Tag: statistics

Scand J Clin Lab Invest. 2026 Aug 5:1-7. doi: 10.1080/00365513.2026.2713141. Online ahead of print.

ABSTRACT

The blood urea nitrogen (BUN)-to-plasma creatinine ratio is a conventional method for diagnosing dehydration. We examined the relationship between this method and the more recently promoted urine biomarkers of dehydration. Blood and urine sampling was performed in 921 patients who were fasting before surgery. The blood was analyzed for the BUN-to-plasma creatinine ratio which was divided into three ranges: low (<50), normal (50-100), and high (>100 mmol/L). The fractions of the cohort that belonged to these ranges were 8.9%, 76.7%, and 14.4%, respectively. The urine was analyzed for color, specific gravity, osmolality, and creatinine, and the results summarized in the Fluid Retention Index, which is a robust measure of renal water conservation. The analysis shows that none of the four urine biomarkers differed statistically between these three groups. The Fluid Retention Index was 2.3, 2.0, and 1.7, respectively (p = 0.17), which means that the degree of urine concentration varied in the opposite direction to that expected. Moreover, no linear correlations were found when individual blood and urine measurements were compared. Patients who were classified as being dehydrated according to the Fluid Retention Index had a mean BUN to creatinine ratio of 77 while the others had 76 mmol/L (p = 0.94). In conclusion, the BUN-to-ratio did not correlate with urine biomarkers of dehydration in fasting pre-surgical patients. This result suggests that the BUN-to-creatinine ratio may not reliably reflect hydration status and motivates a repeat study where the body volume deficit is known or the water consumption is monitored over time.

PMID:42554314 | DOI:10.1080/00365513.2026.2713141

JMIR Res Protoc. 2026 Aug 4;15:e74202. doi: 10.2196/74202.

ABSTRACT

BACKGROUND: The current landscape of emergency care (EC) is marked by high demand, leading to issues such as emergency department boarding, overcrowding, and subsequent delays that impact the quality and safety of patient care. Integrating data science into EC can enhance decision-making with predictive, preventative, personalized, and participatory approaches. However, gaps in adherence to fairness, accountability, interpretability, and responsibility are evident, particularly due to barriers to data-sharing, which often result in a lack of transparency and robust oversight in these applications.

OBJECTIVE: The FAIR-EC (Fair, Accountable, Interpretable, and Responsible-Emergency Care) collaboration adapts the existing Fair, Accountable, Interpretable, and Responsible principles to address emerging challenges as data science integrates with EC. This initiative aims to transform EC by establishing ethical artificial intelligence standards specifically tailored for this integration. By bridging the gap between EC professionals, data scientists, and other stakeholders, the collaboration promotes international cooperation that leverages advanced data science techniques to enhance EC outcomes across different care settings.

METHODS: We propose a federated research design to analyze extensive datasets from various global institutions without compromising patient privacy. This approach transforms epidemiological research with advanced data science techniques, emphasizing the harmonization of data for comprehensive analyses across different health care systems.

RESULTS: The FAIR-EC initiative has facilitated the identification and harmonization of datasets from diverse geographical regions, enabling the examination of regional variations in EC practices. As of paper submission, participating sites have identified retrospective EC datasets totaling >2 million records (eg, Duke Health >400,000 and Singapore General Hospital >1.7 million records). Initial projects have demonstrated feasibility and operational readiness, including implementation of federated workflows and ongoing development of a federated scoring system, cross-site evaluation, and adaptation of association studies and predictive models across various regions. Cross-site harmonization and pilot analyses are underway (with local ethics approvals in progress), and first multisite results are expected to be submitted in mid-late 2026, with additional project-level publications anticipated in 2027. These efforts highlight the feasibility of leveraging advanced data science techniques to address the complexities of EC while preserving patient privacy without centralizing individual-level data. This project was funded from September 1, 2022, to August 31, 2023.

CONCLUSIONS: FAIR-EC integrates data science ethically and effectively into EC, addressing challenges such as fragmented data, real-time handoffs, and public health crises. Its federated design harmonizes diverse data streams while preserving privacy, and its emphasis on ethical artificial intelligence aligns with the dynamic nature of EC. Despite challenges in data variability and system complexity, FAIR-EC establishes a strong foundation for innovation in global EC.

PMID:42554297 | DOI:10.2196/74202

Multivariate Behav Res. 2026 Aug 5:1-16. doi: 10.1080/00273171.2026.2699709. Online ahead of print.

ABSTRACT

In this study we advance causal mediation analysis for nominal mediators within a potential outcome framework. Through Monte Carlo simulations, we compared three inference methods for testing total natural indirect effects (TNIE) and pure natural indirect effects (PNIE): non-parametric bootstrapping, parametric resampling, and Bayesian estimation. Results showed that nominal mediation models yielded accurate estimates across conditions, with both maximum likelihood and Bayesian approaches performing well. All three inference methods maintained acceptable Type I error control and achieved adequate statistical power in larger samples, with comparable performance across approaches. We provide an empirical illustration using survey data on healthcare payment types and mental health help-seeking behavior to illustrate the model’s utility. Findings suggest that researchers can reliably estimate and test nominal mediation effects using any of the three inference approaches, providing a robust methodological framework for investigating causal pathways involving categorical mediating variables in social, behavioral, and health sciences.

PMID:42554287 | DOI:10.1080/00273171.2026.2699709

Int J Neural Syst. 2026 Aug 5:2750007. doi: 10.1142/S0129065727500079. Online ahead of print.

ABSTRACT

This study proposes a novel enhancement to the Conformer architecture for epileptic seizure identification by replacing the standard Vision Transformer (ViT) with the Swin Transformer. The proposed Swin-Conformer model leverages the hierarchical patch merging and shifted-window self-attention mechanisms of the Swin Transformer to better capture both local electrophysiological patterns and long-range temporal dependencies in electroencephalogram (EEG) signals. To handle the significant class imbalance inherent in epileptic EEG data, a weighted focal loss function is employed during training. The model is evaluated on the CHB-MIT dataset through stratified 10-fold cross-validation and validated on the independent Bonn EEG dataset. Experimental results demonstrate that the proposed model achieves accuracy of 99.24%, specificity of 99.55%, and sensitivity of 98.47% on the segment-based evaluation, as well as an event-based sensitivity of 99.50%, outperforming the original Conformer and state-of-the-art baseline methods. Ablation studies confirm that the performance gains originate from the Swin Transformer’s hierarchical multi-scale feature representation and efficient local-global attention mechanism. Statistical analysis confirms that the improvements are statistically significant ([Formula: see text]).

PMID:42554275 | DOI:10.1142/S0129065727500079

J Hypertens. 2026 Jul 17. doi: 10.1097/HJH.0000000000004367. Online ahead of print.

ABSTRACT

BACKGROUND: Many primary aldosteronism (PA) patients harbor concomitant mild autonomous cortisol secretion (MACS), termed “Connshing syndrome.” The prevalence and cardiometabolic impact of this co-secretion have not been quantitatively synthesized.

OBJECTIVE: To determine the pooled prevalence of MACS in PA and evaluate its association with cardiovascular (CV) events, type 2 diabetes mellitus (T2DM), and obesity.

DATA SOURCES: PubMed, Embase, Cochrane, Web of Science, and Scopus through January 2026.

METHODS: Following PRISMA 2020 and MOOSE guidelines (PROSPERO: CRD420261334965), studies reporting MACS prevalence [post-1 mg dexamethasone suppression test (DST) cortisol ≥1.8 μg/dl] in PA were included. Prevalence was pooled using random-effects models. Odds ratios (ORs) were calculated for cardiometabolic outcomes. Certainty was evaluated using GRADE.

RESULTS: Fourteen studies (2356 patients) were included. Pooled MACS prevalence was 26.2% [95% confidence interval (CI): 24.1-28.4; I2 = 24.2%; prediction interval: 21.6-31.4%], consistent across European (27.0%) and East Asian (25.2%) cohorts (P = 0.62). MACS + PA patients had higher odds of CV events (OR 1.60; 95% CI: 1.07-2.38; P = 0.021) and T2DM (OR 1.37; 95% CI: 1.00-1.86; P = 0.048), but not obesity (OR 1.10; P = 0.411). Sensitivity analyses confirmed robustness. GRADE certainty was moderate for prevalence and low for CV events.

CONCLUSIONS: Approximately one in four PA patients has MACS, associated with a 60% higher CV event risk. These findings support routine DST screening in PA and have implications for perioperative management and cardiometabolic risk stratification.

PMID:42554261 | DOI:10.1097/HJH.0000000000004367

Cancer. 2026 Aug 15;132(16):e70560. doi: 10.1002/cncr.70560.

ABSTRACT

BACKGROUND: Sexual health, central to overall well-being, remains under assessed in childhood, adolescent and young adult (CAYA) cancer survivorship. This study examined sexual health outcomes among CAYA cancer survivors using repeated assessments collected as part of routine survivorship care and compared these outcomes with population-based controls.

METHODS: Survivors completed one to six assessments on sexual activity, concerns about sex life, and contraceptive and condom use. Controls included age-matched Canadian Community Health Survey respondents. Multilevel and Bayesian models quantified predictors of sexual health outcomes whereas latent class growth analysis tested for high-risk subgroups.

RESULTS: Among survivors (n = 305; median age, 21.9 years; 49.8% male), 47.5% were not sexually active, compared with 11.2% of controls (unweighted n = 108,252; χ² = 404.35; p < .001; odds ratio [OR], 7.18; 95% Confidence Interval [CI], 5.73-8.99). Being in a relationship predicted sexual activity (Bayesian OR, 1806.83; 95% Credible Interval [CrI], 255.08-20,535.08). Condom use was less frequent among survivors than controls (45.6% vs. 27.2%; χ² = 27.48; p < .001; OR, 1.68; 95% CI, 1.42-1.99) and negatively associated with age (OR, 0.44; 95% CI, 0.26-0.74) and relationship status (OR, 0.09; 95% CI, 0.03-0.24). Not using birth control was similar between survivors and controls (26.9% vs. 25.8%; χ² = 0.10; p = .758). Within survivors, older age (OR, 0.41; 95% CI, 0.20-0.85) and higher treatment intensity (OR, 0.02; 95% CI, 0.00-0.47) were negatively associated with birth control use.

CONCLUSIONS: CAYA cancer survivors demonstrate less sexual activity and condom use than controls. Higher treatment intensity is associated with less birth control use, suggesting potential misaligned fertility perceptions. Survivorship programs should integrate structured sexual health counselling.

PMID:42554247 | DOI:10.1002/cncr.70560

Cancer. 2026 Aug 15;132(16):e70550. doi: 10.1002/cncr.70550.

ABSTRACT

BACKGROUND: Chemotherapy drugs are hazardous and require strict safety protocols to protect health care workers. In the Gaza Strip, cancer is a leading cause of death, yet there is limited research on nurses’ adherence to safe chemotherapy handling practices. This study assesses the safe chemotherapy handling behaviors of nurses at the Turkish Palestinian Friendship Hospital in Gaza.

METHODS: A descriptive cross-sectional study was conducted between July and August 2023. All 110 nurses at the hospital were invited to complete a validated, self-administered questionnaire based on the Nova Scotia Health Authority Chemotherapy Checklist. Data were analyzed using SPSS v25 with descriptive statistics, t-tests, and analysis of variance.

RESULTS: The response rate was 96.36% (n = 106). The mean self-reported scores for safe behavior domains were: safe handling before administration (81.77%), safe handling during administration (71.33%), safe disposal of equipment (83.05%), and safe disposal of cytotoxic body fluids (72.84%). These scores reflect nurses’ perceptions of their own practices rather than objectively observed compliance. Significant associations were found between safe behaviors and age (p = .012), years of nursing experience (p = .001), oncology experience (p = .044), qualifications (p = .004), and previous training (p = .003).

CONCLUSION: Although nurses demonstrated moderate to good compliance with chemotherapy safety protocols, critical gaps remain, particularly in drug administration and disposal practices. Regular targeted training, protocol reinforcement, and hiring of specialized oncology nurses are urgently needed.

PMID:42554107 | DOI:10.1002/cncr.70550

Telemed J E Health. 2026 Aug 5:15305627261476425. doi: 10.1177/15305627261476425. Online ahead of print.

ABSTRACT

OBJECTIVE: A prospective study to compare the mean blood pressure and mean weight of subjects with congestive heart failure (CHF) in the month before Ramadan, during the month of Ramadan, and in each of the two months following Ramadan to determine if fasting has any effect on health.

METHODS: Patients were given a blood pressure meter and weighing scale and instructed to take daily measurements. Data were transmitted wirelessly from the devices to a simple home gateway for automatic onward transmission to the data server without intervention from the subject. Subsets of data for blood pressure and weight were created for each of the months before Ramadan, during the month of Ramadan, and the two months following Ramadan for 2025 and 2026. The mean and standard deviation were determined for each patient, and comparison between successive months was performed for the cohort mean and standard deviation using t-test. Paired t-tests were performed for subgroups containing only patients participating in successive periods.

RESULTS: There was significant variation in the mean of an individual and in the mean of a cohort; however, the mean was consistent across the period with the value for the t-test between successive periods being greater than 0.25 (CI: 0.05). The value for the paired t-test was greater than 0.22 (CI: 0.05) for all periods except between post-Ramadan and 2 months post-Ramadan when the value was 0.10 (CI: 0.05), and some subjects were seen to exhibit significant changes.

CONCLUSIONS: The t-test and paired t-test values show that there were no statistically significant differences between cohort means and paired comparisons for blood pressure and weight for all months, indicating there are no effects on health in patients with CHF due to fasting if appropriately clinically managed.

PMID:42554102 | DOI:10.1177/15305627261476425

Sports Biomech. 2026 Aug 5:1-20. doi: 10.1080/14763141.2026.2711093. Online ahead of print.

ABSTRACT

Comparative data on markerless motion capture systems for upper-extremity kinematics during high-speed movements remain limited. We aimed to examine inter-system modelling differences in shoulder joint kinematics between a markerless motion capture system (Theia3D) and a marker-based system during baseball pitching, focusing on a wide range of shoulder joint motion throughout baseball pitching. Six collegiate pitchers completed 117 trials recorded simultaneously by both systems. Shoulder joint angles and joint centre positions were compared using nested Bland-Altman analysis, intraclass correlation coefficients (ICC (3,1)), and statistical parametric mapping (SPM). At maximum external rotation (MER), inter-system differences were small for external rotation (bias: -0.3°; ICC = 0.77), whereas the horizontal angle demonstrated a pronounced fixed bias (bias: -19.1°). At ball release (BR), inter-system differences increased across all joint angles, with the largest discrepancy for external rotation (bias: -8.5°; ICC = 0.33). Proportional bias was evident for most variables at BR. Between-participant variance exceeded within-participant variance at MER, indicating that participant-specific offsets were primary contributors to the limits of agreement. SPM identified significant inter-system differences during the acceleration phase. These findings highlight the importance of understanding the characteristics of each modelling approach for appropriate interpretation and application of markerless motion capture in overhead athletes.

PMID:42554087 | DOI:10.1080/14763141.2026.2711093

Multivariate Behav Res. 2026 Aug 5:1-19. doi: 10.1080/00273171.2026.2708913. Online ahead of print.

ABSTRACT

Substance use disorder data are often collected by asking individuals to endorse (or not endorse) a set of items pertaining to various diagnostic criteria. The result is a bipartite network, which can be represented by a two-mode binary matrix with rows corresponding to the individuals and columns to the items. Two-mode blockmodeling is an exploratory data analysis approach for bipartite networks that establishes partitions of both the individuals and items. Some two-mode blockmodeling methods are deterministic, whereas the latent blockmodel is stochastic and grounded by an underlying statistical model. A simulation study comparing the latent blockmodel and two deterministic blockmodeling methods revealed that the methods often perform comparably with respect to recovery of the true (known) cluster memberships when the number of clusters for both individuals and items is prespecified. However, the results also showed that one of the deterministic methods is unsuitable for sparse bipartite networks. A key advantage of the latent blockmodel method is a principled approach to selection of the number of clusters for individuals and items. We also demonstrate the effectiveness of the latent blockmodel via comparison to deterministic blockmodeling for a multiple-substance use disorder data set from the literature.

PMID:42554079 | DOI:10.1080/00273171.2026.2708913