Tag: statistics

Neurorehabil Neural Repair. 2026 Feb 28:15459683261418670. doi: 10.1177/15459683261418670. Online ahead of print.

ABSTRACT

BackgroundThe Time to Walking Independently after Stroke (TWIST) prediction tool is designed to predict the number of post-stroke weeks at which patients are expected to achieve walking independence. The external validation of the TWIST tool’s clinical applicability and generalizability has been desired.ObjectiveWe performed a geographic external validation of TWIST prediction in a multicenter prospective cohort.Patients and MethodsAdult post-stroke patients with lower-limb weakness and inability to walk independently were enrolled. Each patient’s TWIST score (max. score: 4 points) was calculated using age, knee-extension strength, and the Berg Balance Scale score at 1 week post-stroke. The TWIST score predicts independent walking by 4, 6, 9, 16, or 26 weeks post-stroke, and we calculated the overall fit, calibration, and discrimination at each of these timepoints to assess the model’s performance.ResultsThe validation cohort consisted of 145 patients (median age 73 years, 44% women, 36% moderate-severe stroke). At 9 and 26 post-stroke weeks, 60.7% and 72.4% of the patients achieved walking independence. The overall fit explained a moderate proportion of the outcome’s variance (Nagelkerke R² = 0.28-0.49), and the discrimination performance was good (c-statistic >0.75). Calibration performance showed over-prediction at all timepoints (calibration-in-the-large = -1.62 to -0.34). Higher TWIST scores (3 or 4 points) over-predicted early post-stroke; lower TWIST scores (1 or 2 points) became increasingly over-predictive over time.ConclusionsThe TWIST prediction tool optimistically predicted walking independence in Japanese patients with stroke. Further validation studies are necessary to assess this tool’s precise clinical impact and generalizability.Clinical Trial Registration URL:https://www.umin.ac.jp/UMIN000050588.

PMID:41761786 | DOI:10.1177/15459683261418670

Lang Speech. 2026 Feb 28:238309261419120. doi: 10.1177/00238309261419120. Online ahead of print.

ABSTRACT

This tutorial paper introduces two approaches to modeling tongue contour data obtained with DeepLabCut using multivariate generalized additive models (MGAMs) and multivariate functional principal component analysis (MFPCA). For each method, we present a fully commented analysis of two illustrative data sets: VC coarticulation in Italian and Polish, and consonant emphaticness in Lebanese Arabic. All the materials (inlcuding data and code) are available in the research compendium of the tutorial at https://github.com/stefanocoretta/mv_uti. We conclude by discussing advantages and disadvantages of the two methods (MGAM and MFPCA) and we recommend researchers to prefer MFPCA over MGAM as an initial step for modeling tongue contours.

PMID:41761784 | DOI:10.1177/00238309261419120

Leuk Lymphoma. 2026 Feb 28:1-11. doi: 10.1080/10428194.2026.2633180. Online ahead of print.

ABSTRACT

In a Norwegian national cross-sectional survey, we assessed the burden of selected late effects (LEs) by a 95-item questionnaire in tumor-free Hodgkin lymphoma survivors (HLSs) diagnosed at age ≥60 years. Responses were compared to age- and sex-matched controls. A total of 290 older HLSs diagnosed 2000-2021 received the questionnaire, 193 (67%) were included. Median age at survey was 76 years (range 63-92) and median time since diagnosis 7 years (2-23). Compared to controls, HLSs reported significantly higher rates of heart failure (10% vs. 6%), atrial fibrillation (19% vs. 14%), memory problems (48% vs. 37%), other cognitive difficulties (34% vs. 17%) and chronic fatigue (29% vs. 13%). HLSs scored lower on physical and mental health-related quality of life (HRQoL) and more often reported needing help with basic (P-ADL) and instrumental activities of daily living (I-ADL). However, differences were small, only for fatigue and dependence in I-ADL did the difference reach moderate statistical effect size.

PMID:41761714 | DOI:10.1080/10428194.2026.2633180

J Neurotrauma. 2026 Feb 28:8977151261424703. doi: 10.1177/08977151261424703. Online ahead of print.

ABSTRACT

Individuals experiencing severe polytrauma are typically transported to the highest level of care as soon as possible, including helicopter evacuation from remote and/or rural environments. However, several recent preclinical and clinical studies have suggested that aeromedical evacuation exacerbates central nervous system injury and inflammation, and potentially results in increased mortality, questioning the right time and conditions under which to fly. Twenty-four swine with moderate-to-severe rotational traumatic brain injury (TBI) and ∼40% blood loss were randomly assigned to standard (∼8500 feet), tactical (evasive maneuvering), or mock (stationary on ground) helicopter (U.S. Army Black Hawk; HH-60M model) evacuation 2 h post-injury, with standard recommended therapies initiated in-flight. Results indicated that tactical evacuation was associated with increased cerebral perfusion pressure and inflammation (IL-6) post-flight relative to the standard and mock evacuation profiles, even after statistically controlling for pre-flight trauma procedures. Although the overall mortality rate was ∼25%, indicating severe polytrauma, no differences in mortality were observed as a function of aeromedical evacuation scenarios. Primary biomarkers of hemorrhagic shock, traumatic brain injury, lung and kidney pathology were also negative for aeromedical evacuation effects. In summary, the medical benefits associated with immediate (i.e., within a few hours of injury) helicopter evacuation of severe polytrauma patients likely outweigh the few increased complications associated with flight, as the latter may only be present during more extreme helicopter evacuation scenarios. Additional studies are needed to address potential adjunctive therapies that can be administered pre-flight to minimize the potential adverse effects of tactical flight.

PMID:41761707 | DOI:10.1177/08977151261424703

Eur J Neurol. 2026 Mar;33(3):e70527. doi: 10.1111/ene.70527.

ABSTRACT

BACKGROUND: Insulin resistance and impaired insulin secretion are hallmarks of type 2 diabetes (T2D) and may influence risks of complications including dementia. We investigated dementia risk across T2D subgroups defined by beta-cell function and insulin sensitivity.

METHODS: We used Homeostasis Model Assessment-2 indices of beta-cell function (HOMA2-B) and insulin sensitivity (HOMA2-S) to classify 7221 individuals with recently diagnosed T2D into insulinopenic (low HOMA2-B, high HOMA2-S), classical (low HOMA2-B, low HOMA2-S), and hyperinsulinemic (high HOMA2-B, low HOMA2-S) subgroups. Incident dementia was ascertained by validated hospital diagnosis codes and dementia-specific medication over 13 years. Absolute risks were estimated using the Aalen-Johansen estimator and adjusted hazard ratios (aHRs) using Cox regression.

RESULTS: Over a median follow-up of 9 years, 179 (2.5%) developed dementia. The 10-year risk (95% CI) was 3.8% (2.4%-5.8%) in the insulinopenic subgroup versus 2.8% in both classical (2.3%-3.5%) and hyperinsulinemic (2.0%-3.8%) subgroups. Compared with classical T2D, aHRs (95% CI) were 1.31 (0.83-2.09) for insulinopenic and 1.10 (0.78-1.54) for hyperinsulinemic T2D. No robust associations with dementia were observed with insulin resistance (HOMA-IR) or C-peptide levels, although compared to the lowest C-peptide levels (quartile 1), aHRs (95% CI) were decreased at 0.67 (0.45-1.01) in quartile 2, 0.73 (0.48-1.09) in quartile 3, and 0.89 (0.59-1.33) in quartile 4.

CONCLUSIONS: We found no clear associations between T2D subgroup, insulin resistance, or C-peptide level at T2D diagnosis and dementia risk. The numerically higher risk in those with lower insulin secretion was statistically imprecise and warrants further study.

PMID:41761701 | DOI:10.1111/ene.70527

Stat Med. 2026 Mar;45(6-7):e70461. doi: 10.1002/sim.70461.

ABSTRACT

One major bias source in causal inference for clinical trials is unmeasured confounding. We propose an innovative, practical Bayesian modeling approach to adjust for unmeasured confounding effects and obtain precise causal average treatment effect estimates for two-arm randomized controlled clinical trials. This approach includes model reparameterization and an iterative algorithm, with a causal inference framework incorporated with unmeasured confounders and related statistical distributions. Model non-identifiability resulting from adjusting for unmeasured confounding is a major inferential problem. Reparameterization transforms one or multiple unmeasured confounders into a single reparameterized unmeasured confounder and can remove model non-identifiability from the model specification of unmeasured confounders. The iterative algorithm consists of detailed steps for inference after model reparameterization and can remove model non-identifiability from prior sensitivity to unmeasured confounders. It includes iterating the prior distribution of the reparameterized unmeasured confounder by certain rules, aggregating posterior means and variances over different prior choices, and obtaining posterior estimates for the average treatment effect. Its essential idea is to make unreliable prior information on unmeasured confounders as close to data information as possible. Compared with usual methods, our approach produces robust effect estimates and correctly concludes statistical significance. From an example using real clinical data, this approach effectively adjusts for confounding effects when we do not adjust for measured confounders. Our approach is also generalizable to other clinical study designs and may be beneficial to applications where data collection is difficult for certain variables or causal relationships are not well understood.

PMID:41761686 | DOI:10.1002/sim.70461

Pediatr Transplant. 2026 Apr;30(3):e70283. doi: 10.1111/petr.70283.

ABSTRACT

INTRODUCTION: Kidney transplantation remains the optimal treatment for children with end-stage renal disease (ESRD), 25%-40% of which are estimated to be caused by congenital malformations and genetic syndromes. Given the widespread nature of this surgical procedure, ocular complications may arise from the operation itself or from subsequent medical treatments. The aim of this study is to determine whether there are postoperative refractive changes in pediatric patients who have undergone kidney transplantation and to detect the presence of refractive changes that may cause amblyopia in patient follow-ups.

METHODS: The electronic medical records of 1144 patients who underwent kidney transplantation at the Akdeniz University Hospital Organ Transplant Center between January 2019 and January 2024 were reviewed retrospectively. Of these, 84 pediatric patients who had undergone a complete ophthalmologic examination at least 1 year after kidney transplantation and had no missing data were included in the study. For both eyes, all data were recorded, including Best Corrected Visual Acuity (BCVA), refractive error (measured with the KR-8900; Topcon, Tokyo, Japan), spherical equivalent refractions (SER), slit-lamp examination of the anterior segment, and a dilated fundus examination.

RESULTS: The average age of patients who underwent kidney transplantation in the study is 13.01 ± 3.43 (6-18). The average follow-up period was 51.81 ± 33.5 (45-129) months. Thirty-five (41.7%) of the patients are female, and 49 (58.3%) are male. Cataracts were observed in 9 (10.7%) patients during follow-up after transplantation. Cataract development was observed on average in 5.6 years. Posterior subcapsular cataracts were observed in seven patients, cortical cataract in one patient, and anterior polar cataract in one patient. The mean preoperative visual acuity value in patients who developed cataracts after kidney transplantation was 0.00 logMAR, while it was measured as 0.19 logMAR in the postoperative period, and this decrease is statistically significant (p = 0.027). In patients who did not develop cataracts during the follow-up period, there was no statistically significant change in visual acuity in both eyes (p = 0.109). When all eyes are evaluated, the change in SER after kidney transplantation is not statistically significant compared with before (p = 0.689 for the right eye, p = 0.596 for the left eye).

CONCLUSION: Although children receive longer-term immunosuppressive treatment, their cataract development rates are lower than those of adults. Despite intensive and prolonged immunosuppression therapy after kidney transplantation, cataract development and refractive changes in the pediatric age group are at an acceptable level. Especially in children who are too young to express themselves clearly, monitoring refractive changes is crucial to prevent permanent vision loss.

PMID:41761679 | DOI:10.1111/petr.70283

Stress Health. 2026 Apr;42(2):e70159. doi: 10.1002/smi.70159.

ABSTRACT

Tuberculosis (TB) remains a leading global infectious cause of illness and death, despite being preventable and curable, with the highest burden in low- and middle-income countries, particularly in Southeast Asia and Africa. TB is closely linked with mental health, as psychological distress manifested by anxiety, depression, and somatic symptoms is a common and significant comorbidity. However, nationally representative data on the prevalence of psychological distress among TB patients are limited. This systematic review and meta-analysis aimed to estimate the pooled prevalence of psychological distress and identify associated factors in TB patients in Ethiopia. A systematic review and meta-analysis of five studies involving 2117 participants was conducted, showing very high heterogeneity (I² = 99.8%). A comprehensive search of PubMed, Scopus, Web of Science, Google Scholar, PsycINFO, and AJOL identified studies published from June 2000 to August 1, 2025. The review followed PRISMA 2020 guidelines, and study quality was assessed using the Joanna Briggs Institute Checklist for Analytical Cross-Sectional Studies. Data were analysed in STATA version 16 using a random-effects model with 95% confidence intervals. Heterogeneity was evaluated using the I² statistic (p < 0.05 indicating significance). Publication bias was assessed using a funnel plot with asymmetry distribution and Egger’s test revealed a statistically significant result (p = 0.007) and meta-regression was conducted to explore potential sources of heterogeneity. The pooled prevalence of psychological distress among 2117 adult tuberculosis patients was 47.47% (95% CI; 11.95, 82.98). In this review, stigma (AOR = 2.21, 95 CI: 1.49, 3.26), and co-infection (AOR = 2.89, 95% CI: 1.57, 5.35) were statistical significant associated with psychological distress. Psychological distress affecting nearly half adult tuberculosis patients in Ethiopia. Stigma and co-infection are statistically significant with psychological distress. Therefore, integrate mental health screening and psychosocial support into tuberculosis programs, strengthen community-based stigma reduction strategies, and provide tailored care for TB-HIV co-infected patients, especially in rural areas with limited resources is essential.

PMID:41761667 | DOI:10.1002/smi.70159

Med Phys. 2026 Mar;53(3):e70361. doi: 10.1002/mp.70361.

ABSTRACT

BACKGROUND: Breath-hold PET imaging helps reduce respiratory motion artifacts in thoracoabdominal scans. However, its clinical application is limited by the short acquisition time, which results in significant image noise and poor lesion detectability. Enhancing image quality under such conditions remains a technical challenge.

PURPOSE: To improve the image quality of 15-s breath-hold PET scans, we investigated a deep learning-based framework using a diffusion probabilistic model. The goal was to suppress noise and enhance lesion visibility while maintaining quantitative accuracy under severely limited acquisition durations.

METHODS: We propose TAM-DiffPET, a denoising diffusion probabilistic model (DDPM) augmented with Temporal Attention Modulation (TAM) to refine intermediate feature representations by injecting diffusion time-step embeddings and temporal contextual cues. The model was trained on paired PET datasets comprising 15-s breath-hold scans and 5-min free-breathing scans from 230 patients at Ren Ji Hospital; 180 cases were used for training and 50 for quantitative and qualitative evaluation. Performance was assessed using PSNR, SSIM, and voxel-wise SUV distributions within lesion ROIs. Visual and statistical comparisons were conducted against U-Net, CycleGAN, and a vanilla DDPM.

RESULTS: The proposed method demonstrated superior performance compared to existing deep learning-based approaches. Quantitatively, it achieved the highest PSNR (40.2 ± 1.2 dB) and SSIM (0.995 ± 0.004), significantly outperforming previous deep learning based methods such as U-Net, CycleGAN, and DDPM. Voxel-wise SUV error distributions showed lower standard deviation and mean absolute error within lesion ROIs. Visual assessments revealed enhanced lesion contrast, sharper anatomical boundaries, and reduced background noise. Difference maps confirmed minimal deviation from the 5-min reference scans. Furthermore, SUV distribution analysis across representative patients confirmed that the proposed method preserves tracer uptake consistency, offering improved fidelity in clinical lesion quantification.

CONCLUSION: Our diffusion-based framework effectively denoises breath-hold PET images acquired under ultrashort durations, offering improved visual clarity and quantitative fidelity. These results support its clinical utility in motion-prone scenarios, such as thoracic or abdominal imaging, and suggest its potential for enhancing diagnostic accuracy while reducing scan time and radiation burden on patients.

PMID:41761600 | DOI:10.1002/mp.70361

J Gerontol A Biol Sci Med Sci. 2026 Feb 27:glag062. doi: 10.1093/gerona/glag062. Online ahead of print.

ABSTRACT

BACKGROUND: The INVEST in Bone Health Trial examined the effects of weight loss (WL), WL plus resistance training (WL+RT), or WL plus weighted vest use (WL+VEST) on musculoskeletal health. This secondary analysis evaluated changes in muscle area and density using computed tomography (CT) and lean and fat mass using dual-energy X-ray absorptiometry (DXA).

METHODS: 150 participants (50/group) were randomized to 12-months of WL, WL+RT, or WL+VEST, undergoing CT and DXA scans at baseline, six- and 12-months. DXA measured lean and fat mass, while CT assessed muscle and intermuscular adipose tissue (IMAT) cross-sectional area (CSA) and density. Mixed linear models evaluated changes and treatment effects, and partial Pearson’s correlations examined relationships between weight change and CT/DXA outcomes.

RESULTS: Participants (66.4±4.6 years,75% female,69% white) were living with overweight (14.7%) or obesity (85.3%). All groups achieved similar and significant weight loss (∼10%). At 12-months, WL+RT increased mid-thigh muscle CSA (0.5%, p < 0.05), improved muscle density (3.7-5.9%, p < 0.03), and reduced IMAT (20-22%, p < 0.05) and fat masses (22-26.8%, all p < 0.061). At the trunk, WL+VEST showed a trend toward muscle preservation and improved density (4.2%, p = 0.08) compared to WL, but had minimal impact on other measures. Differences between WL+VEST and WL were insignificant (all p > 0.05), but group comparisons showed improvements for WL+RT. Weight loss correlated with increased muscle density (r < 0, p < 0.001) but reduced muscle CSA and IMAT (r > 0, p < 0.001), indicating improved quality but reduced quantity.

CONCLUSION: Our findings underscore the significance of weight loss-associated muscle loss, highlighting progressive RT as a minimally effective preservation strategy.

PMID:41761582 | DOI:10.1093/gerona/glag062