Citations

Objective: Lateral condyle fractures are the second most common pediatric elbow fracture after supracondylar humeral fractures. Early complications are frequent which can lead to development of long-term problems. Current literature has evaluated short-term outcomes, but few studies have investigated long-term outcomes into adulthood. Our hypothesis is that the majority of pediatric patients with a lateral condyle fracture will have minimal complications and few surgeries as they age. Methods: A population-based database was used to identify patients who sustained a lateral condyle fracture before the age of 18 between 1966 and 2012. Electronic medical records from all treatment centers in the county were reviewed for clinical and radiographic data. Analysis was performed to determine incidence and long term outcomes based on fracture type and treatment. Results: From 1966 to 2012, 227 pediatric lateral condyle fractures were identified. One hundred seventy-seven fractures (78%) had at least 10 year clinical follow up. Incidence was found to be 13.97 per 100,000. We identified 80 (45%) Weiss type 1, 61 (34%) type 2, and 37 (21%) type 3 fractures. The overall complication rate was 17%, of which 47% were identified >10 years from injury. There was no significant difference in complication rates based on fracture type (P = 0.18) or treatment type (P = 0.55). The most common complication was malunion (n = 15), followed by fishtail deformity (n = 4), stiffness (n = 3), lateral epicondylitis (n = 3), nonunion (n = 2), osteoarthritis (n = 2), and tardy ulnar nerve palsy (n = 1). Five patients underwent revision surgery for nonunion, cubitus valgus, malunion with loose bodies, capitellar osteochondral dessicans with malalignment, and ulnar nerve palsy. Conclusions: This population-based study estimated the overall incidence of pediatric lateral condyle fractures to be 14 per 100,000. Displaced fractures had a higher incidence than undisplaced fractures. Complications beyond 10 years are rare, but the need for future revision surgery is possible, therefore, proper patient and family education is necessary at the time of injury. This is the largest study with the longest follow-up for pediatric lateral condyle fractures. Complications were rare but resulted in a 17% complication rate and a 3% reoperation rate at a minimum. Level of Evidence: Level III.

Abstract Background In BRAF-mutated high-risk melanoma, targeted therapy (BRAF/MEK inhibitors) and checkpoint inhibitor (CPI) immunotherapy have durable benefits as first-line (1L) adjuvant therapy. Based on differing action mechanisms of BRAF/MEK inhibitors and CPI immunotherapies, there is interest in evaluating the activity of 2L adjuvant targeted therapy in decreasing the risk of subsequent recurrence after repeat resection following relapse on/after 1L adjuvant CPI. Patients and methods This was a retrospective review of BRAF V600-mutated resected stage III/IV melanoma patients in the United States, Australia, and The Netherlands who received 1L adjuvant CPI immunotherapy, relapsed locoregionally/distantly, were again resected to no evidence of disease, and received dabrafenib/trametinib (dab/tram) as 2L adjuvant therapy. The primary endpoint was relapse-free survival (RFS) from initiation of 2L adjuvant dab/tram (RFS-2), analyzed via Kaplan-Meier methods. Results Thirty-eight patients were included (median age 50 years, 63% male, 87% stage III, median follow-up 19 months from 2L dab/tram initiation). Median dab/tram duration was 10.1 months (range: 1 day–22.7 months), with half discontinuing due to progression or adverse events. Median (95% CI) RFS-2 was 18.9 (14.9–28.1) months, with 91%, 81%, and 58% remaining relapse-free at 6, 12, and 18 months, respectively. Most patients remained distant metastasis-free at 6, 12, and 18 months (97%, 85%, and 71%, respectively). Two patients were deceased at the last follow-up, with 97% alive at 18 months. Conclusions Over 80% of patients remained relapse- and metastasis-free at 12 months after 2L dab/tram initiation, with only 2 deaths observed. Dab/tram appears to have activity in the 2L adjuvant setting, although more follow-up is required.

Background White matter hyperintensities (WMH) and their progression are associated with risk of dementia and stroke, so are an important target for clinical trials. The cost of broad magnetic resonance imaging (MRI) screening to identify eligible individuals, however, limits the feasibility of designing clinical trials targeting WMH. A low‐cost retinal or clinical screening measure before MRI could reduce recruitment costs versus an MRI‐only screening design in a hypothetical clinical trial. Methods and Results Data from the Atherosclerosis Risk in Communities study with valid retinal and WMH measurements ( N =1311) were used. To identify a population at greater likelihood of significant WMH on MRI and thus reduce the number of screening MRIs required, we evaluated 3 theoretical prescreening measures: (1) retinal, (2) clinical, (3) combined clinical‐retinal. Given a target sample for clinical trials ( N =646), we calculated screening sample sizes based on the proportion within the population having an elevated score for each prescreening measure (separately) multiplied by the proportion of significant WMH among those with that prescreening feature. Recruitment costs were calculated using estimated retinal and MRI cost estimates. Compared with the estimated cost of MRI‐only screening (>$4.24 million, requiring MRI on 6526 participants), prescreening for a high clinical score resulted in total cost of $2.47 million, with an initial screening group of 52 778 participants, with MRI in 3801. A high clinical‐retinal score cutoff resulted in costs of $2.9 million while requiring 13 572 participants, with 3801 completing MRI. Conclusions A 2‐stage design with low‐cost prescreening measures is a promising approach, resulting in reduced theoretical recruitment costs compared with an MRI‐only design.

Introduction: Metabolic pharmacotherapies [Glucagon-like peptide-1 receptor agonists (GLP1RA) and sodium-glucose cotransporter type 2 inhibitors (SGLT2i)] have shown benefit in patients with heart failure and preserved ejection fraction (HFpEF). It remains unclear whether the two classes would have additive effects. Methods: We performed a retrospective study using a de-identified federated database with 89 contributing health care organizations (HCO), including over 126 million patients (TriNetX Research Network, Cambridge, MA; date of data access: May 23, 2024). TriNetX regularly aggregates clinical data directly from participating HCOs, and performs extensive data quality and accuracy assessment. While TriNetX obfuscates institutional information relating to participating HCOs, a typical HCO includes a large academic health center with inpatient, outpatient, and specialty care services. We identified all patients with a diagnosis of Heart failure with preserved ejection fraction (HFpEF, ICD-10: I50.3), and SGLT2i usage. We then categorized this patient population into two cohorts, including patients with concomitant GLP1RA use, and patients without GLP1RA use. For both cohorts, we collected data on patient demographics, and the outcomes of all-cause mortality, and all-cause hospitalization, occurring up to 10-years after the index diagnosis. We evaluated differences in outcome risk using hazards ratios and 95% confidence intervals. Results: Prior to propensity score matching, we identified 114,329 patients, with 7931 patients receiving SGLT2i +GLP1RA vs 106398 receiving SGLT2i-alone. Majority (55.7%) identified as white and 24.4% as African Americans and >90% of the patients had a diagnosis of type 2 diabetes mellitus. After propensity matching, the rate of all-cause hospitalization within the combination group was lower than SGLT2i group (29.6% vs 32.4%, HR 0.76 [0.73- 0.79], P<0.001). All-cause mortality for the combination group was 6.8% versus 10.6% within the SGLT2i-alone group (HR 0.52 [0.47-0.56], P<0.001)). Conclusion: In this propensity-matched cohort, patients with HFpEF receiving GLP1RA and SGLT2i had lower rates of hospitalizations and all-cause mortality compared with those receiving SGLT2i alone. Large randomized controlled trials are warranted to corroborate these findings.

Background Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in adults using a 12‐lead ECG; however, its efficacy in children is uncertain. We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. Methods and Results We identified 10 142 unique pediatric patients (age≤18) with a 10‐second, 12‐lead surface ECG within 14 days of a transthoracic echocardiogram, performed between 2002 and 2022. LVSD was defined quantitatively by left ventricular ejection fraction (LVEF). RVSD was defined semiquantitatively. Novel pediatric models for LVEF ≤35% and LVEF <50% achieved excellent test areas under the curve of 0.93 (95% CI, 0.89–0.98) and 0.88 (95% CI, 0.83–0.94) respectively. The model to detect LVEF <50% had a sensitivity of 0.85, specificity of 0.80, positive predictive value of 0.095, and negative predictive value of 0.995. In comparison, the previously validated adult data‐derived model for LVEF <35% achieved an area under the curve of 0.87 (95% CI, 0.84–0.90) for LVEF ≤35% in children. A novel pediatric model for any RVSD detection reached a test area under the curve of 0.90 (0.87–0.94). Conclusions An artificial intelligence–enabled ECG demonstrates accurate detection of both LVSD and RVSD in pediatric patients. While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.

Abstract Objectives To define the prevalence, distribution and characteristics of patients with VEXAS (vacuoles, E1-enzyme, X-linked, autoinflammation, somatic) syndrome who have confirmed vasculitis. Methods Patients with VEXAS syndrome, verified by positive UBA1 mutation, were included. Chart review was performed to identify patient characteristics and outcomes. Vasculitis diagnosis was based on either histopathology showing vascular inflammation or non-invasive angiography findings. Summary statistics were calculated. Results Eighty-nine patients met inclusion criteria. All were male with a median age of onset of 66.9 years (interquartile range 60.1, 72.7). Median (interquartile range) follow-up was 3.8 (2.2–5.5) years, during which 21 patients (23.6%) had evidence of vasculitis. Vasculitis subtypes included small vessel vasculitis (19.1%), cutaneous medium vessel vasculitis (2.2%) and large vessel vasculitis (2.2%). No patient had more than one vessel size involved. Histopathology in small vessel vasculitis patients was consistent with cutaneous leukocytoclastic vasculitis in the majority, though one patient had leukocytoclastic peritubular capillaritis on renal biopsy. Cranial symptoms (headache, vision changes or jaw pain) were noted in 18.0%. Two additional patients not experiencing cranial symptoms exhibited large vessel involvement with confirmed carotid thickening on non-invasive angiography; one of these had a positive temporal artery biopsy. Conclusion VEXAS syndrome manifests as a variable vessel vasculitis in a quarter of patients, with cutaneous small and medium vessel involvement being particularly common. Some patients may have positive ANCA serologies or even renal vasculitis leading to misdiagnosis. Cranial symptoms are common and may mimic GCA, though documented large vessel inflammation is rare.

Abstract The OmicsFootPrint framework addresses the need for advanced multi-omics data analysis methodologies by transforming data into intuitive two-dimensional circular images and facilitating the interpretation of complex diseases. Utilizing deep neural networks and incorporating the SHapley Additive exPlanations algorithm, the framework enhances model interpretability. Tested with The Cancer Genome Atlas data, OmicsFootPrint effectively classified lung and breast cancer subtypes, achieving high area under the curve (AUC) scores—0.98 ± 0.02 for lung cancer subtype differentiation and 0.83 ± 0.07 for breast cancer PAM50 subtypes, and successfully distinguished between invasive lobular and ductal carcinomas in breast cancer, showcasing its robustness. It also demonstrated notable performance in predicting drug responses in cancer cell lines, with a median AUC of 0.74, surpassing nine existing methods. Furthermore, its effectiveness persists even with reduced training sample sizes. OmicsFootPrint marks an enhancement in multi-omics research, offering a novel, efficient and interpretable approach that contributes to a deeper understanding of disease mechanisms.