Tag: pubmed

PLoS One. 2025 May 22;20(5):e0323619. doi: 10.1371/journal.pone.0323619. eCollection 2025.

ABSTRACT

This study investigates the determination of stratification points for two study variables within the framework of simple random sampling, with a focus on estimating the population mean using a closely related auxiliary variable. Employing a superpopulation model, the research aims to minimize overall variance by deriving simplified equations that enhance the precision of parameter estimates. Instead of categorizing variables, the study emphasizes continuous variables to establish optimal strata boundaries (OSB), which are essential for creating homogeneous groups within each stratum. This stratification leads to more efficient sample sizes (SS) and improved accuracy in parameter estimation. However, achieving optimal OSB and SS poses challenges in scenarios with a fixed total sample size, such as survey designs constrained by limited budgets. To address this, the study proposes a robust methodology for calculating OSB and SS, leveraging knowledge of the survey’s per-unit stratum measurement costs or its probability density function. An empirical application of the method is demonstrated using breast cancer data, where the mean perimeter is estimated based on mean radius and mean texture. Additionally, hypothetical examples using Cauchy and standard power distributions are provided to illustrate the versatility of the proposed approach. The newly developed method has been integrated into the updated stratifyR package and implemented in LINGO software, facilitating its practical application. Comparative analysis reveals that this approach consistently outperforms or matches existing methods in enhancing the precision of population parameter estimation. Furthermore, simulation studies confirm its higher relative efficiency, making it a valuable contribution to the field of stratified sampling.

PMID:40403232 | DOI:10.1371/journal.pone.0323619

ACS Synth Biol. 2025 May 22. doi: 10.1021/acssynbio.5c00129. Online ahead of print.

ABSTRACT

DNA logical circuits can be applied to accurate classification of cancer status, benefiting from their excellent biocompatibility and parallelism. However, the existing cancer diagnosis models based on DNA logic circuits mainly adopt a linear structure, which makes it difficult to fully capture the complex nonlinear distribution characteristics in the disease data. In addition, DNA logic circuits cannot directly sense the expression levels of microRNAs (miRNAs). Here, we constructed a nonlinear classifier based on DNA logic circuits with the random forest algorithm. The classifier can directly sense the expression level of miRNAs in serum samples without isolating specific miRNAs and transmit the signals to the logic classification module and complete the nonlinear classification of cancer status. We validated the classification performance of the constructed nonlinear classifiers by using miRNA expression level samples to diagnose adenocarcinoma, ductal and lobular neoplasms, and squamous cell carcinoma with accuracies of 95.4%, 96.6%, and 97.2%, respectively. The classification results generated using the nonlinear classifiers based on DNA logic circuits showed a strong agreement with the actual disease states labeled in TCGA, as well as with the random forest algorithm, and had high parallelism and stability in the multiclassification of three different cancers. This work shows the great potential of DNA logic circuit-based nonlinear classifiers in cancer diagnosis, which provides a new approach to design efficient, accurate, and intelligent integrated disease diagnosis schemes.

PMID:40403203 | DOI:10.1021/acssynbio.5c00129

Am Soc Clin Oncol Educ Book. 2025 Jun;45(3):e473590. doi: 10.1200/EDBK-25-473590. Epub 2025 May 22.

ABSTRACT

The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field. For example, AI-driven adaptive trial designs may allow for real-time modifications based on emerging safety and efficacy signals, enabling more responsive and efficient trials. AI-powered diagnostic tools, including radiomics, computational pathology, and spatial omics, can improve trial patient selection and response assessments. ML-based patient outcome simulations can similarly enhance patient stratification strategies and statistical power. Application of AI can also improve the accessibility of real-world data, including opportunities to enhance data extraction, standardization, and harmonization of data from routine clinical practice. Data generated from digital health technologies (eg, wearable devices, electronic sensors, computing platforms, software applications) may enable a more comprehensive understanding of patient populations to support clinical trials from enrollment to assessment. Automation of trial operations and data management can also improve data fidelity and decrease investigator burden, which has the potential to streamline trial execution and increase potential use of decentralization. There are ongoing efforts to enhance regulatory clarity, mitigate bias, and uphold ethical use of these novel technologies. In this article, we review use cases of AI and ML in oncology clinical trials, including their role in patient recruitment, trial design and operations, data management, and diagnostics. Although these technologies can have applications across all phases of drug development including early discovery, we focus on phase II and III trials, where AI and ML may have a pronounced ability to enhance trial efficiency, patient stratification, and regulatory decision making. By integrating AI and ML, clinical trials can become more adaptive, data-driven, and inclusive in the pursuit of improving patient outcomes.

PMID:40403202 | DOI:10.1200/EDBK-25-473590

JCO Glob Oncol. 2025 May;11:e2400625. doi: 10.1200/GO-24-00625. Epub 2025 May 22.

ABSTRACT

PURPOSE: Integrating palliative care into oncology is essential, yet disparities in access and quality persist, particularly in low- and middle-income countries (LMICs). The ASCO guidelines advocate for early, routine, interdisciplinary palliative care for patients with advanced cancer. Barriers to implementing these recommendations include resource limitations, inadequate training, and cultural perceptions. Recognizing these challenges is essential for improving equitable access to palliative care worldwide.

METHODS: This prospective survey assessed adherence to ASCO recommendations for palliative care integration among LMIC health care providers (HCPs). Participants were recruited via e-mail, social media, and a list of members involved in the ASCO Palliative Care Communities of Practice from February to May 2024. The survey included sections on sociodemographic information, self-perceived adherence to ASCO guidelines on a 5-point Likert scale, and open-ended questions on implementation barriers. Data were collected using Research Electronic Data Capture system. Participants were grouped by WHO regions. Descriptive statistics were used to summarize characteristics and adherence scores, and chi-square tests were used to evaluate regional differences. Thematic analysis identified key themes from open-ended responses.

RESULTS: One hundred eighty HCPs participated; 62% was female, and 51.1% was age 35-44 years. Most were physicians (66%), and 50% lacked palliative care specialization. Adherence to ASCO guidelines varied, with early palliative care referrals ranging from 50% in the Americas region to 0% in the Western Pacific region. Key barriers included lack of policy support (25%), unmet educational needs (22%), and accessibility constraints (19%).

CONCLUSION: Addressing identified barriers through evidence-based advocacy, comprehensive policy changes, training, and continuing education programs is essential for integrating palliative care into oncology services across LMICs, promoting health equity for patients with cancer.

PMID:40403199 | DOI:10.1200/GO-24-00625

Int J Psychiatry Med. 2025 May 22:912174251345007. doi: 10.1177/00912174251345007. Online ahead of print.

ABSTRACT

ObjectiveThis study investigated the effects of Electroconvulsive Therapy (ECT) on intracranial pressure (ICP) by measuring the optic nerve sheath diameter (ONSD) using ultrasonography. While ECT is a common and effective treatment for various psychiatric disorders, its impact on cerebral hemodynamics, particularly ICP, remains unclear. Previous research suggests that ECT may increase cerebral blood flow and oxygen consumption, potentially elevating ICP. However, there is limited direct evidence linking ECT to measurable ICP changes.MethodsIn this study, ONSD was measured at 4 time points during ECT in 24 patients, including pre-ECT, post-induction, post-ictal, and in the post-anesthesia care unit (PACU).ResultsThe results showed no statistically significant changes in ONSD, indicating that ECT does not significantly alter ICP based on this non-invasive measurement.ConclusionThese findings suggest that, at least in the context of this study, ECT does not lead to clinically relevant changes in ICP.

PMID:40403192 | DOI:10.1177/00912174251345007

Anesth Analg. 2025 May 22. doi: 10.1213/ANE.0000000000007548. Online ahead of print.

ABSTRACT

BACKGROUND: Postoperative delirium (POD), emergence delirium (ED), and postoperative cognitive dysfunction (POCD) are disorders of the neuropsychiatric spectrum affecting the elderly during the postoperative period, potentially sharing a common pathophysiological pathway. Disrupted sleep postoperatively correlates with both POD and POCD, revealing overlapping risk factors. This study investigates the potential of dexmedetomidine anesthesia to reduce the incidence of POD (primary outcome), ED, POCD, impairment of sleep quality, and emergent chronic pain (secondary outcomes) in older adults undergoing major orthopedic surgery under regional anesthesia.

METHODS: In this double-blind randomized control trial, patients scheduled for major lower limb orthopedic surgery under regional anesthesia were randomized to receive either dexmedetomidine or propofol for sedation at a 1:1 ratio. POD, ED, and POCD were assessed with the Confusion Assessment Method tool, the Riker Sedation-Agitation scale, and the European Battery of psychometric tests, respectively. Sleep quality was assessed using the Pittsburg Sleep Quality Index and chronic pain with the painDETECT tool. Assessments of all outcome variables were performed before surgery, and at 48 hours and 3 months postoperatively.

RESULTS: A total of 80 patients (dexmedetomidine group n = 41) were enrolled in the study and completed the follow-up. POD, ED, and early POCD incidence were significantly lower in dexmedetomidine compared to propofol group (4.8% vs 38.4%, P = .001; 2.4% vs 38.4%, P < .001; 2.4% vs 56.4%, P < .001, respectively). Patients in the dexmedetomidine group reported improved sleep quality in the immediate postoperative period (lower PSQI score) and lower painDETECT scores at 3 months (4.4 ± 0.7 vs 13.4 ± 0.8, P < .001; 2.4 ± 0.9 vs 5.3 ± 0.9, P = .023, respectively). Intraoperative bradycardia and hemodynamic instability episodes were more common in the dexmedetomidine group while a single patient presented airway obstruction (2.4% vs 30.8%, P = .002) in the dexmedetomidine group.

CONCLUSIONS: Sedation with dexmedetomidine resulted in a statistically and clinically important reduction in the incidence of POD, ED, and early POCD, while it improved self-reported postoperative sleep quality and reduced chronic pain scores in patients undergoing major elective lower limb surgery under regional anesthesia.

PMID:40403182 | DOI:10.1213/ANE.0000000000007548

Acad Med. 2025 May 22. doi: 10.1097/ACM.0000000000006093. Online ahead of print.

ABSTRACT

PURPOSE: To determine the relationship between adverse childhood experiences (ACEs), social disadvantage, psychological distress, and resilience in graduate health professions students.

METHOD: This study includes cross-sectional analyses from a longitudinal survey of medical, veterinary, and advanced practice provider students at matriculation to the University of California Davis in July 2019. The survey contained an expanded Adverse Childhood Experiences Questionnaire (ACEs-14), a measure of psychological distress (the Medical Student Well-Being Index [MSWBI]), and the Brief Resilience Scale. Responses were linked to demographics, including markers of social disadvantage (female gender, underrepresented in medicine [URM] status, and first-generation college graduate [first-gen] status). The relationships between ACEs, social disadvantage, psychological distress, and resilience were tested using linear or logistic regression.

RESULTS: Complete survey responses were provided from 240 of 357 students (67% completion rate). About two-thirds of students (67%, 161/240) reported ≥1 ACE, while a quarter (25%, 60/240) reported ≥4 ACEs. URM and first-gen students had higher odds of reporting ≥4 ACEs (odds ratio [OR] = 1.56; P = .049 and OR = 2.63; P < .001, respectively) than their nondisadvantaged peers based on binary logistic regression analysis. Higher ACEs-14 scores were associated with higher psychological distress scores (P < .001). The majority of students reported normal or high resilience (normal: 76%, 183/240; high: 10%, 25/240) regardless of ACEs-14 scores. There was not a statistically significant relationship between ACEs-14 scores and resilience scores (P = 0.936).

CONCLUSIONS: Health professions students from some socially disadvantaged backgrounds at this institution reported statistically significantly higher ACEs-14 scores than their nondisadvantaged peers. Childhood adversity was associated with increased psychological distress but not with low resilience. Implications for equity- and trauma-informed health professions education and interventions are discussed.

PMID:40403161 | DOI:10.1097/ACM.0000000000006093

JBJS Rev. 2025 May 22;13(5). doi: 10.2106/JBJS.RVW.25.00052. eCollection 2025 May 1.

ABSTRACT

BACKGROUND: Childhood obesity is a growing global health crisis with significant health and orthopedic complications such as slipped capital femoral epiphysis (SCFE), a hip disorder characterized by the displacement of the metaphysis relative to the epiphysis. SCFE always requires surgical intervention to prevent severe outcomes such as avascular necrosis, gait abnormalities, and lifelong disability and deformity. Obesity is a well-established risk factor for SCFE; however, emerging evidence suggests that elevated leptin levels may independently contribute to the development of SCFE, regardless of obesity status. This systematic review synthesizes geographic, socioeconomic, age, and sex-related trends in SCFE incidence among children with obesity.

METHODS: Searches of Embase, OVID Medline, and Emcare databases were performed from inception through October 1, 2024. Observational studies reporting the incidence of SCFE in children and adolescents with obesity (aged ≤18 years) across various geographic populations were included. Studies involving children with other chronic health conditions or animal studies on the physis were excluded. Study quality was evaluated using the methodological index for nonrandomized studies scoring system. Descriptive statistics were presented as absolute frequencies with percentages or as weighted means with corresponding measures of variance where applicable.

RESULTS: Fifteen studies (5,467 patients) from North America, Europe, Asia, and Oceania met inclusion criteria. SCFE patient samples ranged from 55 to 1,630, with some larger cohorts monitoring multiple medical conditions. The mean age was 12.0 years (SD = 0.4), and male-to-female ratios ranged from 1.43:1 to 3.12:1. SCFE incidence varied by region, from 50.5 per 100,000 (Sweden) to 0.33 per 100,000 (South Korea), with a pooled incidence of 9.62 per 100,000. Overweight prevalence was highest in Sweden (66%) and South Korea (67.6%) and lowest in Japan (11.8%). Unilateral SCFE predominated (68.4% to 90.6%). In situ screw fixation was the most common treatment, with 1 study reporting intertrochanteric osteotomy.

CONCLUSION: Geographic variation in SCFE incidence suggests multifactorial influences beyond obesity, including socioeconomic factors, healthcare access, and genetic predisposition. Limited high-quality comparative studies and inconsistent BMI criteria highlight the need for further research to clarify SCFE risk factors.

LEVEL OF EVIDENCE: Level IV, systematic review. See Instructions for Authors for a complete description of levels of evidence.

PMID:40403127 | DOI:10.2106/JBJS.RVW.25.00052

J Med Internet Res. 2025 May 22;27:e63961. doi: 10.2196/63961.

ABSTRACT

BACKGROUND: Virtual reality (VR) simulators are increasingly used in dental education, offering advantages such as repeatable practice and immediate feedback. However, evidence comparing their efficacy to traditional phantom heads for veneer preparation training remains limited.

OBJECTIVE: This study aimed to compare the effectiveness of 2 widely used VR simulators (Unidental and Simodont) against traditional phantom heads for veneer tooth preparation training and evaluate the impact of training sequence (simulator-first vs phantom-head-first) on skill acquisition.

METHODS: A randomized controlled trial was conducted with 80 fourth-year dental students from Peking University School of Stomatology. Participants were stratified by gender and academic performance, then equally allocated to 8 groups. Groups 1-3 trained exclusively using Unidental, Simodont, or phantom heads, respectively, while groups 4-8 followed hybrid sequences combining simulator and phantom-head training. Each participant performed veneer preparations on a maxillary central incisor. Preparations were evaluated by a blinded instructor using a validated 100-point rubric assessing marginal integrity (30%), preparation depth (25%), proximal contour (25%), and surface smoothness (20%). Posttraining questionnaires (100-point scale) compared user perceptions of simulator realism, haptic feedback, and educational value.

RESULTS: There were no statistically significant differences in the preparation quality among groups using different training methods (Unidental: 88.9, SD 3.6; Simodont: 88.6, SD 1.6; phantom heads: 89.4, SD 2.8; P=.81) or different training methodologies (simulator-first vs phantom-head-first) (simulator first: P=.18; phantom head first: P=.09, different sequences of Unidental: P=.16; different sequences of Simodont: P=.11). However, significant differences were observed between the evaluations of the 2 simulators in terms of realism of the odontoscope’s reflection (Simodont: 55.6, SD 33.7; Unidental: 87.5, SD 13.9; P<.001), force feedback (Simodont: 66.2, SD 22.4; Unidental: 50.8, SD 18.9; P=.007), and simulation of the tooth preparation process (Simodont: 64.4, SD 16.0; Unidental: 50.6, SD 16.6; P=.003). Evaluation results showed no statistical differences between the 2 simulators in display effect (Simodont: 77.43, SD 21.58; Unidental: 71.68, SD 20.70; P=.24), synchronism of virtual and actual dental instruments (Simodont: 67.86, SD 19.31; Unidental: 59.29, SD 20.10; P=.11), and dental bur operation simulation (Simodont: 63.32, SD 19.99; Unidental: 55.79, SD 19.62; P=.16). The Unidental simulator was rated better than the Simodont simulator in terms of the realism of odontoscope’s reflection. In all other aspects, Simodont was superior to Unidental. There was no significant difference in the students’ attitudes towards the 2 simulators (improve skills: P=.19; inspire to learn: P=.29; will to use: P=.40; suitable for training: P=.39).

CONCLUSIONS: The study found no significant differences in training outcomes between VR simulators and traditional phantom heads for veneer preparation, suggesting that VR technology may serve as a viable alternative or supplementary tool in dental education. However, the absence of significant differences does not imply equivalence, as formal equivalence testing was not performed. Future studies should incorporate equivalence testing and explore cost-effectiveness, long-term skill retention, and adaptability to complex clinical scenarios.

PMID:40402564 | DOI:10.2196/63961

JMIR Hum Factors. 2025 May 22;12:e62960. doi: 10.2196/62960.

ABSTRACT

BACKGROUND: Problem anger is common after experiencing trauma and is under-recognized relative to other posttraumatic mental health issues. Previous research has shown that digital mental health tools have significant potential to support individuals with problem anger after trauma.

OBJECTIVE: The objective of this study was to describe the co-design and development of a just-in-time adaptive intervention (JITAI) targeting problem anger in individuals who have experienced trauma.

METHODS: We used a participatory design process following the double-diamond framework. Phase 1 involved one-on-one qualitative interviews with trauma-exposed individuals with problem anger (n=10). Using an inductive approach (interpretative phenomenological analysis), we thematically coded interview data to create design principles for this population and generate potential content for the intervention. Phase 2 involved academic and clinical experts in trauma and experts in digital health reviewing the Phase 1 results and an evidence-based cognitive behavioral approach to treating anger. We then created intervention content and prototypes, which we then took to workshops with all participants for feedback, using group discussions and ratings of desirability and feasibility.

RESULTS: From Phase 1, core considerations for a JITAI included look and feel preferences, self-led and personalized support and content, and different support needed for each anger stage. A JITAI was developed with the following components: (1) personalized schedules and content onboarding; (2) psychoeducation about problem anger; (3) crisis support; (4) mood monitoring via anger check-ins; (5) self-led and personalized circuit breakers; (6) cognitive-behavioral based skills; (7) and a digital Coach embedded in the app. Some suggested features, such as social networking and sharing data with loved ones, were not pursued due to feasibility reasons relating to participant safety or technical costs.

CONCLUSIONS: The resulting JITAI, termed “Shift,” is the first digital mental health tool designed with end users to manage anger after trauma.

PMID:40402559 | DOI:10.2196/62960