Citations

Objectives: Modifiable lifestyle factors are associated with morbidity and mortality in hematopoietic stem cell transplant (HSCT) survivors. The aims of the study were to examine: (a) receipt of provider advice to change behaviors, (b) health behavior change, and (c) how modifiable lifestyle factors might cluster together. Methods: Patients within a large HSCT program completed a survey (N =870) of lifestyle factors at pre-HSCT evaluation. The survey assessed self-reported adherence to American Cancer Society and HSCT guidelines for cancer survivorship in the year prior to a pre-HSCT evaluation. Lifestyle factors of interest were physical activity, fruit and vegetable consumption, tobacco use, alcohol use, and height/weight to calculate Body Mass Index (BMI). Results: Among patients not meeting all five guidelines (98%), 31% received provider advice to change. Between 10% and 42% reported healthy behavior change since diagnosis. Physical activity, fruit and vegetable consumption, and BMI were the most commonly clustered lifestyle behaviors. Conclusions: A considerable proportion of patients did not meet national guidelines for lifestyle factors. Results highlight an immediate opportunity to improve health care delivery and transplant outcomes via pre-HSCT lifestyle screening and implementation of effective health behavior change interventions.

Fusobacterium nucleatum and Prevotella loescheii are anaerobic gram-negative rods that exist in the oral cavity. To our knowledge, pediatric central nervous system complications with these pathogens have not been well described. An 11-year-old previously healthy vaccinated female child presented for 2 weeks of sinusitis that progressed to left arm and leg hemiplegia. Initial neuroimaging demonstrated a superior sagittal sinus thrombosis and a right hemispheric subdural empyema with midline shift, necessitating surgical evacuation. Culture of the subdural accumulation demonstrated coinfection of Fusobacterium nucleatum and Prevotella loescheii . Within 24 hours of evacuation, the patient progressed to have right hemispheric electrographic status epilepticus, with neuroimaging demonstrating reaccumulation of the empyema and a moderate right middle cerebral artery vasospasm. Transcranial doppler ultrasonography of the right middle cerebral artery territory demonstrated mean flow velocities up to 148 cm/s with a Lindengaard ratio of 3.44. The patient underwent repeat subdural evacuation and was managed with intravenous fluids, permissive hypertension, oral nimodipine, and intravenous milrinone. Electrographic status epilepticus was treated with intravenous lacosamide and levetiracetam. Repeat neuroimaging demonstrated improvement in subdural collection size and resolution of vasospasms. She was discharged after 16 days with continued lacosamide and levetiracetam for seizures, and enoxaparin (Lovenox) for the superior sagittal sinus thrombosis. We present a novel pediatric case of Fusobacterium nucleatum and Prevotella loescheii manifesting with rapid subdural empyema reaccumulation after surgical evacuation, status epilepticus, cerebrovascular vasospasms, and cerebral sinus venous thrombosis. Further work is needed to understand the potential neurologic complications of this condition.

Background: Procalcitonin (PCT) is recognized as an inflammatory biomarker, often elevated in COVID-19 pneumonia alongside other biomarkers. Understanding its association with severe outcomes and comparing its predictive ability with other biomarkers is crucial for clinical management. Objectives: This retrospective multicenter observational study aimed to investigate the association between PCT levels and adverse outcomes in hospitalized COVID-19 patients. Additionally, it sought to compare the predictive performance of various biomarkers. Design: The study analyzed data from the Society of Critical Care Medicine (SCCM) Viral Infection and Respiratory Illness Universal Study (VIRUS) registry, comprising COVID-19 patients hospitalized across multiple Mayo Clinic sites between March 2020 and June 2022. Methods: A total of 7851 adult COVID-19 patients were included. Patients were categorized into 6 groups based on the worst WHO ordinal scale. Multivariate models were constructed using peak biomarker levels within 72 hours of admission, adjusted for confounders. Results: Elevated PCT levels were independently associated with increased odds of adverse outcomes, including ICU admission (adjusted odds ratio [aOR] 1.32, 95%CI 1.27-1.38), IMV requirement (aOR 1.35, 95%CI: 1.28-1.42), and in-hospital mortality (aOR 1.30, 95%CI: 1.22-1.37). A 3.48-fold increase in IMV requirement and 3.55 times increase in in-hospital mortality were noted with peak PCT ⩾ 0.25 ng/ml. Similar associations were observed with other biomarkers like NLR (AUC 0.730), CRP, IL-6, LDH (AUC 0.800), and D-dimer (AUC 0.719). Models incorporating NLR, LDH, D-dimer, and PCT demonstrated the highest predictive accuracy, with a combined model exhibiting an area under the curve (AUC) of 0.826 (95%CI 0.803-0.849). Conclusions: Higher PCT levels were significantly linked to worse outcomes in COVID-19 patients, emphasizing its potential as a prognostic marker. Biomarker-based predictive models, particularly those including PCT, showed promising utility for risk assessment and clinical decision-making. Further prospective studies are warranted to validate these findings on a larger scale.

Abstract Glioblastoma (GBM) remains the most common and lethal adult malignant primary brain cancer with few treatment options. A significant issue hindering GBM therapeutic development is intratumor heterogeneity. GBM tumors contain neoplastic cells within a spectrum of different transcriptional states. Identifying effective therapeutics requires a platform that predicts the differential sensitivity and resistance of these states to various treatments. Here, we developed a novel framework, ISOSCELES ( I nferred cell S ensitivity O perating on the integration of S ingle- C ell E xpression and L 1000 E xpression S ignatures), to quantify the cellular drug sensitivity and resistance landscape. Using single-cell RNA sequencing of newly diagnosed and recurrent GBM tumors, we identified compounds from the LINCS L1000 database with transcriptional response signatures selectively discordant with distinct GBM cell states. We validated the significance of these findings in vitro, ex vivo, and in vivo , and identified a novel combination of an OLIG2 inhibitor and Depatux-M for GBM. Our studies suggest that ISOSCELES identifies cell states sensitive and resistant to targeted therapies in GBM and that it can be applied to identify new synergistic combinations. Highlights Integration of GBM single-cell RNA sequencing data with L1000-derived drug response signatures facilitates clustering of tumor cells and small molecules on cell-drug connectivity. Cell-drug connectivity predicts the identities of drug-sensitive and resistant cell states. In silico perturbation analysis using cell-drug connectivity predicts drug-induced changes in the cell-drug connectivity landscape in vivo. In silico perturbation analysis to predict drug-induced changes in the tumor cell-drug connectivity landscape predicts drug combinations that synergize in vivo to extend survival.

Background The management and use of antibiotics in pediatric ear lacerations lacks standardization. This study sought to provide a comprehensive review of these injuries and assess the impact of administering perioperative antibiotics on the incidence of infections after repair. Methods Retrospective review of all pediatric ear lacerations treated at our institution's emergency department (ED) between 1998 and 2024. Results A total of 246 patients (177 boys) were included. Patients aged 0–6 years were most affected (n = 117, 47.6%), with the peak between 2–5 years old (n = 78, 31.7%). Most lacerations were superficial (n = 145, 58.9%), followed by intermediate (n = 62, 25.2%), full thickness (n = 34, 13.9%), and split earlobe defects (n = 5, 2%). Most of the patients (n = 110, 54.7%) were managed by emergency medicine providers. Plastic and reconstructive surgery (n = 34, 16.9%) and otorhinolaryngology (n = 32, 15.9%) consultations were obtained when the lacerations affected cartilage (P < 0.001). Surgical repair included primary closure in 203 (82.5%), with 179 (88.2%) performed under local/topical anesthesia in the ED. Of patients with cartilage lacerations (n = 61), 48 had cartilage repair. Eight patients had preoperative intravenous antibiotics, while 105 (42.7%) received postoperative prophylactic oral antibiotics. Among those with intermediate and full-thickness injuries (n = 96), 67.7% were discharged on prophylactic oral antibiotics. Only 1 case of surgical site infection occurred in a patient with a superficial laceration. Conclusions Pediatric ear lacerations mostly affect boys aged 2–5 years and are usually repaired under local anesthesia in the ED. The incidence of infection is low, and the routine prescription of prophylactic oral antibiotics appears to have a limited impact on the overall incidence of surgical site infection. Further studies are needed to validate these findings.

INTRODUCTION: The SPEC-AI Nigeria trial (NCT05438576) was designed to use artificial intelligence (AI) to screen for pregnancy-related cardiomyopathy in the peripartum period. Using data from this study, we evaluated the utility of AI-predicted delta age (adjusted AI-predicted age − chronological age) as a surrogate for biological age. METHODS: We included 1,187 pregnant and postpartum women enrolled between August 2022 and September 2023 with follow-up through May 2024. Standard 12-lead electrocardiograms (ECGs) were recorded at study entry to generate AI age predictions. Artificial intelligence-predicted age was adjusted using estimated reference ranges obtained from a community-dwelling cohort of 25,144 individuals with AI-ECG age estimated and documented chronological age. Logistic and Cox-proportional hazards regression were used to examine associations with comorbid cardiovascular conditions and maternal mortality, respectively. RESULTS: Adjusted AI-predicted age was significantly higher among women with any cardiovascular condition, peripartum cardiomyopathy, or who died within 18 months (7, 14, and 23 years older, respectively) compared to those without these conditions who had values similar to the normal reference ranges (adjusted AI-predicted age difference less than 1 year). Artificial intelligence-predicted delta age greater than the 75th percentile was associated with an odds ratio (OR) of 2.06 for any cardiovascular condition, OR of 4.98 for left ventricular systolic dysfunction, and a hazard ratio of 32.81 for all-cause mortality; all values of P<.001. CONCLUSIONS/IMPLICATIONS: Artificial intelligence-ECG-derived biological age appears to be a potentially useful measure of cardiovascular health status and risk among pregnant and postpartum women. However, its role in monitoring maternal health requires further exploration.

INTRODUCTION: After an increase in labor induction-associated uterine rupture cases, our institution implemented a restrictive trial of labor after cesarean (TOLAC) induction of labor (IOL) eligibility policy. The policy did not allow elective IOL to TOLAC patients and denied medically indicated IOL to patients who met any of the following criteria: two or more cesarean deliveries; body mass index greater or equal to 50 AND without a prior vaginal delivery; a priori predicted success rate of less than 60% AND Bishop score of less than 8. We investigated how this policy affected uterine rupture and VBAC rates. METHODS: This was a retrospective cohort of 4,356 participants with a prior cesarean delivery who delivered a subsequent neonate between 2011 and 2022. Uterine rupture rates were compared before and after implementation of the eligibility policy in 2018. The primary outcomes were uterine rupture and rates of VBAC. Multivariable logistic regression was performed. RESULTS: The uterine rupture rate decreased by 50% after implementation of eligibility criteria (0.9% pre-policy, 0.5% post-policy). The VBAC rate decreased from 30% to 25%, whereas the unsuccessful TOLAC rate decreased from 7.3% to 5%. CONCLUSIONS/IMPLICATIONS: This study supports previous studies that demonstrate IOL in TOLAC patients may increase the risk of uterine rupture. Restrictive criteria for IOL in TOLAC patients decreased the rates of uterine rupture and unsuccessful TOLAC, however decreased the overall VBAC rate. Uterine rupture is a rare, yet catastrophic event, and more studies are needed to develop policies that minimize risk to TOLAC patients and maximize VBAC rates.

INTRODUCTION: Cardiovascular disease is a leading cause of maternal mortality. Our aim was to evaluate the feasibility and quality of artificial intelligence (AI)-guided focused cardiac ultrasound (FoCUS) by novice scanners to screen for left ventricular (LV) systolic dysfunction in pregnant individuals. METHODS: Patients were prospectively enrolled during routine obstetric appointments. FoCUS images were acquired by individuals without scanning or clinical experience using AI-guided image acquisition software (UltraSight) on a Philips Lumify device. Standard two-dimensional imaging views were attempted: parasternal long axis (PSLA), parasternal short axis mid-level (PSSA Mid), apical four chamber (A4C), three chamber (A3C), and two chamber (A2C). Two experienced cardiologists reviewed all images and graded diagnostic quality: poor, adequate, good, excellent. RESULTS: A total of 101 pregnant participants were enrolled; median age was 32 (interquartile range [IQR], 29, 35) years. The median gestational age was 23 (IQR, 16, 31) weeks; 16% first trimester, 45% second, and 39% third. The most feasible views were the PSLA and PSSA Mid, 98% and 97% with adequate or greater image quality, respectively. A3C and A2C were least feasible, acquired in 34% and 40% with adequate or greater image quality in 28% and 35%, respectively. Average scan time was 6 minutes, 46 seconds ± 0.2. The LV ejection fraction could be determined for the entire cohort and was normal (50–75%) for all. CONCLUSIONS/IMPLICATIONS: Implementation of AI-guided FoCUS in pregnant individuals is feasible, even in the absence of an experienced sonographer. This approach could allow for low-cost screening and early diagnosis of LV systolic dysfunction during pregnancy.