Citations

Introduction Post-intubation hypotension (PIH) is a frequent complication of emergency endotracheal intubation and is associated with increased mortality. Early identification of high-risk patients remains challenging, and existing prediction tools demonstrate moderate accuracy. Objective We aim to identify predictors of PIH and develop machine learning models for pre-intubation risk stratification. Methods We conducted a multicentre retrospective study across 3 Mayo Clinic hospitals, including 600 adults undergoing urgent intubation in the intensive care unit. PIH was defined by mean arterial pressure<65 mm Hg, systolic blood pressure (SBP)<80 mm Hg or ≥40% decline or vasopressor initiation/escalation within 30 min. Three model frameworks were developed: Shock Indices (SIs), Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA), incorporating demographic, haemodynamic, laboratory and sedation variables. Various machine learning algorithms were applied to analyse the three models. Results PIH occurred in 46% of patients included in the study. In the SIs model, stepwise logistic regression achieved an area under the curve (AUC) of 0.76. The APACHE II framework showed the strongest performance, with random forest achieving an ROC AUC of 0.82 and the ensemble model demonstrating the highest overall discrimination (Receiver operator Curve [ROC] AUC 0.83) with favourable accuracy and F1 metrics. The SOFA framework showed moderate performance, with an ensemble ROC AUC of 0.73. Key predictors included pre-intubation vasopressor use, SBP, platelet count and haematological parameters. Conclusions Machine learning models using routinely available pre-intubation data showed potential to predict PIH in this retrospective proof-of-concept study. These findings support further development of anticipatory artificial intelligence-driven risk stratification in critical care, but the models should not be considered ready for bedside implementation until they undergo prospective validation in larger, independent and more diverse cohorts.

ABSTRACT Purpose This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Background Connective tissue disorders (CTDs) such as Marfan syndrome, Loeys-Dietz syndrome, and Ehlers-Danlos syndromes are traditionally defined by vascular fragility and aortic complications. Increasing evidence, however, demonstrates that CTDs also predispose to atrial and ventricular arrhythmias, often independent of overt cardiomyopathy or severe valvular disease. Content This review integrates emerging data on the arrhythmogenic substrates of CTDs. Four mechanistic bridges are emphasized: (1) diffuse myocardial fibrosis driven by dysregulated TGF-β signaling, (2) structural valve and annular abnormalities, particularly mitral valve prolapse and mitral annular disjunction, (3) altered mechanotransduction linking extracellular matrix instability to cytoskeletal and nuclear signaling pathways, and (4) downstream ion-channel and gap-junction remodeling as secondary amplifiers. We outline the genetic architecture underlying these processes, focusing on established CTD-implicated genes in the TGF-β/SMAD pathway, valve and annulus regulators, cytoskeletal and myocyte-coupling proteins, and extracellular matrix components, while incorporating emerging CTD modifiers that expand the spectrum of arrhythmia susceptibility. Summary Recognition of CTDs as both vascular and electrical disorders reframes clinical management. Imaging markers such as mitral annular disjunction and diffuse fibrosis, together with targeted ambulatory rhythm monitoring and consideration of genetic context, may improve recognition of higher-risk phenotypes. Therapeutic strategies must balance arrhythmia control with procedural risk in fragile connective tissue substrates. Conclusions By unifying genetic, mechanistic, and clinical insights, this review provides an integrated framework for understanding arrhythmias in CTDs. It underscores the need for prospective registries and genotype-phenotype studies to refine surveillance and prevention strategies.

Background Alzheimer's disease (AD) and related dementias are leading causes of death worldwide. While socioeconomic status (SES) is a critical determinant, its impact on mortality after diagnosis remains understudied. Objective To investigate the roles of neighborhood-level and individual-level SES in predicting mortality risk among older adults with incident dementia. Methods We analyzed data from 924 participants with incident dementia from the Mayo Clinic Study of Aging (N = 6909), a cohort with clinical follow-up visits every 15 months. We assessed mortality risk using Cox's time-varying survival regression, adjusting for time-fixed and time-varying covariates. Primary predictors were neighborhood-level SES (Area Deprivation Index [ADI]) and individual-level SES (housing-based SES index [HOUSES], education, and occupation). We also applied a random survival forest model to assess the predictive contribution of SES indicators and identify influential predictors. Results 857 participants (92.7%) died, with a median time from dementia diagnosis to death of 29 months (IQR: 12–54). Lower SES measured by HOUSES was associated with increased mortality risk (HR 1.28, 95% CI 1.07–1.52). Conversely, ADI, education, and occupation were not associated with mortality. Male sex, older age, congestive heart failure and diabetes were associated with higher mortality risk. In predictive analysis, HOUSES ranked among the top 10 contributors to mortality risk. Conclusions Among older adults with dementia, lower HOUSES was associated with higher mortality risk beyond neighborhood-level deprivation, education, and occupation. Integrating this housing-based individual-level SES measure into dementia care planning may help identify patients with greater socioeconomic vulnerability and inform mortality risk stratification.

Background: Tobacco use is a known risk factor for poor healing after rotator cuff repair (RCR), but the effects of nontobacco nicotine products remain unclear. Purpose: To compare postoperative complications among nontobacco nicotine users, tobacco users, and nonusers undergoing RCR. Study Design: Cohort study; Level of evidence, 3. Methods: Using the PearlDiver database, the authors identified patients who underwent arthroscopic RCR with ≥2 years of follow-up. Three 1:1 propensity-matched comparisons were conducted: nontobacco nicotine users versus nonusers (n = 4844), tobacco users versus nonusers (n = 19,182), and nontobacco nicotine users vs tobacco users (n = 4882). Outcomes included 90-day complications and 2-year revision surgeries. Results: Nontobacco nicotine users had mildly higher rates of lysis of adhesions than controls (0.7% vs 0.4%; OR, 1.95; P = .033) but no other significant differences. Tobacco users showed increased rates of acute kidney injury (AKI), pneumonia, infections, emergency department (ED) visits, readmissions, and revision surgery compared to controls. Compared to tobacco users, nontobacco nicotine users had moderately strong lower risks of pneumonia (0.6% vs 1.2%; OR, 0.46), ED visits (8.8% vs 13.6%; OR, 0.62), and readmissions (0.8% vs 1.5%; OR, 0.54) (all P < .01). Conclusion: While nontobacco nicotine use was associated with a modestly increased risk of lysis of adhesions after RCR, it did not significantly elevate the risk of major medical complications, infections, or revision surgery when compared to nonnicotine users. In contrast, tobacco users demonstrated consistently worse postoperative outcomes across multiple domains, including higher rates of AKI, pneumonia, surgical site infection, ED visits, readmissions, and revision procedures. Notably, when compared directly to tobacco users, nontobacco nicotine users had significantly lower rates of pneumonia, ED utilization, and readmissions. These findings suggest that although nontobacco nicotine products may not be entirely benign, their perioperative risk profile appears to be less severe than that of traditional tobacco use.

Introduction Advancements in transplant care have led to an increasing number of women with solid organ transplantation (SOT) living through peri- and postmenopause. Menopause can significantly impact quality of life, and the added burden of SOT may exacerbate symptoms. Few studies have evaluated the menopausal experience in this population, and existing data rarely use validated questionnaires. Research Question This study aimed to characterize menopausal symptoms and menopausal hormone therapy (MHT) use in peri- and postmenopausal SOT recipients using validated measures. Design A cross-sectional survey study of female patients ≥18 years who underwent SOT between 2018 and 2023 was conducted at a tertiary transplant center. A reproductive and sexual health questionnaire incorporating validated instruments, including the Menopause Rating Scale (MRS), was administered. Results Among peri- and postmenopausal SOT recipients ( n = 192), 8.9% reported use of MHT. The median MRS total score was 8.0, consistent with mild-to-moderate symptom severity overall. Symptom severity differed by menopausal status for vasomotor symptoms ( P =.03), sleep disturbances ( P = .04), depressive mood ( P = .04), and anxiety ( P <.001), with perimenopausal participants generally reporting more symptoms in these domains than postmenopausal participants. Despite these differences, overall symptom severity remained mild to moderate in both groups. Conclusion Menopausal symptoms among female SOT recipients are common but generally mild to moderate, with low utilization of MHT. The lack of increased vasomotor burden compared to prior literature may reflect under-recognition or misattribution of symptoms to transplant-related factors. Incorporating menopause-specific screening into transplant care may improve symptom recognition, quality of life, and long-term health outcomes.

Aims Two-stage exchange arthroplasty with an antibiotic-eluting cement spacer remains the predominant strategy in the USA for managing chronic periprosthetic joint infection (PJI) following total hip arthroplasty (THA). The aim of this study was to evaluate a commercially available, partially intraoperatively fabricated articulating high-dose antibiotic cement spacer, focusing on survival, complications, and patient-reported outcomes. Methods A total of 298 patients (302 THAs) underwent two-stage exchange arthroplasty for PJI using a specific articulating antibiotic spacer between August 2005 and May 2022. Patients with a previous failed two-stage exchange were excluded, although 121 THAs (302, 40%) had undergone previous PJI-related procedures. The mean age of the patients was 65 years (SD 11), the mean BMI was 32 kg/m 2 (SD 7), and 116 (38%) were female. Most patients were classified as McPherson host B (158; 52%) and limb grade 2 (165; 55%), and 265 (88%) met the 2011 Musculoskeletal Infection Society criteria. The mean follow-up was six years (2 to 16). Results At five years after reimplantation, survival free of reinfection, aseptic rerevision, any rerevision, or any reoperation were 89% (95% CI 85.2 to 93.1), 93% (95% CI 89.3 to 96.1), 86% (95% CI 81.3 to 90.3), and 80% (95% CI 74.7 to 84.9), respectively. Dislocation accounted for most aseptic rerevisions (15/20). McPherson host C (HR 3.7 (95% CI 1.4 to 9.6); p = 0.007) and limb grade 3 (HR 3.3 (95% CI 1.0 to 11.1); p = 0.049) were significantly associated with an increased risk of reinfection. The mean Harris Hip Score at the latest follow-up was 76 (29 to 100). A total of 17 patients underwent revision or removal of a spacer for concerns about persistent infection and two for dislocation of the spacer. Eight patients underwent a non-rerevision reoperation during the spacer interval for wound drainage (n = 5), dislocation of the spacer (n = 2), and perispacer fracture (n = 1). A total of 26 spacer-related complications were treated nonoperatively (15 perispacer fractures, 11 dislocations). Dislocation of the spacer was strongly associated with dislocation after reimplantation (HR 6.2 (95% CI 2.3 to 16.9); p < 0.001). Conclusion This commercially available, partially intraoperatively fabricated articulating spacer showed excellent reinfection-free five-year survival (89%). Spacer-related fracture and dislocation each occurred in 5% of patients. Dislocation of the spacer significantly increased the risk of dislocation following reimplantation, supporting the use of higher-stability bearings in these high-risk patients. Cite this article: Bone Joint J 2026;108-B(9):1104–1112.