Category: Statistics

J Am Coll Surg. 2026 Jan 30. doi: 10.1097/XCS.0000000000001814. Online ahead of print.

ABSTRACT

BACKGROUND: Robotic surgery benefits include a binocular vision, increased dexterity, and adjustable hand control speed. We hypothesized perforation rate of robotic Heller myotomy (RH) was lower than laparoscopic Heller myotomy (LH).

STUDY DESIGN: A retrospective cohort study of a prospectively maintained database of 135 patients diagnosed with achalasia or esophagogastric junction outlet obstruction who underwent Heller myotomy by a single surgeon were identified for inclusion. After exclusions 107 patients were analyzed. Primary outcome was intraoperative perforation rate. Secondary outcomes were length of stay, short and long-term GERD Health Related Quality of Life (GERD-HRQL), dysphagia and Eckardt scores. Results are expressed mean + SD and statistical analysis performed with GraphPad Prism (10.4.2).

RESULTS: RH had a lower rate of intraoperative perforation (n=0), compared to LH (n=3, 13.6%) (p<0.01). The median length of stay was shorter for the RH group 1 day verses 2 days for LH (p<0.01). RH and LH significantly improved both GERD-HRQL and Eckardt scores in short term and long-term follow-up. Long term success (Eckardt score <3) was achieved in 88% of LH and in RH (p=0.03).

CONCLUSIONS: Robotic surgery allows for a safer myotomy with a significant reduction in intraoperative perforation rate and in LOS. Robotic surgery enhanced the surgeon’s performance of an extended myotomy resulting in long term success of RH. RH has decreased complication rates and is superior to LH and is our technique of choice.

PMID:41615705 | DOI:10.1097/XCS.0000000000001814

Rheumatology (Oxford). 2026 Jan 30:keag053. doi: 10.1093/rheumatology/keag053. Online ahead of print.

ABSTRACT

OBJECTIVES: The objective of the study was to explore left atrial (LA) strain, a quantitative index of left ventricular (LV) diastolic function, in risk stratifying patients with systemic sclerosis-related pulmonary hypertension (SSc-PH).

METHODS: This was an exploratory, retrospective single-centre study of 124 patients with SSc-PH confirmed on right heart catheterization. We quantified and clustered the three components of LA global longitudinal strain (GLS): 1) Reservoir (systole); 2) Conduit (early diastole); and 3) Contractile (late diastole) using echocardiograms closest to timing of right heart catheterization. We applied both the Kaplan-Meier method and a Cox proportional hazards model to determine associations with our primary outcome of all-cause mortality.

RESULTS: Using K-means clustering, we divided our cohort into three clusters: Cluster 1 (N = 40), Cluster 2 (N = 34), and Cluster 3 (N = 50). Compared with Cluster 1, Cluster 2 had the lowest median LA conduit strain, and Cluster 3 exhibited the lowest median LA contractile strain. There was a statistically significant difference in survival between clusters (log-rank p= 0.005). Median survival was 122.4 months, 67.9 months, and 48.4 months for Cluster 1, Cluster 2, and Cluster 3, respectively. Compared with those in Cluster 1, patients in Cluster 2 and Cluster 3 had adjusted HRs of 1.46 (95% CI: 0.71, 2.97) and 2.57 (95% CI: 1.32, 5.02) for all-cause mortality, respectively.

CONCLUSION: Of the three LA GLS clusters, Cluster 3 had the shortest median survival. LA GLS may provide further risk stratification of patients with SSc-PH.

PMID:41615697 | DOI:10.1093/rheumatology/keag053

JAMA Health Forum. 2026 Jan 2;7(1):e256442. doi: 10.1001/jamahealthforum.2025.6442.

ABSTRACT

IMPORTANCE: Firearm suicides constitute a crisis in the US, accounting for more than half (55.4%) of all suicide deaths in 2023. Extreme Risk Protection Orders (ERPOs; ie, red flag laws) authorize temporary firearm removal from individuals deemed at high risk of harming themselves or others. While ERPOs are designed to reduce firearm-related suicides, whether they result in a net reduction in suicide deaths or shift firearm suicides to suicides by other methods remains an important but unresolved issue in determining their effectiveness.

OBJECTIVE: To determine the association of ERPOs with firearm suicides and nonfirearm suicides in states with sufficient postpolicy data and no confounding firearm legislation that may bias findings on ERPO outcomes.

DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, 2-way difference-in-differences event study analyses were conducted using county-level data from 2012 to 2022. All states that passed ERPO laws alone, with no other new firearm laws, from 2018 to 2020, and had at least 1 year post-ERPO laws during which no new firearm laws were passed were investigated. All states that had no existing ERPO laws and passed no new firearm legislation from 2016 to 2022 were used for comparison. The model accounted for staggered treatment timing, treatment heterogeneity, and key methodological assumptions. Data were analyzed between February 6 and October 9, 2025.

EXPOSURE: State-level ERPO law passage.

MAIN OUTCOMES AND MEASURES: County-level annual firearm suicides and nonfirearm suicides per 100 000 population, derived from Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research.

RESULTS: This study examined county-level data from 4 states passing ERPO laws alone (Massachusetts, New Jersey, New Mexico, and Rhode Island) compared with 8 that did not (Alabama, Alaska, Michigan, Minnesota, Nebraska, North Carolina, Pennsylvania, and South Carolina). ERPO passage was associated with a mean reduction of 3.79 firearm suicides per 100 000 population after 1 year (95% CI, -6.74 to -0.83; P = .01), equivalent to an estimated 675 suicides. With regard to nonfirearm suicides, no association was found in the year ERPO laws were passed (0.41; 95% CI, -1.21 to 1.94; P = .60) or in the next year (-2.45; 95% CI, -6.84 to 1.93; P = .27).

CONCLUSIONS AND RELEVANCE: In this cohort study, ERPO laws in Massachusetts, New Jersey, New Mexico, and Rhode Island were associated with substantial reductions in firearm suicides, with no evidence of substitution with nonfirearm methods. These findings support ERPOs as targeted public health interventions to reduce firearm suicides without increasing suicides by other methods.

PMID:41615664 | DOI:10.1001/jamahealthforum.2025.6442

Ann Biomed Eng. 2026 Jan 30. doi: 10.1007/s10439-025-03970-1. Online ahead of print.

ABSTRACT

PURPOSE: To establish an automated, landmark-based patellar coordinate system for standardized alignment, develop a patellar statistical shape model (SSM), and quantify 3D morphological variations associated with patellar dislocation (PD).

METHODS: Patellar surface models were reconstructed from CT/MRI scans of 54 participants (33 PD, 21 controls). An automated coordinate system was established and quantitatively validated. Demographic/morphometric risk factors were assessed using logistic regression. An SSM was built for the entire cohort, and principal component analysis (PCA) was used to extract major 3D shape modes. Between-group differences in PC scores were evaluated with multiple-testing control and covariate adjustment. A logistic regression classifier based on shape modes and demographics was evaluated using stratified 10-fold cross-validation.

RESULTS: The automated coordinate system showed high repeatability. Patellar linear dimensions and centroid size did not differ between groups and were not independent predictors. Two robust shape modes differentiated PD from controls: PC4 (thickness/facet morphology) and PC7 (facet-edge morphology). A cross-validated classifier showed good in-cohort discrimination (mean AUC ≈ 0.91).

CONCLUSION: In this cohort, PD was associated with localized 3D articular-surface shape patterns, characterized by a prominent medial facet, a flattened posterolateral facet, and accentuated facet margins, without corresponding differences in linear dimensions. The automated coordinate system and SSM provide a reproducible approach for quantitative patellar phenotyping. These shape modes may deepen understanding of PD pathomechanics and provide a quantitative basis for future, externally validated risk modeling in diverse populations.

PMID:41615643 | DOI:10.1007/s10439-025-03970-1

J Imaging Inform Med. 2026 Jan 30. doi: 10.1007/s10278-026-01843-0. Online ahead of print.

ABSTRACT

Otosclerosis is a disease affecting the middle and inner ear, characterized by abnormal bone remodeling that leads to stapes fixation and progressive hearing loss. Although high-resolution computed tomography (HRCT) is the standard imaging modality for diagnosis, its sensitivity is limited, with a high false-negative rate (FNR). This study investigates the use of radiomics and machine learning (ML) to improve diagnostic accuracy. HRCT scans from 99 subjects (48 otosclerosis, 51 controls) were analyzed, focusing on the stapes, antefenestral region (AF), and oval window (OW). From each scan, 6048 radiomic features were extracted and reduced to 1317 through feature selection. Statistical analyses and ML modeling were performed using the selected features. Sixty-seven biomarkers showed significant differences between cases and controls, primarily in the AF (56) and stapes (11); none were found in the OW. Both the AF and stapes exhibited increased heterogeneity in otosclerosis, reflecting the bone remodeling process. A reduction in the stapes’ major axis was also observed, possibly related to torsional deformation. Image transformation filters enhanced disease visibility. Among several ML classifiers tested, L2-regularized logistic regression performed best, achieving an AUC of 0.90 ± 0.06, thereby enhancing the diagnostic accuracy reported in some studies for radiologists. Hierarchical clustering of the most predictive features further confirmed their strong discriminative power. Our findings highlight the potential of radiomics and ML to standardize otosclerosis diagnosis, reduce FNR, and support surgical decision-making. Future studies should validate these results using larger cohorts and advanced imaging technologies such as Photon-Counting CT.

PMID:41615634 | DOI:10.1007/s10278-026-01843-0

Odontology. 2026 Jan 30. doi: 10.1007/s10266-026-01328-0. Online ahead of print.

ABSTRACT

This in vitro study aimed to evaluate the effects of office and home bleaching agents containing nano-hydroxyapatite (n-HAP) on the surface roughness, microhardness, and micromorphology of sound and demineralized enamel. A total of 120 enamel specimens were obtained from extracted human third molars, half of which underwent a demineralization cycle to simulate initial enamel demineralization. The specimens were divided into five subgroups (n = 12) based on the bleaching agent applied: no bleaching (control), 40% hydrogen peroxide (HP), 16% carbamide peroxide (CP), 40% HP + n-HAP, and 6% HP + n-HAP. Surface roughness was measured using non-contact optical profilometry, and microhardness was assessed via the Vickers hardness test. Micromorphological changes were examined by scanning electron microscopy (SEM) at × 1,000 and × 4,000 magnifications. Statistical analyses were performed using the Shapiro-Wilk, Mann-Whitney U, Kruskal-Wallis H, and Bonferroni post hoc tests (p < 0.05). In the demineralized groups, surface roughness significantly increased while microhardness decreased (p < 0.05). The highest surface roughness was observed in the demineralized group treated with 16% CP, whereas microhardness significantly increased in the group treated with 6% HP + n-HAP. SEM findings revealed pronounced structural degradation in groups treated with high-concentration HP, while n-HAP-containing groups exhibited mineral deposition and preservation of the prismatic enamel structure. Although no remineralization protocol was used before bleaching, the findings indicate that low-concentration HP agents containing n-HAP may protect enamel with initial demineralization. These results highlight the potential clinical benefit of such formulations in reducing bleaching-related enamel damage.

PMID:41615631 | DOI:10.1007/s10266-026-01328-0

Acta Neurol Belg. 2026 Jan 30. doi: 10.1007/s13760-025-02984-9. Online ahead of print.

ABSTRACT

BACKGROUND: Relapsing-remitting multiple sclerosis (RRMS) often necessitates treatment changes due to safety concerns, inadequate efficacy, or patient-specific factors. While second-line therapies (e.g., natalizumab, ocrelizumab) are effective, real-world evidence on outcomes after switching or discontinuing these therapies are limited, particularly in diverse healthcare settings.

OBJECTIVE: This study aimed to evaluate treatment transition patterns, reasons for discontinuation, and six-month clinical/MRI outcomes in patients with RRMS switching between second-line therapies or discontinuing treatment.

METHODS: A retrospective cohort study was conducted at Sina Hospital, Tehran, Iran, including 338 RRMS patients who switched or discontinued second-line therapies including fingolimod, natalizumab, ocrelizumab and rituximab. Clinical and MRI data were collected at baseline (therapy change/discontinuation) and six-month follow-up. Outcomes included relapse frequency, disability progression (Expanded Disability Status Scale [EDSS]), and MRI lesion activity. Statistical analysis was done using paired t-tests and descriptive statistics.

RESULTS: Among 338 patients (83.1% female, mean age 33.9 years), treatment transitions occurred most frequently to ocrelizumab (42.3%) or rituximab (33.4%). Safety concerns (32.0%), inadequate efficacy (29.9%), tolerability issues (13.6%), and pregnancy planning (8.9%) were primary reasons for therapy changes. Overall paired analyses of EDSS scores showed a strong correlation between pre- and post-switch measurements (r = 0.944, p < 0.001), although the average change for the entire cohort was minimal and not statistically significant. Notably, the subgroup of patients who switched from fingolimod to ocrelizumab demonstrated a statistically significant reduction in EDSS scores, with a mean difference of 0.19 (p = 0.019). Furthermore, among 110 patients whose treatment change was driven solely by inadequate efficacy (e.g., ongoing relapses or poor symptom control), the mean EDSS improved significantly from 2.41 (± 1.74) at baseline to 2.16 (± 1.80) at six months, with a mean difference of 0.25 (p < 0.001) and a strong correlation between baseline and follow-up scores (r = 0.92, p < 0.001).

CONCLUSION: B-cell-depleting therapies, particularly ocrelizumab, may help lower disability in active RRMS, but longer follow-up is needed to confirm sustained benefits. Personalized strategies that balance efficacy, safety, and patient-specific factors (e.g., PML risk, pregnancy) are essential. Although most patients had low baseline disability, which may limit generalizability, these findings still offer real-world insight into treatment transitions. Longer prospective studies are needed to confirm long-term outcomes.

PMID:41615580 | DOI:10.1007/s13760-025-02984-9

Cardiovasc Drugs Ther. 2026 Jan 30. doi: 10.1007/s10557-026-07846-x. Online ahead of print.

NO ABSTRACT

PMID:41615573 | DOI:10.1007/s10557-026-07846-x

Discov Oncol. 2026 Jan 30. doi: 10.1007/s12672-026-04506-2. Online ahead of print.

ABSTRACT

BACKGROUND: The detection rate of early-stage gastric cancer remains relatively low. Early detection is beneficial for improving prognosis. We aim to explore the risk factors for lymph node metastasis(LNM) in elderly patients with early gastric cancer (EGC), and to construct a nomogram prediction model for validation.

METHODS: 136 patients diagnosed with elderly EGC accompanied by LNM in Cangzhou Central Hospital and Cangzhou People’s Hospital from January 2021 to June 2024 were selected as the training cohort. The new gastric cancer screening score (GCSS), regenerated-protein 4(REG4), tumor abnormal protein(TAP) levels and clinicopathologic characteristics were compared in elderly EGC, gastric precancerous disease and control groups. Lasso-Logistic regression was used to identify risk factors affecting LNM, and the nomogram model was established and verified. The clinical decision curve analysis (DCA) and clinical impact curve (CIC) were performed to evaluate the model. In addition, the clinical data of 72 patients with elderly EGC who met the inclusion criteria in two hospitals from July 2024 to June 2025 were selected as the validation cohort to verify the nomogram model.

RESULTS: There was no statistically significant difference in general clinical data between the training cohort and the validation cohort (P > 0.05). The incidence of LNM in the training cohort was 22.79% (31/136), while that in the validation cohort was 23.61% (17/72). GCSS, REG4, and TAP levels in EGC group were higher than gastric precancerous disease group and control group. Lasso-Logistic regression showed that REG4, TAP, vascular invasion, undifferentiated type, infiltrate into the submucosa, and diameter ≥ 2 cm were independent risk factors for LNM in elderly EGC. The Nomogram model was constructed based on the independent risk factors screened out, which showed that the predicted values were in good agreement with the measured values, The area under the receiver operating characteristic curve (ROC) (AUC) of the training cohort and the validation cohort was 0.853 and 0.878, respectively. The goodness-of-fit test was conducted using the Hosmer-Lemeshow method, and the result was P = 0.751. The DCA and CIC of the training and validation cohort both indicate that the model had good clinical application value.

CONCLUSION: The results of this study indicate that REG4, TAP, vascular invasion, undifferentiated type, infiltrate into the submucosa and diameter ≥ 2 cm are at a higher risk for LNM in elderly EGC. A nomogram model can be helpful for early prediction of LNM in elderly EGC, It provides certain references for the treatment strategies of elderly EGC.

PMID:41615557 | DOI:10.1007/s12672-026-04506-2

Environ Monit Assess. 2026 Jan 30;198(2):188. doi: 10.1007/s10661-026-14996-w.

ABSTRACT

Vegetation phenology needs to be considered in the assessment of agricultural drought severity, especially in drylands such as Botswana. Using Remote Sensing time-series data (2000 – 2020), this study evaluated vegetation productivity using the annual sum of the Enhanced Vegetation Index (EVI_sum) and computed changes as trends (EVIsum_trend) in agricultural lands comprising grasslands and croplands. To assess agricultural drought severity, a weighted linear combination was applied to the EVI-based Vegetation Condition Index (VCI_wlc) and compared to the conventional Standardized Precipitation Index. To detect how agricultural drought has impacted vegetation phenology, we identified dynamics in vegetation greenup, maturity, peak, senescence and dormancy and correlated these to the EVI_sum and VCI_wlc. Differentiating between croplands and grasslands, vegetation productivity in grasslands was consistently lower than in croplands during droughts. The seasonal agriculture-related phenology, such as late vegetation greenup – the start of the season – is correlated with reduced vegetation productivity and severe agricultural droughts as evidenced by lower EVI_sum and VCI_wlc values, respectively. Notable phenology patterns include delayed greenup in grasslands compared to croplands, while the peak period often overlaps between grasslands and croplands. Overall, phenological shifts detected over agricultural lands in Botswana were about 58 days delayed greenup between the earliest and latest detection, whereas for peak, senescence and dormancy, delays were between 60 and 61 days. Findings provide valuable insights into how vegetation responds over time to changing environmental stressors such as drought. Understanding and monitoring how drought impacts agriculture-related phenology in dryland ecosystems is essential to informing national drought policies.

PMID:41615550 | DOI:10.1007/s10661-026-14996-w