Citations

Background: Adequate cam resection during hip arthroscopy for femoroacetabular impingement syndrome (FAIS) is necessary to restore femoral head-neck offset while avoiding under- or over-resection. The relationship between the extent of femoroplasty and postoperative patient-reported outcomes remains unclear. Purpose: We sought to answer the following questions: What is the association between the extent of cam femoroplasty resection and postoperative improvements? and is a 5% resection threshold associated with improved outcomes? Methods: We conducted a retrospective review of patients with adequate acetabular coverage who underwent primary hip arthroscopy with femoroplasty between January 2015 and December 2022 at our institution and had preoperative and 1- and/or 2-year postoperative modified Harris hip score (mHHS) and/or International Hip Outcome Tool (iHOT) scores. We included 400 patients (409 hips; ages 14–50 years). Outcomes included score changes and achievement of minimum clinically important difference (MCID) and substantial clinical benefit (SCB). Postoperative Dunn lateral radiographs quantified femoroplasty by resection depth percentage (resection depth/femoral head diameter), proximal resection angle, and postoperative α angle. Hips were classified as under-resection, neutral (0%–5%), or over-resection (>5%), and differences in outcomes were compared between resection groups. Multivariable regression analyses controlled for demographic, radiographic, and surgical variables. Results: Mean resection depth was 4.8%; mean proximal resection angle was 72.6°. No differences were observed in score improvements or MCID/SCB rates between groups with under-resection versus over-resection at 1 or 2 years. Greater resection depth was associated with larger 1-year mHHS and iHOT improvements and independently predicted 1-year iHOT MCID and SCB. Higher proximal resection angle predicted 2-year iHOT MCID. Conclusion: In this retrospective, single-institution cohort study, we found that in patients with FAIS, greater femoroplasty depth was associated with improved 1-year clinical outcomes. Level of Evidence: Level III, retrospective cohort study.

Squamous cell lung cancer (SqCLC) accounts for 20–30% of non-small cell lung cancer (NSCLC) and remains associated with a poorer prognosis compared with adenocarcinoma. Despite advances in treatment, 5-year overall survival for advanced (stage IV) disease remains below 10–15%. Unlike non-squamous NSCLC, SqCLC is characterized by a high tumor mutational burden and complex genomic landscape dominated by alterations in tumor suppressor genes and lineage survival pathways including TP53, CDKN2A, PIK3CA, FGFR1, SOX2, and the NFE2L2/KEAP1 oxidative stress pathway, as well as dysregulation of the NOTCH signaling pathway, but it harbors relatively few actionable oncogenic drivers, resulting in limited treatments for targeted therapy. HER2 alterations can occur by multiple mechanisms, including activating mutations, gene amplifications, and protein overexpression. They comprise a very small percentage of NSCLC, with HER2 mutations reported in approximately 1–3% and HER2 amplifications observed roughly in 2–4%. While HER2 alterations are well characterized in lung adenocarcinoma, the prevalence, genomic context, and clinical significance of HER2 alterations in SqCLC remain incompletely defined. Advances in next-generation sequencing have led to improved ability to detect HER2 alterations and facilitated the development of HER2 targeted therapies. Available treatments for advanced/metastatic SqCLC have been historically limited to platinum-doublet chemotherapy, with immune checkpoint inhibitors such as anti-PD-1/PD-L1 newly emerging in the past decade. Selective HER2 tyrosine kinase inhibitors and HER2 antibody/drug conjugates have shown improved efficacy in HER2-altered NSCLC as shown in DESTINY-LUNG02 and BEAMION LUNG-1 trials; however, most of the enrolled patients had non-squamous histology, with minimal or no SqCLC-specific efficacy data reported. Future progress in HER2-altered SqCLC will require inclusion of SqCLC in HER2 basket trials, incorporation of comprehensive molecular profiling and standardized HER2 testing in squamous histology. This review summarizes the current state of knowledge of HER2 biology in SqCLC and highlights areas for future directions for precision oncology in SqCLC.

The Omicron variant of SARS-CoV-2 is associated with milder symptoms and lower hospitalization and mortality rates than Delta variants, although the impact of Omicron on immunocompromised patients, especially solid organ transplant (SOT) recipients, is still unclear. This study compares the hospitalization rate and outcomes between immunocompromised, immunocompetent, and SOT patients during the Delta and Omicron periods. We included adult patients who tested positive for SARS-CoV-2 on PCR or nasopharyngeal antigen test between 26 June 2021 to 8 September 2022, at our institution. A total of 12,401 COVID-19 patients were included, of which 11,055 were immunocompetent, and 1346 were immunocompromised (375 SOT recipients). Throughout the Delta and Omicron outbreaks, immunocompromised patients exhibited higher comorbidities and 30-day hospitalizations, but rates of mechanical ventilation and ICU-level care were like immunocompetent patients. During the Omicron wave, immunocompromised patients had higher unadjusted relative risk estimates (RR = 2.37, 95% CI 1.96–2.87, p < 0.05) than Delta (RR = 1.58, 95% CI 1.24–2.01, p < 0.05), with higher adjusted relative risk for hospitalization in Omicron (RR = 1.50, 95% CI 1.10–2.03, p = 0.01). Analyses show increased hospitalization risk in immunocompromised during the Omicron wave compared to the Delta wave, with no significant difference in hospitalization outcomes. The relative risk of hospitalization for SOT patients was higher in both waves.

Vertebral fractures are among the most common skeletal injuries and present significant clinical and biomechanical challenges, particularly in older adults and individuals with low bone density. Accurate prediction of vertebral mechanical response and failure under varying loading conditions is essential for improving understanding of spinal injury mechanisms. This study develops a density-dependent viscoelastic analytical model to predict the stiffness and fracture force of human vertebral specimens subjected to different compression rates. The vertebral body is represented as a composite structure consisting of a cortical shell and a trabecular core. Cortical bone is modeled as a linear elastic material, whereas trabecular bone is described using a Kelvin–Voigt viscoelastic formulation. Density-dependent constitutive relationships are incorporated for the elastic modulus and viscous coefficient of trabecular bone. Unknown material parameters are identified through optimization using the Nelder–Mead algorithm, based on experimental compression data from cadaveric vertebral specimens tested under quasi-static and dynamic loading conditions. The calibrated model reproduced the overall trend of specimen-to-specimen mechanical variation observed experimentally. Predicted stiffness values were in reasonable agreement with measured data. Fracture force predictions showed moderate agreement for dynamically tested specimens (R2 = 0.60), which improved to R2 = 0.88 after exclusion of one statistically identified outlier. Compared with a purely linear elastic formulation, the proposed viscoelastic model demonstrated modest improvement in stiffness prediction and more substantial improvement in fracture force prediction. These findings indicate that incorporating density-dependent viscoelastic effects improves representation of vertebral mechanical behavior, particularly at higher loading rates. Owing to its simplicity and computational efficiency, the proposed model requires only limited imaging input and may be useful for future biomechanical investigations, rapid screening, and injury risk prediction.

Pollen exposure drives allergic disease in millions of Americans, yet no standardized, publicly available national pollen dataset has existed until now. We describe the first nationally standardized and publicly available dataset of pollen season timing and airborne pollen concentrations. The data were derived from the National Allergy Bureau™ (NAB™), the only pollen and mold measuring network in the United States certified by the American Academy of Allergy, Asthma & Immunology (AAAAI), and curated, processed, and disseminated by the U.S. Centers for Disease Control and Prevention (CDC). The 2003–2024 dataset provides standardized measures of (1) taxa-specific historical average main pollen season (MPS) concentrations and timing (e.g., start dates, peak dates, end dates, season length); (2) taxa-specific yearly MPS concentrations and timing; (3) grouped weekly MPS concentrations, levels, and timing; and (4) grouped daily pollen levels and MPS timing. Pollen concentrations are reported as pollen grains per cubic meter (PPCM). MPS timing is computed using a 3-day consecutive method: season start occurs after the first occurrence of three consecutive days with concentrations > 1.0 PPCM; season peak is the day of maximum concentration; and season end occurs after the first occurrence of three consecutive days with concentrations < 1.0 PPCM after the peak. Historical average timing is calculated in a 365-day-of-year format and converted to calendar dates using 2024 as a reference year for display and consistency. By combining long-term data from monitoring sites across the country, this dataset shows how pollen levels vary over time and across geographic locations. This resource supports tracking pollen trends, linking pollen with weather and climate factors, and informing public health action, clinical care, and communication about population exposure and the impact to allergic diseases such as asthma and hay fever.

Background/Objectives: In the United States, HF prevalence is projected to progressively rise by 2030. Prior research suggests a strong association between reduced sleep duration and increased cardiovascular disease and HF risk. This study introduces an alternative parameter, the weekend sleep recovery (WSR), measured by the weekend-to-weekday sleep duration ratio (SDR), to evaluate its association with HF risk. Methods: We conducted a cross-sectional analysis of NHANES (National Health and Nutrition Examination Survey) 2017–2023 to examine self-reported sleep patterns. Participants were classified as WSR (SDR > 1) or non-WSR (SDR ≤ 1). Multivariate logistic regression assessed the association between WSR and HF, adjusting for demographics and comorbidities. Results: Among 8320 participants included in the fully adjusted analysis, WSR was associated with lower odds of HF compared with non-WSR (adjusted OR 0.73, 95% CI 0.55–0.96; p = 0.026). A significant interaction was observed between WSR and weekday sleep duration (P for interaction = 0.003), whereas no interaction was found with weekend sleep duration. In exploratory subgroup analyses, nominally significant associations were observed in several clinical subgroups; however, after correction for multiple comparisons, only participants without dyslipidemia retained statistical significance. No significant effect modification by race/ethnicity was observed (P for interaction = 0.436). Conclusions: Weekend sleep recovery was associated with lower odds of HF in this cross-sectional study. The association varied according to weekday sleep duration but was generally consistent across racial/ethnic groups. Given the observational design, these findings should be interpreted as associative rather than causal and warrant confirmation in prospective studies.

Racial and ethnic survival disparities exist in pediatric and young adult acute lymphoblastic leukemia (ALL), with differential treatment toxicity and setting of care as possible drivers. Whether treatment cost and utilization disparities exist, or how they may contribute to differences in ALL survival, is unknown. Patients with ALL diagnosed between 2000 and 2019 at ages 1 to 24 years were identified using ICD-9/10 codes in the administrative claims data from the OptumLabs Data Warehouse and the Surveillance, Epidemiology, and End Results program. Sex, race and ethnicity, age, year, and subtype of ALL diagnosis were collected. Reimbursed treatment cost and utilization (number of inpatient and outpatient days) were computed over the initial 8 months of treatment. Regression models assessed associations with demographic and clinical characteristics. Survival analyses assessed associations between race and ethnicity and overall survival. Among 374 individuals with ALL, treatment costs were 57% lower for Black patients than for White patients (estimate 0.43, 95% CI: 0.19-0.96; P =0.04). Utilization was similar across groups, though Black patients had 24% fewer outpatient visits (estimate 0.76, 95% CI: 0.58-0.99; P =0.04). No significant differences in survival were detected, but observations are consistent with previous reports. Despite a small sample size, the statistically significantly lower cost and utilization among Black relative to White ALL patients are concerning and warrant further research.

Immune checkpoint inhibitors (ICIs) in non–small cell lung cancer (NSCLC) have improved survival for patients with early-stage NSCLC who are candidates for surgical resection. ICIs enhance antitumor responses and improve a variety of perioperative outcomes when used in the neoadjuvant, adjuvant, or perioperative setting. This review summarizes immunotherapies currently approved for neoadjuvant, adjuvant, and perioperative treatment of resectable NSCLC and the supporting evidence for approval. Gaps in data and future areas of clinical interest of using immunotherapies to maximize survival outcomes are also discussed.