Citations

Summary: Umbilical piercings are popular among young individuals for aesthetic body enhancement. However, umbilical piercings can lead to complications such as infections, hypertrophic scarring, and epithelialized tracts that require surgical intervention. This case report presents a novel, minimally invasive technique using a lacrimal probe and iris scissors under local anesthesia to excise the epithelialized piercing tracts. A 23-year-old patient underwent the procedure, resulting in minimal scarring and high satisfaction at an 11-month follow-up. Compared with the existing methods, this approach ensures complete tract removal while preserving the natural umbilical contour. Given the limited literature, this technique offers an effective solution with excellent cosmetic outcomes.

Abstract Introduction There is convincing evidence that overall adiposity increases the risks of several cancers. Whether the distribution of adiposity plays a similar role is unclear. Methods We used 2-sample Mendelian randomization (MR) to examine causal relationships of 5 adiposity distribution traits (abdominal subcutaneous adipose tissue (ASAT); visceral adipose tissue (VAT); gluteofemoral adipose tissue (GFAT); liver fat; and pancreas fat) with the risks of 12 obesity-related cancers (endometrial, ovarian, breast, colorectal, pancreas, multiple myeloma, liver, kidney (renal cell), thyroid, gallbladder, esophageal adenocarcinoma, and meningioma). Results Sample size across all genome-wide association studies (GWAS) ranged from 8407 to 728 896 (median: 57 249). We found evidence that higher genetically predicted ASAT increased the risks of endometrial cancer, liver cancer, and esophageal adenocarcinoma (odds ratios (OR) and 95% confidence intervals (CI) per standard deviation (SD) higher ASAT = 1.79 (1.18 to 2.71), 3.83 (1.39 to 10.53), and 2.34 (1.15 to 4.78), respectively). Conversely, we found evidence that higher genetically predicted GFAT decreased the risks of breast cancer and meningioma (ORs and 95% CIs per SD higher genetically predicted GFAT = 0.77 (0.62 to 0.97) and 0.53 (0.32 to 0.90), respectively). We also found evidence for an effect of higher genetically predicted VAT and liver fat on increased liver cancer risk (ORs and 95% CIs per SD higher genetically predicted adiposity trait = 4.29 (1.41 to 13.07) and 4.09 (2.29 to 7.28), respectively). Discussion Our analyses provide novel insights into the relationship between adiposity distribution and cancer risk. These insights highlight the potential importance of adipose tissue distribution alongside maintaining a healthy weight for cancer prevention.

Background: Postoperative failure to wean from ventilator support is associated with poor outcomes. This study characterizes patients requiring prolonged ventilation after head-and-neck reconstructive surgery and their outcomes. Methods : Patients who underwent head-and-neck reconstructive surgery were identified in the National Surgical Quality Improvement Program (NSQIP) database using CPT codes, ICD-10 codes, and free-text search. Hypothesis testing and regression analysis was utilized to compare patient characteristics and peri/postoperative complication rates between those with and without extended ventilation. Results : NSQIP contained 4661 patients who underwent free flap surgery; 180 experienced prolonged ventilation. Patients with primary oral cavity/sinonasal malignancy, preoperative ventilator dependence, and preoperative open wound/wound infection were more likely to experience prolonged ventilation. Prolonged ventilation patients experienced double the overall hospital stay, and increased rates of wound disruption, reoperation, and mortality. (p<0.05). Conclusion : Prolonged mechanical ventilation can significantly affect outcomes of free flap patients, including longer hospital stays, and higher 30-day mortality.

ABSTRACT Objectives To explore the clinical impact of social determinants of health (SDoH) stress in bipolar disorder (BD) course of illness and to explore potential gender differences in SDoH stress endorsement. Methods 2280 individuals living with BD type I or II (62% women; 67.5% BD‐I) participating in the Mayo Clinic Bipolar Biobank who completed a questionnaire assessing positive and negative‐valent stressors in the 12 months prior to study enrollment were included for this analysis. Six negative stressors were used as proxies of SDoH. Generalized linear models were used to test the association between SDoH stressors and markers of illness severity as well as potential differences by sex by including an interaction term. Results After adjusting for age, sex, and recruitment site, SDoH‐related stressors were significantly associated with a more severe course of illness in both men and women. Except for unemployment rates, women reported more frequently SDoH‐related stress (i.e., lack of family support, financial problems, health coverage and access problems). Conclusions The study found significant gender differences in both the endorsement of specific SDoH stressors and in the prevalence of specific illness severity markers; however, it did not directly test the predictive relationship between gender differences in SDoH and illness severity markers. Future studies aiming to achieve health equity in mental health care should continue assessing social determinants of health stressors, incorporating a gender perspective to better understand their influence on bipolar disorder.

Association of Outpatient Follow-up with 30-day Readmission after Epilepsy or Seizure Discharge in Medicare Beneficiaries Aged 65 and Older Blank LJ, Van Hyfte G, Agarwal P, Mazumdar M, Jette J. Neurology . 2025;104(10):e213638. Background and Objectives: Older adults are expected to have higher readmission rates after seizure-related hospitalization. We sought to define the 30-day readmission rate for older adults after seizure hospitalization and to examine whether occurrence, timing, or specialization of follow-up with primary or neuro-related care is associated with lower readmission risk. Methods: This is a retrospective cohort study using 2016–2019 Medicare claims data, including adults aged older than 65 years hospitalized with a primary diagnosis of seizure/epilepsy. The primary outcome was readmission within 30 days. Exposure of interest was presence or absence of follow-up and specialty of the follow-up provider. Beneficiaries were followed from 90 days before admission to 30 days after discharge. We defined variables a priori based on literature/clinical judgment and used a least absolute shrinkage and selection operator (LASSO) method to determine factors that were contributing to the data's variance for inclusion in the final model. Results: Of 80,620 beneficiaries with admissions for seizure/epilepsy, 17.72% were readmitted within 30 days. Overall, 20.6% saw only primary care, 2.5% neurology only, 0.3% neurosurgery only, and 0.1% epilepsy only, and 5.4% had a combination of visits. Readmission rates differed by follow-up visit status: 22% readmission rate for those with no follow-up and only 6% with any health care visit. Among those with a visit, the readmission rates by specialty were as follows: 8% for primary care alone, 5% for neurology alone, 16% for neurosurgery alone, 1% for epileptology alone, and 2% for those who had seen a combination of these specialties. In our LASSO-selected multivariable model, outpatient follow-up was associated with lower odds of readmission: early (days 1–15) primary care visit (adjusted odds ratio [aOR] 0.49; 95% CI 0.45–0.52, p < .001); early neurology visit (aOR 0.39; 95% CI 0.33–0.46, p < .001); and later (days 16–30) neurosurgery visit (aOR 0.42; 95% CI 0.27–0.67, p < .001), later neurology visit (aOR 0.16; 95% CI 0.13–0.21, p < .001), or later primary care visit (aOR 0.16; 95% CI 0.14–0.17, p < .001), all associated with reduced odds of readmission. Discussion: We found high rates of readmission in older adults. Outpatient follow-up was associated with reduced odds of readmission. These findings reinforce the importance of discharge planning and suggest that ensuring outpatient follow-up with either primary care or neurology may be an easy intervention to reduce readmissions.

AbstractFatiguing inspiratory work has been shown to evoke a sympathetically mediated reflex that has systemic cardiovascular consequences, including increases in heart rate and blood pressure and a decrease in resting limb vascular conductance. Moreover, the response to this reflex appears to be attenuated in females compared with males. It remains to be seen whether this respiratory muscle metaboreflex also exerts an effect on cerebral blood flow. Cerebral blood flow is tightly regulated to maintain homeostasis and critical function. Therefore, it stands to reason that cerebrovascular haemodynamics would not be compromised through this respiratory muscle metaboreflex. We hypothesized that fatiguing inspiratory work would reduce resting limb conductance, but cerebral blood flow would be minimally impaired. Females (34 ± 10 years old, n = 12) and males (31 ± 8 years old, n = 12) performed a 5 min, high‐intensity bout of inspiratory pressure threshold loading (IPTL) designed to evoke the respiratory muscle metaboreflex. In response to IPTL, mean arterial pressure increased in both males and females (p < 0.001), and limb vascular conductance decreased to a greater degree in males than in females (p = 0.005). The cerebrovascular conductance index was higher in females (p = 0.007) but not affected by IPTL (p = 0.417). Our findings suggest that cerebral blood flow is spared from the redistribution of blood flow in response to fatiguing inspiratory work and that this protection is true in both males and females.

Importance Little research has been done on post-COVID symptoms at 24 months postinfection and on the association these may have on health-related quality of life (HRQOL). Objective We assessed the prevalence and severity of post-COVID symptoms and quantified EuroQol 5 Dimension 5 Level (EQ-5D-5L), self-perceived health question (EuroQol Visual Analogue Scale (EQ-VAS)) and health utility scores (HUS) up to 24 months follow-up. Design The longitudinal multiple cohort CORona Follow-Up (CORFU) study combines seven COVID-19 patient cohorts and a survey among the general public. The participants received questionnaires on several time points. Participants were stratified by: without a known SARS-CoV-2 infection (control group), proven SARS-CoV-2 infection but non-hospitalised, proven SARS-CoV-2 infection hospitalised to the ward, and proven SARS-CoV-2 infection hospitalised to the intensive care unit (ICU). Setting In this study, data of seven COVID-19 patient cohorts and a survey among the general public are included. Participants Former COVID-19 patients and controls participated in this cohort study. Main outcomes and measures Former COVID-19 patients and non-COVID-19 controls were sent questionnaires on symptoms associated with post-COVID condition. The CORFU questionnaire included 14 symptom questions on post-COVID condition using a five-level Likert-scale format. Furthermore, HRQOL was quantified using the EuroQol EQ-5D-5L questionnaire: EQ-VAS and the EQ-5D-5L utility score. The EQ-5D-5L questionnaire includes five domains that are scored on a five-point Likert scale: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Results A total of 901 participants (and 434 controls) responded at 24 months follow-up. In all former COVID-19 patients, the presence of post-COVID condition at 24 months was observed in 62 (42.5%, 95% CI 34.3% to 50.9%) of the non-hospitalised patients, 333 (65.0%, 95% CI 60.7% to 69.2%) of the hospitalised ward patients and 156 (63.2%, 95% CI 56.8% to 69.2%) of the ICU patients, respectively (p<0.001). The most common symptoms included fatigue, sleep problems, muscle weakness/pain and breathing issues, with hospitalised participants reporting most often having symptoms. Multiple post-COVID symptoms were significantly associated with EQ-5D-5L measures. The mean and SD of the EQ-VAS were 71.6 (17.9), 70.0 (17.3) and 71.4 (17.5) for non-hospitalised, ward and ICU participants, respectively, and 75.6 (17.7) for the controls (p<0.001). The HUS resulted in 0.81 (0.20), 0.77 (0.19) and 0.79 (0.22) for non-hospitalised, hospitalised ward and ICU participants, respectively, and 0.84 (0.19) for the control group (CG) (p<0.001). Conclusions Many former COVID-19 patients experience post-COVID symptoms at 24 months follow-up, with the highest prevalence in hospitalised participants. Also, former patients reported a lower HRQOL. Trial registration number The CORFU study was registered at clinicaltrials.gov (registration number NCT05240742).

The aortic pulsatility index (API) (systolic blood pressure-diastolic blood pressure/pulmonary capillary wedge pressure [PCWP]) integrates ventricular output with left ventricular (LV) filling pressures. It offers a surrogate for ventricular-arterial coupling and is associated with the need for advanced therapies and outcomes in decompensated heart failure. However, its use in patients in cardiogenic shock requiring temporary mechanical circulatory support (tMCS) is limited and requires invasive measurement of PCWP. This case series evaluates the concept of echo-API as a noninvasive tool to estimate API using Doppler echocardiography, and its feasibility in patients with cardiogenic shock on tMCS.

Purpose: Model interpretability is a critical requirement for deploying artificial intelligence (AI) applications in clinical speech settings, yet existing evaluation methods often overlook this aspect. The complex nature of speech features and the opaque decision-making processes of AI models underscore the need for a tailored framework to assess interpretability in speech-based clinical AI systems. This article proposes an initial framework composed of eight key factors to consider when evaluating the interpretability of clinical speech AI models. These factors are categorized into two groups: functional factors and clinician-centered factors. The functional factors, which can be assessed independently without user involvement, include faithfulness and computational efficiency. The clinician-centered factors include four established ones from existing literature (cognitive load, human–AI task performance, mental model, and user trust) and two new factors tailored to the unique demands of clinical speech applications: clinical understandability and decision relevance. We further suggest evaluation methods for each of the identified factors and propose modifying existing instruments such as the System Usability Scale and the Healthcare Systems Usability Scale to evaluate the two newly introduced factors. Conclusions: Our identified factors form an initial framework for evaluating the interpretability of speech-based clinical AI systems, supporting the effective integration of AI into clinical workflows. Future works include conducting an evaluation experiment using the proposed framework and refining it further based on the findings from the experiment.