Tag: statistics

Anesthesiol Perioper Sci. 2026;4(1):33. doi: 10.1007/s44254-026-00179-w. Epub 2026 Jun 22.

ABSTRACT

PURPOSE: Perioperative metabolic vulnerability is an important contributor to postoperative morbidity, yet preoperative risk stratification relies largely on conventional glycemic measures such as hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG). Hemoglobin glycation index (HGI) quantifies interindividual discordance between HbA1c and contemporaneous glycemia and may capture metabolic phenotypes not reflected by absolute glucose values. We investigated the association between preoperative HGI and postoperative outcomes in adults undergoing non-cardiac surgery.

METHODS: We conducted a retrospective single-center cohort study including adult inpatients who underwent non-cardiac surgery under general anesthesia between January 2013 and June 2024. Patients with both preoperative HbA1c and FPG measured within 60 days before surgery were included. HGI was calculated as the residual of observed HbA1c minus HbA1c predicted from FPG using a cohort-specific linear regression model. The primary outcome was any postoperative complication occurring before hospital discharge. Secondary outcomes included major complications (Clavien-Dindo grade ≥ III), organ-specific complications, deep-vein thrombosis, Intensive Care Unit (ICU) admission, hospital and postoperative length of stay, and in-hospital mortality. Associations were evaluated using multivariable regression models with HGI analyzed as a continuous variable (per 1-SD increase) and by quartiles (Q2 as reference), complemented by restricted cubic spline analyses and prespecified subgroup analyses.

RESULTS: A total of 24,307 patients were included (mean age 58.8 ± 13.3 years; 51% women). Postoperative complications occurred in 8.4% of patients. In adjusted continuous models, higher HGI was independently associated with postoperative complications (odds ratio [OR] per 1-SD increase 1.068; 95% confidence interval [CI], 1.018-1.120; P = 0.007), urinary complications (OR 1.155; 95% CI, 1.024-1.301; P = 0.018), and longer total hospital length of stay (adjusted mean ratio 1.030; 95% CI, 1.017-1.043; P = 0.001). Quartile analyses demonstrated the lowest risk of postoperative complications in the mid-range HGI group, with higher risks observed at extreme HGI values. Restricted cubic spline models revealed an approximately linear association between HGI and overall postoperative complications, while outcome-specific nonlinear relationships were observed for major complications, ICU admission, and in-hospital mortality. Associations were generally consistent across subgroups, with no statistically significant interaction detected across prespecified strata.

CONCLUSIONS: Preoperative hemoglobin glycation index was independently associated with postoperative complications after non-cardiac surgery and identified nonlinear risk patterns for selected severe outcomes. HGI may serve as a complementary perioperative metabolic risk marker beyond HbA1c and fasting plasma glucose to provide incremental risk information.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s44254-026-00179-w.

PMID:42339472 | PMC:PMC13284033 | DOI:10.1007/s44254-026-00179-w

Front Bioeng Biotechnol. 2026 Jun 8;14:1767092. doi: 10.3389/fbioe.2026.1767092. eCollection 2026.

ABSTRACT

BACKGROUND: Proprioceptive deficits following anterior cruciate ligament (ACL) injury increase reliance on visual input in athletes after ACL reconstruction (ACLR). Visual disruption may therefore alter movement patterns and increase re-injury risk. However, its influence on lower limb biomechanics during cutting maneuvers in ACLR athletes remains unclear.

PURPOSE: To investigate the effects of visual disruption on the kinematic and kinetic characteristics of the lower limb during the 90° cutting maneuver in athletes after ACLR.

METHODS: Twenty athletes after ACLR and twenty healthy athletes were recruited to randomly undergo two different visual conditions, eyes-open and visual disruption, and to complete the 90° cutting maneuver in each of the two visual conditions. Visual disruption was performed with strobe glasses. A nine-camera infrared motion capture system (Vicon T40, 200 Hz) was used to collect lower-limb kinematics data during the 90° cutting task, while a three-dimensional force platform (Kistler, 1,000 Hz) recorded kinetic data. Data were processed using Visual 3D software, and statistical analyses were conducted using SPSS (version 25.0). A two-factor repeated measures analysis of variance was used to determine the effects of group and visual conditions on kinematic and kinetic variables.

RESULTS: (1) Compared with the eyes-open condition, the peak knee valgus angle (P = 0.025, ES = 0.157) and peak ankle inversion angle (P = 0.005, ES = 0.233) of athletes after ACLR were significantly increased under visual disruption conditions. There was no significant difference between the kinematic variables of the healthy athletes in the two visual conditions (P > 0.05). (2) Compared with the eyes-open condition, the hip extension moment of athletes after ACLR was significantly increased (P = 0.037) and the knee extension moment was significantly reduced (P = 0.039) under visual disruption conditions. There was no significant difference (P > 0.05) in the kinetic variables of the healthy athletes between the two visual conditions.

CONCLUSION: Visual disruption increased knee valgus and ankle inversion angles in athletes after ACLR, which may increase the risk of secondary anterior cruciate ligament injuries and lateral ankle sprains. These results suggest that ACLR athletes have a poorer ability to recalibrate sensory information to visual disruption compared to healthy athletes.

PMID:42339465 | PMC:PMC13284120 | DOI:10.3389/fbioe.2026.1767092

Front Cognit. 2024 Mar 5;3:1336379. doi: 10.3389/fcogn.2024.1336379. eCollection 2024.

ABSTRACT

During visual search, the spatial configuration of the stimuli can be learned when the same displays are presented repeatedly, thereby guiding attention more efficiently to the target location (contextual cueing effect). This study investigated how the presence of a task-irrelevant object influences the contextual cueing effect. Experiment 1 used a standard T/L search task with “old” display configurations presented repeatedly among “new” displays. A green-filled square appeared at unoccupied locations within the search display. The results showed that the typical contextual cueing effect was strongly reduced when a square was added to the display. In Experiment 2, the contextual cueing effect was reinstated by simply including trials where the square could appear at an occupied location (i.e., underneath the search stimuli). Experiment 3 replicated the previous experiment, showing that the restored contextual cueing effect did not depend on whether the square was actually overlapping with a stimulus or not. The final two experiments introduced a display change in the last epoch. The results showed that the square does not only hinder the acquisition of contextual information but also its manifestation. These findings are discussed in terms of an account where effective contextual learning depends on whether the square is perceived as part of the search display or as part of the display background.

PMID:42339460 | PMC:PMC13281161 | DOI:10.3389/fcogn.2024.1336379

Front Cognit. 2024 Feb 2;3:1323438. doi: 10.3389/fcogn.2024.1323438. eCollection 2024.

ABSTRACT

INTRODUCTION: Aerobic exercise has been shown to improve cancer-associated cognitive decline (CACD) in breast cancer survivors (BCS), and recent findings suggest that one mechanism by which exercise may reduce cognitive decline is through alteration of the brain’s functional organization. Many cognitive abilities and measures of functional brain organization change with age and disease, typically reflected in cognitive decline and reduced differentiation of brain networks, or “modularity.” Although previous research has identified associations between lifestyle interventions, such as exercise, and increased modularity, no studies have examined these relationships in cancer populations. The primary aim of this study was to investigate the preliminary effects of a 12-week aerobic exercise program on changes in brain network modularity in BCS. As a secondary aim, we explored correlations between changes in modularity with moderate-to-vigorous physical activity (MVPA) and cognitive function. Data were exploratory and used for hypothesis generation for a future, larger study.

METHODS: Participants included a subsample of 10 BCS (M age = 65.9 ± 9.3 years) from a larger pilot study (N = 30 BCS) who were randomized to a 12-week aerobic exercise program (AE) or usual care (UC). The present study collected brain magnetic resonance imaging, Actigraph accelerometry, and cognitive task performance at baseline and 3-month follow-up (i.e., post-intervention; n = 4 AE, n = 6 UC). Intervention effects on modularity, MVPA, and cognition were quantified as magnitude of change between groups (Cohen’s d). Changes in modularity were further explored via paired t-tests within groups. Associations between changes in modularity, MVPA, and cognitive performance were explored using Spearman’s correlations.

RESULTS: The magnitude of changes in modularity between groups were small-to-moderate and favored the AE group (d = 0.23 to d = 0.67 across thresholds). Paired t-tests revealed a significant increase in modularity in the AE group from baseline to 3-month follow-up (t = 3.08, p = 0.03, d = 1.17), but not in the UC group. The correlation between changes in MVPA and changes in modularity were not statistically significant (r = 0.36, p = 0.39), and correlations between modularity and cognitive performance yielded mixed effects by cognitive domain.

DISCUSSION: Findings suggest that aerobic exercise may influence functional brain network organization and cognition in BCS. These data warrant further investigation in larger exercise trials.

PMID:42339451 | PMC:PMC13281212 | DOI:10.3389/fcogn.2024.1323438

Commun Med (Lond). 2026 Jun 23. doi: 10.1038/s43856-026-01735-y. Online ahead of print.

ABSTRACT

BACKGROUND: Accurate tumor segmentation is essential for early diagnosis, treatment planning, and prognostic evaluation. Although manual annotation can achieve high accuracy, it is time-consuming and requires substantial expert involvement. While deep learning has significantly advanced medical image analysis, fully automated methods often fail to segment atypical lesions within complex abdominal anatomy, leading to missed lesions and misclassification of normal tissues, which may compromise clinical decision-making.

METHODS: To address these challenges, we incorporated guidance masks into a convolutional neural network (CNN)-based deep learning framework. Using our Star-Rain software, users place interactive clicks on lesion locations, and the system adaptively generates task-specific guidance masks. This approach directs the model’s attention to relevant regions, particularly in atypical or anatomically complex cases.

RESULTS: Our method is validated on four independent cohorts comprising 1,217 CT scans from 726 patients, encompassing hepatic, renal, and pancreatic tumors. Across these datasets, our approach outperforms state-of-the-art baseline models on independent test sets, achieving Dice scores consistently above 0.7 and reducing the false negative rate (FNR) by 0.006 to 0.346 compared to the best fully automated approaches. In addition, the model’s segmentation outputs effectively support downstream prognosis tasks, highlighting its clinical value.

CONCLUSIONS: These findings underscore the promise of semi-automatic deep learning frameworks that integrate minimal user input for reliable tumor segmentation. The proposed approach offers a practical and robust solution for clinical applications, enhancing segmentation accuracy and decision support while reducing the annotation burden.

PMID:42337366 | DOI:10.1038/s43856-026-01735-y

Nat Food. 2026 Jun 23. doi: 10.1038/s43016-026-01394-1. Online ahead of print.

NO ABSTRACT

PMID:42337342 | DOI:10.1038/s43016-026-01394-1

Sci Rep. 2026 Jun 23. doi: 10.1038/s41598-026-58833-z. Online ahead of print.

ABSTRACT

Spaceborne optical sensors provide continuous Earth observation, but atmospheric interference still limits their practical reliability. On average, clouds cover 67% of the Earth’s surface. This constant coverage degrades the data continuity needed for precision agriculture, disaster monitoring, and proactive Internet of Things (IoT) systems. Recent deep generative networks produce visually appealing cloud-free images. However, when faced with thick clouds ([Formula: see text] opacity), these models often hallucinate topologies. They synthesize statistical guesses instead of recovering the actual ground reflectance. For high-stakes telemetry, predictable failure is safer than an undetected hallucination. This paper introduces Thermo-Cloud Removal (Thermo-CR), a real-time cloud removal framework. It integrates Radiative Transfer inversion, weather-driven transmission estimates, geographic priors, and multi-scale fusion to restore optical imagery without requiring Synthetic Aperture Radar (SAR). Thermo-CR treats the cloudy atmosphere as a thermodynamic medium. By pulling live meteorological telemetry (Relative Humidity (RH) and Temperature (T)) through the Open-Meteo REST API, the system calculates optical depth and performs a deterministic inversion of the Radiative Transfer Model. Pure inverse models amplify noise under extreme occlusion ([Formula: see text]). To prevent this, we apply a Global Positioning System (GPS)-anchored multi-scale fusion with clear-sky temporal priors. We evaluated Thermo-CR on a synthetically occluded paired dataset covering varied topologies (Amazon, London, Seattle). The system degrades predictably under 90% cloud cover and avoids structural hallucination. It achieves an average Structural Similarity Index Measure (SSIM) of 0.9925 and a Peak Signal-to-Noise Ratio (PSNR) of 55.94 dB in under 13 milliseconds per frame, outperforming standard Dark Channel baselines.

PMID:42337308 | DOI:10.1038/s41598-026-58833-z

Sci Rep. 2026 Jun 23. doi: 10.1038/s41598-026-58392-3. Online ahead of print.

ABSTRACT

Surgical procedures cause significant stress for children and their caregivers. Virtual reality (VR) may reduce perioperative fear and physiological stress by delivering engaging, preparatory information. This study aimed to determine the effect of a VR-delivered animated educational video on perioperative anxiety and fear in children and their mothers. This randomized controlled study was conducted with a total of 60 children aged 7-13 years and their mothers who underwent day surgery at a tertiary hospital and met the inclusion criteria (Intervention: children n = 30, mothers n = 30; Control: children n = 30, mothers n = 30). Measures for children included the Physiological Parameters Form, Child Fear Scale and Multidimensional Perioperative Anxiety Scale for Children (MPAS-C); mothers completed the State Anxiety Inventory-Short Form. The intervention consisted of a pre-recorded, approximately five-minute VR-delivered animated educational video administered on the morning of surgery. The children in the intervention group showed a steady decline in their fear scores before the procedure (M = 1.47), after the procedure (M = 0.80), and after surgery (M = 0.70). Conversely, children in the control group showed an increase in fear scores from before the procedure (M = 0.73) to after the procedure (M = 1.33), followed by a minimal decrease after surgery (M = 0.83) (p = 0.002, η² = 0.12). Children’s anxiety scores showed a sharper decline in the intervention group (from M = 151.33 pre-procedure to M = 41.72 post-surgery) compared to the control group (pre-procedure M = 151.37 to postoperative M = 73.67), indicating a larger reduction over time in the intervention group (p < 0.001, η² = 0.33). Maternal anxiety decreased in both groups, but the VR-delivered animated educational video did not provide a statistically significant additional benefit (p = 0.784). The VR-delivered animated educational video was associated with lower child fear, lower perioperative anxiety, and lower heart rate at specific perioperative time points, while no statistically significant additional benefit was observed for maternal state anxiety.Trial Registration: Clinical Trial Number NCT07131982, registration date 2023-06-20.

PMID:42337300 | DOI:10.1038/s41598-026-58392-3

Sci Rep. 2026 Jun 24. doi: 10.1038/s41598-026-59005-9. Online ahead of print.

ABSTRACT

The objective of this study was to estimate the prevalence of primary dysmenorrhea and associated symptoms among adolescent girls. This school based cross-sectional study was conducted among 5,000 adolescent girls from 55 randomly selected schools. The data were collected by using Dysmenorrhea questionnaire and numerical pain rating scale along with demographic details. The data were analysed using Jamovi -open statistical software version 2.6.44. A bivariate logistic regression model was computed and variables whose p-value was < 0.05 in the bivariate logistic regression analysis were further included in the multiple logistic regression analysis. The prevalence of primary dysmenorrhea was found among 3441 (68.82%), 1686 (49.01%) had mild pain, 1496 (43.4%) had moderate pain, 259 (7.52%) had severe pain. Multiple logistic regression revealed, factors such as mothers with and without dysmenorrhea, having menstruation more than once in a month, menstruation once in two months, lethargy and tiredness day before menstruation, lethargy and tiredness day after, irritability on the day before menstruation, and constipation on the first day of menstruation were associated with primary dysmenorrhea. The prevalence of dysmenorrhea is high among adolescent girls, which highlights the need for early diagnosis and development and implementation of interventions to promote the school health and wellbeing.

PMID:42337292 | DOI:10.1038/s41598-026-59005-9

Sci Rep. 2026 Jun 23. doi: 10.1038/s41598-026-57002-6. Online ahead of print.

ABSTRACT

Visceral leishmaniasis (VL) remains a lethal parasitic disease, disproportionately affecting resource-limited regions where sustained control measures are often economically and logistically impractical. Consequently, cost-effective and sustainable strategies tailored to seasonal transmission patterns are urgently needed. Because temperature and rainfall strongly influence sandfly populations, aligning control efforts with seasonal transmission dynamics may enhance effectiveness while reducing costs. This study proposes an impulsive control strategy within a temperature- and rainfall-dependent VL transmission model to assess how strategically timed, short-term interventions optimize disease control. We examine the effects of intervention timing, frequency, and coverage for measures including sandfly breeding site elimination, insecticide spraying, and culling infected reservoir animals. Theoretical analysis shows that the disease-free periodic solution is locally asymptotically stable when the basic reproduction number ([Formula: see text]) is below one, while endemic persistence occurs when [Formula: see text]. The calibrated model closely reproduced observed seasonal transmission patterns, providing a robust basis for evaluating interventions under climatic forcing. Global sensitivity analysis revealed that vector-related parameters consistently drive infection burden, while reservoir parameters show negligible effects, indicating that vector control should be prioritized over reservoir culling for cost-effective VL management. Simulations indicate that targeted interventions implemented for only a few weeks annually substantially reduce transmission. Although vector control and reservoir culling independently decrease cases, their combined application is more effective. A biannual one-week intervention reduces human cases by 95.11%, increasing to 96.6% when extended to two weeks. Initiating interventions six weeks after peak infection yields the most substantial long-term impact, achieving a 98.89% reduction at 85% coverage.

PMID:42337291 | DOI:10.1038/s41598-026-57002-6