Citations

Introduction: Procedural competence is essential to clinical practice, yet assessment of technical skills such as suturing remains highly variable and often relies on subjective evaluations. While tools with limited validity evidence exist in surgical specialties, their use in family medicine is limited. This study evaluated the interrater reliability of a suture assessment tool developed by Sundhagen et al when used by family medicine faculty to evaluate the simple interrupted suturing skills of family medicine residents. Methods: In this cross-sectional reliability study, 15 core faculty members from four family medicine residency programs were recruited to evaluate the simple interrupted suturing skills of 20 family medicine residents using a modified suture assessment tool developed by Sundhagen et al. Intraclass correlation coefficients were used to evaluate interrater reliability. Light’s κ was calculated for each question. Results: A total of 15 evaluators assessed 20 videos of resident suturing performance. The Light’s κ estimates ranged from 0.11 to 0.50, indicating slight to moderate agreement. None of the items reached the threshold for substantial agreement (κ≥0.61). Conclusions: The modified Sundhagen suture assessment tool demonstrated fair to moderate reliability when used to evaluate family medicine residents. While the level of agreement limits the tool’s effectiveness for standardized summative assessment, the tool may still offer value as a structured framework for formative feedback. Future studies may improve reliability through refined rater training, behaviorally anchored scoring criteria, and the use of visual exemplars.

Ramdas et al. propose renaming ‘congenital myasthenic syndrome’ as ‘genetic myasthenic syndrome’. They argue that ‘congenital’ misleadingly implies neonatal onset, which may contribute to delayed diagnosis and management, and that revised nomenclature could improve patient outcomes.

Introduction: AI-driven software has been recommended as a means of triaging suspected large vessel occlusions (LVOs) on CT angiography (CTA), and different solutions are now commercially available. This study compared the performance of two software packages, Brainomix 360 Triage LVO and Rapid LVO, in prospective, real-world use. Methods: Consecutive patients scanned for suspected stroke at 3 comprehensive stroke centres from May to July 2024 (3 months) were included in the study. CTA, where available, was processed in real time by both Rapid and Brainomix software. Ground truth on vessel occlusion was ascertained using clinical review of electronic medical records. Occlusion location was coded as intracranial internal carotid artery terminus (ICA-T), middle cerebral artery (MCA) M1 or MCA M2. If more than one occlusion was observed, the most proximal of these was taken as the primary vessel affected. Results: There were 561 suspected stroke patients scanned during the study period across the three sites. Of these, CTA was sent for processing by both Rapid LVO and Brainomix 360 Triage LVO for 359 cases. Cases were excluded if no contrast was detected (n=17), leaving 342 cases (Table 1). Of these, proximal LVO (ICA-T or MCA M1) was confirmed in 14 cases and MCA M2 occlusions were present in 6 cases. Table 2 shows the LVO detection results for all cases from the two software packages. For both devices, sensitivity was higher when considering only proximal occlusions (ICA-T or M1). Performance was similar overall, but there was a trend towards differing sensitivity for more distal occlusions. As a composite measure, area under the curve (AUC) was higher for Brainomix than Rapid (Figure 1) but this difference was not significant. The positive predictive value (PPV) was low for both software packages due to the low incidence of LVO in the patient population. Conclusions: This study demonstrated consistent performance of two AI software devices, Brainomix 360 Triage LVO and Rapid LVO, for detection of LVO on CTA imaging, in prospective, real-world use. The low number of positive cases in the dataset (N=21) is a limitation of the study. There was a trend towards different performance for more distal vessel occlusion locations. Overall, the sensitivity observed in this dataset was in line with reports from previous retrospective studies for both software packages and underlines the importance of prospective evaluation to understand real-world performance.

Abstract Early-onset Alzheimer’s disease (EOAD) and Late-onset AD (LOAD) differ in clinical presentations and rates of progression. We aimed to compare baseline and longitudinal tau PET burden, and their relationship with clinical variables in amyloid-PET positive, cognitively impaired participants from the Longitudinal Early-Onset Alzheimer’s Disease Study (EOAD; n=390) and Alzheimer’s Disease Neuroimaging Initiative (LOAD; n=211). Patients with EOAD showed higher baseline tau PET retention, broader neuroanatomical involvement and faster accumulation rates over time compared to LOAD, after adjusting for amyloid load and clinical stage. Tau PET showed stronger correlations with baseline amyloid burden and clinical measures of global cognition and function in EOAD than LOAD. We conclude that earlier age of onset in AD is linked to a more aggressive tauopathy, which in turn is a primary driver of clinical decline. These findings suggest that optimal therapeutic targets and strategies may differ between EOAD and LOAD. One Sentence Summary Younger patients with Alzheimer’s disease show more aggressive tau spread, suggesting age of onset defines distinct disease pathways with key clinical implications.

OBJECTIVE The aim of this study was to determine predictors of the minimum clinically important difference (MCID) in the Neck Disability Index (NDI) following cervical spinal deformity surgery. METHODS A retrospective review was performed of a prospective, multicenter adult cervical spinal deformity database. All patients had baseline and 1-year NDI scores. Patients met MCID with an improvement of NDI by 7 points between baseline and 1 year, as previously established. Baseline demographics, comorbidities, and both baseline and 1-year spinopelvic parameters were evaluated for statistical significance in a univariate logistic regression analysis. Significant variables, in addition to baseline NDI, were analyzed in a multivariable logistic regression model by backward selection with Akaike information criterion minimization. RESULTS A total of 122 patients were included with a median age of 62 (IQR 56, 69) years; 62% of patients were female. Of the 122 patients, 72 (59%) achieved NDI MCID at 1 year. Predictors of achieving MCID on univariate analysis included a lower Charlson Comorbidity Index (CCI) total score (OR 0.70, p = 0.03), depression as a comorbidity (OR 2.9, p = 0.02), lower C2 tilt at the 1-year follow-up (OR 0.92, p = 0.02), and a greater difference between 1-year postoperative C2–7 sagittal vertical axis (SVA) and preoperative C2–7 SVA (OR 0.98, p = 0.0495). On multivariable logistic regression analysis, predictors of achieving MCID included a lower CCI (OR 0.62, p = 0.03), depression as a comorbidity (OR 3.1, p = 0.059), a greater change in C2–7 SVA at the 1-year follow-up compared with baseline (OR 0.97, p = 0.055), and baseline NDI (OR 1.02, p = 0.24) with an area under the curve of 0.74. CONCLUSIONS The best-fit multivariable model included higher baseline NDI, a greater change in C2–7 SVA, patient-reported baseline depression, and lower CCI as important factors in predicting NDI MCID.

Abstract Background We aimed to describe the real-world durability of clinical and endoscopic outcomes of upadacitinib (UPA) in ulcerative colitis (UC). Methods We retrospectively analyzed an ongoing multi-center cohort of UC patients(pts) in the United States who were started on UPA for active disease. Primary outcome was clinical remission at 1yr assessed by partial Mayo score(pMS)(resolution of all UC related symptoms and physician global assessment). Secondary outcomes assessed at various timepoints, including after re-escalation, included clinical response(>50%reduction in symptoms utilizing the pMS), endoscopic response (Mayo endoscopic score≤1or absence of erosions/ulcerations) and histological remission(defined as normal or chronic inactive). Durable secondary outcomes achieved at both 6months and at 1yr and beyond were also assessed. Descriptive statistics were performed. Adverse events(AEs) investigated included cardiovascular events and herpes zoster (HZ). Results 416pts were included(Table 1) with median values for age at initiation of36.00yrs(range27-48), disease duration7.00yrs(range3-14)and follow-up 993days(IQR,672-1103), with206(49.52%)with follow-up at 1yr or beyond. Of these, 66.1%had extensive colitis. Induction duration was8wks in 86.5%and16wks in 4.8 %(20/416). Most received an induction dose of45mg(97.1%)and maintenance dose of30mg(85.8%). Among the evaluable population at1yr and beyond, 62.5%(45/80)were in clinical remission, 75.9%(22/29)in endoscopic response with58.6%(17/29) in remission and66.6%(20/30)in histological remission. At 6months, clinical remission was51.6%(42/93), endoscopic response was 75%(24/32) of which43.75%(14/32)were in remission and histologic remission was seen in 40.8%(20/49).Durable secondary outcomes of clinical remission were seen in 71.4%(30/42), endoscopic improvement in 45.8%(11/24), and histologic remission in35%(7/20). Re-escalation to 45mg occurred in 35pts, of which48.6%(17/35)were re-escalated due to incomplete induction clinical response with all achieving response(11 in remission). The rest(18/35)were re-escalated for clinical relapse after initial remission where72.2%(13/18)were able to recapture remission. After re-escalation,54.3%(19/35)continued on 45mg daily. AEs were reported in12.7%with HZ in 7pts(2.1%). One pt aged53yrs had an episode of TIA after 1yr on UPA at 15mg, without pre-existing cardiovascular risk factors and UPA use is ongoing at the same dose. There were no reported episodes of worsening of pre-existing cardiovascular disease or DVT/PE. Conclusion UPA is durably effective and safe in a real-world clinical setting with re-escalation to 45mg capturing response in a majority of the pts. Ongoing recruitment will provide further evidence on long term effectiveness and safety. Conflict of interest: Ms. Huang, Katherine: No conflict of interest Chandnani, Arun: No conflict of interest Samaan, Sami: None Tan, Tingyi: I have no conflict of interests to declare. Ramesh, Prajith Raj: None Conlon, Caroline: No conflict of interest Klein, Jeremy: None Reddy, Nikhil: No conflict of interest Ayoub, Malek: None Cervantes Limon, Gabriela: none Myers, Melissa: None Bucaram, Martha: No conflict of interest Lieto, Stephen: No conflict of interest Scalzo, Nicholas: No conflict of interest Cohen, Benjamin: Abbvie - consulting and speaking ALPCO - consulting J & J Innovative Medicine - consulting Takeda - consulting and speaking Emmes Biopharma Services LLC - DSMB Pfizer - consulting Mohamed, Islam: nothing to declare Ciorba, Matthew: Advisory Board: Janssen, AbbVie, Pfizer, Geneoscopy Consulting: Janssen, AbbVie, Pfizer, Geneoscopy Grant contracts: Janssen, Pfizer, Incyte Shukla, Richa: Speakers bureau - Abbvie and Lilly Wright, Michael: None Xu, An Tao: No conflict of interest Chowla, Navreet: No conflict of interest Ogholikhan, Sina: Abbvie Medical Director Kujawski, Michelle: Abbvie Scientific Director Dulaney, David: Speaker bureau - Regeneron Speaker bureau - Sanofi Speaker bureau - Takeda Speaker bureau - Eli Lilly Fenster, Marc: none Benson, Caroline: No conflict of interest Alhobayb, Tamara: No conflict of interest Berinstein, Jeffrey: No conflict of interest Shivashankar, Raina: Abbvie and BMS - speaker bureau Janssen and Celltrion - grant for IBD fellowship funding Pfizer - consultant Bishu, Shrinivas: None Patel, Anish: speaker: abbvie, J & J, Lilly, BMS, Pfizer, Phathom, Takeda consultant: abbvie Ungaro, Ryan: Personal Fees: AbbVie, Bristol Myers Squibb, Genentech, Lilly, Pfizer, Janssen, Takeda Johnson, Amanda: Research grant: Abbvie, Spyre Therapeutics Pekow, Joel R.: CVS Health - Consulting Abbvie, Eli Lilly, Pfizer, Johnson and Johnson - Stocks Yarur, Andres: Personal Fees: Consultant for Takeda, Pfizer, Roche, Merck, Abbvie, Eli Lilly. Bristol Myers Squibb, Celltrion, Johnson and Johnson. Deepak, Parakkal: Parakkal Deepak has received research support under a sponsored research agreement unrelated to the data in the abstract from AbbVie, Johnson and Johnson, Sanofi, Merck, Teva, Direct Biologics, Tr1x, Boehringer Ingelheim, Bristol Myers Squibb, Pfizer, Prometheus Biosciences, Takeda Pharmaceuticals, Roche Genentech, Eli Lilly, AstraZeneca, Spyre and Agomab, has received consulting fees from Johnson and Johnson, Abbvie, Merck, Sobi, Celltrion, Fresenius Kabi, Asahi Kasei Pharma, Sandoz and CorEvitas, LLC and has served on the board of the Srategic Alliance for Intercultural Advocacy in GI.

Abstract Objective To develop a comprehensive risk stratification model to identify patients at high risk of cesarean surgical site infection (cSSI) based on information available at the time of hospital discharge. Methods This is a retrospective cohort study based on datasets from two independent level IV academic medical centers to improve generalizability. The first study includes 2336 cesarean deliveries for analysis with 109 instances of cSSI (4.7%). The second study includes 2936 cesarean deliveries with 72 instances of cSSI (2.5%). The first study cohort was utilized for both model training and internal validation, using the 15 shared features present in both datasets. Random search with cross‐validation was used to choose the type of machine learning (ML) model and its hyperparameters, with area under the receiver operating characteristic curve (AUC) as the validation metric. The second study cohort was then used to evaluate testing accuracy (external validation) and generalization capability of this model. The predictive importance of each feature was evaluated using permutation importance applied to the second cohort. Risk stratification cutoff scores were defined based on centiles over the first patient cohort and evaluated on the second cohort. Results The ML model with the highest validation AUC was an XGBoost classifier. This trained model achieved an AUC of 0.78 on the training data and a 0.72 cross‐validated AUC. When tested on data from the second study cohort, it achieved an AUC of 0.69. The features showing the strongest predictive generalization, as measured by permutation importance, were length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Using the second cohort to test our model, the model shows a 22.7% positive predictive value (PPV) of cSSI among women in the highest risk group, and a 0.8% PPV among women in the bottom risk group, compared with 2.5% cSSI incidence for the study population at large. Conclusion We developed and validated a predictive ML model for cSSI with information available to healthcare professionals at the time of hospital discharge. This model suggests that the most predictive risk factors for cSSI include length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Additionally, the model provides reasonable risk stratifications for individual patients. This tool may be used for identifying subgroups at higher risk of cSSI and identifying those who may require closer surveillance or clinical intervention.