Category: Statistics

Musculoskeletal Care. 2026 Sep;24(3):e70249. doi: 10.1002/msc.70249.

ABSTRACT

PURPOSE: Athlete-specific patient-reported outcome measures (PROMs) are essential for evaluating shoulder function in sports contexts; however, their measurement properties, sport-specific applicability and responsiveness remain inconsistently established. This study aimed to critically appraise the development, psychometric properties and cross-cultural adaptations of athlete-specific shoulder PROMs, with a particular focus on reliability, validity and responsiveness.

METHODS: A comprehensive search was conducted in MEDLINE, Embase, Web of Science, SPORTDiscus and Scopus up to September 2025, complemented by manual reference screening. Studies were considered eligible if they evaluated at least one psychometric property of PROMs specifically developed to assess shoulder function in athletic populations. Methodological quality was appraised using the COSMIN Risk of Bias checklist, and overall study quality was rated using the Quality Appraisal for Clinical Measurement Studies tool. Meta-analysis was considered but not feasible due to substantial heterogeneity in study populations, PROMs and statistical indices.

RESULTS: Twenty studies met the inclusion criteria: six original PROMs and fourteen cross-cultural adaptations, mostly of the KJOC. Reliability was good-to-excellent (ICC = 0.88-0.97) across PROMs. Construct validity was strongest for the KJOC and FAST, while single-item PROMs (SSV-Sport, SPORTS) showed feasibility but narrower construct coverage and ceiling effects. Responsiveness was best supported for the FAST and SSV-Sport, whereas longitudinal responsiveness was rarely examined in translations.

CONCLUSIONS: The FAST and KJOC exhibit the most consistent and comparatively robust measurement evidence among athlete-specific shoulder PROMs. Single-item scores offer practicality but limited scope, and future validation studies should prioritise responsiveness, interpretability and anchor-based minimal clinically important differences to enhance clinical applicability.

PMID:42420771 | DOI:10.1002/msc.70249

JMIR Med Inform. 2026 Jul 8;14:e84804. doi: 10.2196/84804.

ABSTRACT

BACKGROUND: Supraspinatus tendon pathologies are common causes of shoulder pain. Magnetic resonance imaging (MRI) is the reference imaging method but requires expert interpretation. Automated classification may improve diagnostic consistency and support musculoskeletal imaging workflows.

OBJECTIVE: This study aimed to develop and evaluate a hierarchical deep learning model to classify supraspinatus tendon status as intact tendons, tendinopathy/partial-thickness tears, or full-thickness tears.

METHODS: A total of 1192 shoulder MRI scans were analyzed. The hierarchical system consisted of a left-right orientation classifier, a full-thickness tear detector (model F), and a classifier for distinguishing intact tendons from tendinopathy/partial-thickness tears (model ITP). A flat 3-class model served as a baseline comparator. Performance was evaluated on both an internal test set and an independent external cohort.

RESULTS: On the internal test set, the hierarchical system achieved a system-level sensitivity of 68.1% for tendinopathy/partial-thickness tears, outperforming the flat baseline (57.4%) while maintaining comparable sensitivity for full-thickness tears (hierarchical vs flat: 94.1% vs 95.1%). On the independent external cohort, the sensitivity for tendinopathy/partial-thickness tears was 45.5% for the hierarchical model and 18.2% for the flat baseline. The hierarchical model also showed a numerically higher balanced accuracy (hierarchical vs flat: 68.1% vs 64.5%), macro F1-score, and macro area under the curve, although its overall accuracy was lower (76.4% vs 79.8%).

CONCLUSIONS: A hierarchical deep learning approach that mirrors clinical diagnostic reasoning may improve the recognition of tendinopathy and partial-thickness tears, a challenging category for nonspecialist readers. Given the overlapping CIs, these findings should be interpreted as indicative of a trend rather than definitive improvement. External validation supports feasibility across different MRI sources, though the predominance of data from a single institution limits generalizability and warrants further prospective evaluation.

PMID:42420768 | DOI:10.2196/84804

Int J Cardiovasc Imaging. 2026 Jul 8. doi: 10.1007/s10554-026-03769-8. Online ahead of print.

ABSTRACT

BACKGROUND: In this exploratory diagnostic study, although our previous study demonstrated the strong prognostic value of CZT-SPECT-derived stress myocardial blood flow (sMBF) and myocardial flow reserve (MFR) in patients with ischemia and non-obstructive coronary artery disease (INOCA), their diagnostic value and optimal cut-off values for coronary microvascular dysfunction (CMD) remain unclear.

METHODS: We prospectively recruited 56 INOCA patients referred from cardiovascular medicine to nuclear medicine. Each underwent CZT-SPECT and coronary angiography-derived index of microcirculatory resistance (caIMR) within one week. CMD was defined as caIMR > 25 U. Bonferroni correction was applied for multiple comparisons of regional coronary physiological parameters.

RESULTS: Based on caIMR, CMD was present in 42 INOCA patients (75%). After correction, regional MFR (LAD: 2.9 ± 0.9 vs. 3.7 ± 0.7, p =0.02; LCX: 2.8 ± 1.0 vs. 4.0 ± 1.5, p = 0.02; RCA: 2.9 ± 1.1 vs. 3.9 ± 0.7, p = 0.04) and global MFR (3.0 ± 0.9 vs. 3.9 ± 0.8, p < 0.01) were significantly lower in the CMD group, while no significant difference was observed in regional sMBF. Only global sMBF (r=-0.43, p < 0.01) and global MFR (r=-0.32, p = 0.02) showed moderate inverse correlations with caIMR. The optimal diagnostic cut-offs were global sMBF ≤ 3.8 mL/min/g (AUC = 0.68, 95%CI 0.55-0.80, p = 0.02) and global MFR ≤ 2.9 (AUC = 0.80, 95%CI 0.68-0.90, p < 0.01). DeLong test showed no statistically significant difference in diagnostic efficacy between the two parameters (95%CI for AUC difference: -0.06 to 0.30, p = 0.19). Conclusions These preliminary results demonstrate that CZT-SPECT-derived global sMBF and MFR provide modest diagnostic accuracy for identifying CMD in INOCA patients. This non-invasive approach may support identification of CMD and help guide clinical decision-making.

TRIAL REGISTRATION: ChiCTR2000037112. Registered 27 August 2022, https://www.chictr.org.cn/.

PMID:42420743 | DOI:10.1007/s10554-026-03769-8

Methods Mol Biol. 2026;3041:213-227. doi: 10.1007/978-1-0716-5304-3_10.

ABSTRACT

Synthetic biology aims to customize biological systems by programming genetic circuits. However, the scale and complexity of genetic circuits are limited by a shortage of composable, programmable, and orthogonal regulatory parts. Recently, split-intron-enabled trans-splicing riboregulators (SENTRs) have emerged as a promising tool for regulating gene expression at the post-transcriptional level, featuring low leakage expression, wide dynamic range (> 1000-fold), high predictability using machine learning, and orthogonality across multiple intronic components. SENTR’s composability with other regulatory modalities, such as split inteins, enables the establishment of a novel split-biomolecule-enabled circuit design paradigm, unleashing the information-processing capacity of a single regulator gene for complex cellular logic computation with up to six inputs. Here, we describe the methods and strategies to implement SENTRs for efficient gene regulation, including computational design, experimental assessment, and statistical analysis of SENTR-based genetic circuits. Validated on ten genes encoding fluorescent proteins, transcription factors, and ncRNAs, this method can be readily utilized to develop SENTRs for diverse applications, such as stringent gene regulation, complex logic computation, and biosensing for intracellular RNAs or physiological biomarkers.

PMID:42420730 | DOI:10.1007/978-1-0716-5304-3_10

J Pharmacokinet Pharmacodyn. 2026 Jul 8;53(5):37. doi: 10.1007/s10928-026-10044-9.

ABSTRACT

The evolution of nonlinear mixed effects (NLME) modeling reflects a continuous cycle of innovation based on advances in numerical methods and computational power. This commentary outlines the evolution of NLME modeling that began with linearization-based approaches in the 1980s, progressed through sampling-based methods in the 2000s, and is now entering a new phase shaped by AI. Variational autoencoders bridge classical NLME modeling with AI-based methods allowing the development and application of AI-augmented PMX models. This opens the route for integrating multimodal data and addressing increasingly complex modeling challenges.

PMID:42420693 | DOI:10.1007/s10928-026-10044-9

Acad Psychiatry. 2026 Jul 8. doi: 10.1007/s40596-026-02395-9. Online ahead of print.

ABSTRACT

OBJECTIVE: Suicidal ideation is a pressing mental health issue among medical students worldwide, but there has been limited investigation into this phenomenon among medical students. Identifying the associated risk factors is essential for creating targeted prevention strategies. This study aims to assess the prevalence of suicidal ideation and to identify the risk factors associated with it among medical students.

METHODS: This cross-sectional study surveyed 705 medical students at Islamic Azad University, Mashhad Medical Sciences, in 2023-2024. Participants completed demographic and psychometric questionnaires including the Beck Scale for Suicidal Ideation. Data were analyzed using descriptive statistics, non-parametric tests, and multivariate models to identify independent risk factors for suicidal ideation, with significance set at p < 0.05.

RESULTS: Approximately 78.3% of participants reported experiencing suicidal thoughts, while 18.6% demonstrated a readiness for suicide, and 3.1% expressed suicidal intent. Multivariate analysis revealed significant independent associations with a history of drug use, prior psychiatric disorders, recent relationship breakups, and academic probation (all p < 0.001). In contrast, age, gender, educational level, and place of residence did not show any significant associations.

CONCLUSION: Suicidal ideation is alarmingly prevalent among medical students. Key risk factors such as substance use, psychiatric disorders, relationship breakdowns, and academic challenges necessitate immediate intervention. It is essential to implement systematic psychological screening programs, ensure accessible mental health services, develop academic support initiatives, and promote institutional efforts to destigmatize seeking help within medical education settings.

PMID:42420685 | DOI:10.1007/s40596-026-02395-9

Ann Hematol. 2026 Jul 9. doi: 10.1007/s00277-026-07171-1. Online ahead of print.

ABSTRACT

Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment landscape for relapsed/refractory (R/R) lymphoma. However, heterogeneous responses and treatment-related toxicities remain significant challenges. The prognostic nutritional index (PNI), reflecting both nutritional status and systemic immune competence, has emerged as a potential biomarker in various malignancies. This study aimed to evaluate the predictive value of the PNI assessed specifically prior to lymphodepletion in patients with R/R lymphoma receiving CAR T-cell therapy. We retrospectively analyzed 449 patients with R/R lymphoma treated with CAR T cells. The PNI was calculated using serum albumin levels and absolute lymphocyte counts measured before administering lymphodepleting chemotherapy. The optimal PNI cutoff for predicting survival was determined to be 39.2 using maximally selected rank statistics. The patients were stratified into high-PNI (> 39.2, n = 363) and low-PNI (≤ 39.2, n = 86) groups on the basis of the PNI cutoff value. The median age of the patients was 52 years. All patients had R/R aggressive B-cell lymphoma and were treated with CAR T cells. Compared with patients in the low-PNI group, patients in the high-PNI group achieved significantly superior clinical responses, with higher overall response rates (ORRs: 65.5% vs. 44.2%, P < 0.001) and complete response rates (CRRs: 52.2% vs. 27.9%, P < 0.001). The median follow-up period was 33.12 months, and long-term survival markedly improved among patients in the high-PNI group; the 5-year overall survival (OS) rates were 59.02% vs. 21.88% (P < 0.001), and the 5-year progression-free survival (PFS) rates were 42.69% vs. 13.29% (P < 0.001) for patients in the high- and low-PNI groups, respectively. In terms of safety, multivariate analysis confirmed that a high PNI independently reduced the risk of any-grade CRS (P = 0.047), but was not significantly associated with grade ≥ 3 CRS (P = 0.121). No significant association was observed between a high PNI and the occurrence or severity of ICANS (all P > 0.05). Multivariate analysis revealed that a PNI > 39.2 remained an independent predictor of both OS (HR = 0.425, P < 0.001) and PFS (HR = 0.542, P < 0.001). The pre-lymphodepletion PNI is a simple, noninvasive, and robust tool for predicting therapeutic efficacy, long-term survival, and treatment-related toxicity in patients with R/R lymphoma receiving CAR T-cell therapy. A PNI threshold of 39.2 provides a valuable reference for risk stratification and clinical management.

PMID:42420673 | DOI:10.1007/s00277-026-07171-1

Surg Today. 2026 Jul 8. doi: 10.1007/s00595-026-03398-7. Online ahead of print.

ABSTRACT

PURPOSE: We evaluated the perioperative outcomes and learning process during the introduction of uniportal video-assisted thoracoscopic surgery (uVATS) at a university hospital.

METHODS: uVATS was initiated by two experienced thoracic surgeons using a safety-oriented, stepwise approach with a flexible team rotation. We retrospectively reviewed 83 consecutive patients (84 lesions) who underwent uVATS between October 2020 and December 2024 for clinically node-negative primary lung cancer or metastatic lung tumors. Learning patterns were analyzed using the cumulative sum (CUSUM) of the operative time.

RESULTS: The procedures included 46 lobectomies and 38 segmentectomies (23 complex). No conversion to thoracotomy occurred; four cases (4.8%) required conversion to multiportal VATS (mVATS) owing to lymph node dissection difficulty. The median operative time was 174 min, and reoperation was performed in two patients (2.4%). Among the 84 lesions, 76 were primary lung cancers, and eight were non-primary lesions. Among the primary lung cancer cases, the median tumor size was 19.0 mm. Most patients had early stage disease, including stage 0 (n = 5), stage IA1 (n = 17), stage IA2 (n = 19), stage IA3 (n = 14), and stage IB (n = 12), whereas a smaller proportion had more advanced disease (stage IIA, n = 2; stage IIB, n = 4; stage IIIA, n = 3). During a median follow-up period of 2.6 years, tumor recurrence was observed in five patients, including two cases of local recurrence. A CUSUM analysis did not demonstrate a distinct early learning phase, and operative performance remained relatively stable from the initial cases.

CONCLUSIONS: uVATS was safely introduced without any early performance deterioration, likely reflecting the transfer of skills from prior open and mVATS experience.

PMID:42420671 | DOI:10.1007/s00595-026-03398-7

Mem Cognit. 2026 Jul 8. doi: 10.3758/s13421-026-01894-2. Online ahead of print.

ABSTRACT

Implicit statistical learning of a sequence of information is determined by several factors, including the number of repetitions of the sequence and the distance between each repetition. In the present study, we used a Hebbian version of the lexical decision task in which participants must decide whether the items presented in the center of a computer screen are words or non-words. Unbeknownst to the participants, a sequence of three words is presented and repeated in the same order several times (30 times). For each group of participants, we manipulated the distance between each repetition of the triplet of words by inserting the same number of filler items (i.e., on average, 4, 7, 10, 20, 30 or 60). Our results show that learning of the sequence is still possible at large distances (60 filler items apart) and that the learning rate best fit a power law. Furthermore, the processing speed of the words in the repeated triplet is differentially affected by the distance between repetitions. These data thus provide novel constraints for current models of implicit statistical learning.

PMID:42420669 | DOI:10.3758/s13421-026-01894-2

Aesthetic Plast Surg. 2026 Jul 8. doi: 10.1007/s00266-026-06116-3. Online ahead of print.

ABSTRACT

INTRODUCTION: Recent research suggests that body contouring surgeries may reduce benzodiazepine (BNZ) use in patients with anxiety or depressive disorders. This study explores whether similar benefits occur in women with lipedema-a chronic adipose disorder causing pain, limited mobility, and psychological distress-who are often prescribed BNZ.

MATERIALS AND METHODS: We conducted a retrospective observational study on 100 adult female patients with Stage I-III lipedema undergoing tumescent or water-assisted liposuction between 2019 and 2024. All participants were on stable BNZ therapy for at least six months before surgery. The primary outcome was BNZ usage at six months postoperatively. Secondary outcomes included anxiety (GAD-7), pain (VAS), sleep quality (PSQI), and body image (BODY-Q) and assessed pre- and post-surgery using validated instruments.

DISCUSSION: At six months, 77% of patients reduced or discontinued BNZ (32% stopped entirely), with average daily dosage decreasing from 3.2 ± 1.1 to 1.4 ± 1.2 mg (p < 0.001). Statistically significant improvements were also observed in anxiety, pain, sleep quality, and body image (all p < 0.001). Reductions in BNZ use correlated with improvements in pain (r = 0.56), anxiety (r = 0.47), and body image (r = – 0.52). Only minor complications occurred (8%), and no major adverse events were reported.

CONCLUSION: Liposuction for lipedema not only improves physical symptoms but also supports psychological recovery, reducing dependence on benzodiazepines. These findings highlight the potential of surgical treatment as part of an integrated approach to managing chronic conditions with both somatic and mental health components. Further research is needed to confirm long-term effects and underlying mechanisms.

LEVEL OF EVIDENCE I: Level I, therapeutic study using a properly randomized controlled trial. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

PMID:42420665 | DOI:10.1007/s00266-026-06116-3