegetation mobility, location, or number) and TTP. Conclusions: Larger vegetation size in S. aureus IE was associated with shorter TTP. These findings highlight the importance of vegetation size in the pathophysiology of S. aureus IE and its role in bacteremia dynamics.

Background/Objectives: Malnutrition is a prevalent yet under-recognized condition in patients with advanced chronic kidney disease (CKD), contributing to increased morbidity, mortality, and healthcare burden. The aim of this study is to determine the prevalence and trends of malnutrition and investigate the impact of malnutrition on in-hospital outcomes, treatments, and resource utilization in hospitalized patients with advanced CKD. Methods: This study utilized the National Inpatient Sample (NIS) database to identify hospitalized patients with advanced CKD from 2016 to 2021. This study investigated temporal trends in the prevalence and in-hospital mortality across different degrees of malnutrition in advanced CKD patients. Multivariable regression models were used to assess the association between malnutrition and in-hospital outcomes. Results: Out of 1,244,415 advanced CKD patients, 67,587 (5.4%) had mild to moderate malnutrition, and 63,785 (5.1%) had severe malnutrition. Malnourished patients exhibited significantly higher in-hospital mortality, with adjusted odds ratios of 1.70 (95% confidence interval (CI), 1.64–1.75) for mild to moderate cases and 2.67 (95% CI, 2.60–2.75) for severe cases. Severely malnourished patients were associated with longer mean hospital stay by 7.0 days and higher hospitalization costs by $97,767 compared with non-malnourished patients. The prevalence of severe malnutrition showed a significant uptrend from 4.2% in 2016 to 5.5% in 2021 (p for trend < 0.001). Conclusions: Malnutrition in advanced CKD is an increasingly prevalent condition linked to worsened in-hospital outcomes and heightened healthcare resource utilization. The rising trend of severe malnutrition underscores the need for early nutritional screening and the need for future interventional studies to mitigate adverse clinical outcomes in this high-risk population.

SummaryFrom a historical perspective, the treatment landscape of myelodysplastic syndromes/neoplasms (MDS) has experienced a standstill in terms of new approvals by the U.S. Food and Drug Administration up until the recent 5 years. The widespread availability of comprehensive genome sequencing has shed insight into human MDS biology toward the goal of rational therapeutic design. This new knowledge has inspired the development of investigational therapies that extend beyond the scope of traditional erythropoiesis‐stimulating agents and hypomethylating agents. We describe how these contemporary treatment options are changing the management paradigms for lower‐risk and higher‐risk MDS, based on the landmark trial data. We discuss investigational therapies in the MDS pipeline, such as venetoclax, emavusertib, canakinumab and olutasidenib. We highlight challenges and solutions to the successful translation of emerging therapies based on our improved understanding of the biology of MDS, including the genomics of MDS with mutated TP53. We discuss how the identification of biomarkers of response to therapeutics may help guide clinical trial design for certain subsets of patients. Finally, we discuss how multicentre randomized trials can help facilitate the clinical rollout of emerging MDS therapeutics.

Background The Woven EndoBridge (WEB) device is a prevalent treatment for intracranial aneurysms. While many studies have assessed the obliteration rate post-WEB embolization, few have focused on long-term outcomes in partially thrombosed aneurysms. Objective To assess whether partially thrombosed aneurysms are at higher risk of recurrence or retreatment following WEB embolization compared with non-thrombosed aneurysms. Methods We evaluated data from 22 academic institutions, focusing on previously untreated cerebral aneurysms treated with the WEB device. Logistic regression was utilized to analyze factors predicting long-term aneurysm obliteration and retreatment necessity. Results Among 1303 patients, 26 presented with a partially thrombosed aneurysm. In the partially thrombosed group, the mean aneurysm maximal diameter was 10.7±4 mm with a neck ratio of 1.99±1.19 mm, larger than in the control group where the mean aneurysm maximal diameter was 6.81±2.37 mm with a neck ratio of 1.64±0.51 mm (P<0.001 for both maximal diameter and neck ratio). At the final follow-up, partially thrombosed aneurysms treated by the WEB device had a 38.5% retreatment rate, compared with 7.0% for non-thrombosed aneurysms (P<0.001). Among partially thrombosed aneurysms, the Raymond-Roy type IIIa/b occlusion rate was higher (38.5% vs 9.9%, P<0.001). On multivariate analysis, partially thrombosed aneurysms compared with non-thrombosed aneurysms had an increased rate of retreatment (OR 3.64, 95% CI 1.28 to 10.1). Conclusion Partially thrombosed aneurysms are associated with a poorer occlusion rate and a higher rate of retreatment following WEB embolization. For partially thrombosed aneurysms, the WEB device appears suboptimal as a first-line treatment, and therefore alternative techniques should be prioritized.

Abstract Clonal hematopoiesis (CH) of indeterminate potential (CHIP), driven by somatic mutations in leukemia-associated genes, confers increased risk of hematologic malignancies, cardiovascular disease, and all-cause mortality. In blood of healthy individuals, small CH clones can expand over time to reach 2% variant allele frequency (VAF), the current threshold for CHIP. Nevertheless, reliable detection of low-VAF CHIP mutations is challenging, often relying on deep targeted sequencing. Here, we present UNISOM, a streamlined workflow for enhancing CHIP detection from whole-genome and whole-exome sequencing data that are underpowered, especially for low VAFs. UNISOM utilizes a meta-caller for variant detection, in couple with machine learning models which classify variants into CHIP, germline, and artifact. In whole-exome sequencing data, UNISOM recovered nearly 80% of the CHIP mutations identified via deep targeted sequencing in the same cohort. Applied to whole-genome sequencing data from Mayo Clinic Biobank, it recapitulated the patterns previously established in much larger cohorts, including the most frequently mutated CHIP genes and predominant mutation types and signatures, as well as strong associations of CHIP with age and smoking status. Notably, 30% of the identified CHIP mutations had &lt; 5% VAFs, demonstrating its high sensitivity toward small mutant clones. This workflow is applicable to CHIP screening in population genomic studies. The UNISOM pipeline is freely available at https://github.com/shulanmayo/UNISOM and https://ngdc.cncb.ac.cn/biocode/tool/7816.