Khanijo, Aditya

Emerging evidence links veno-venous extracorporeal membrane oxygenation (VV-ECMO) to right ventricular (RV) dysfunction, but the relative contribution of ECMO versus underlying disease progression remains unclear. We conducted a multicenter, retrospective, propensity-matched study including 408 intubated acute respiratory distress syndrome (ARDS) patients who were admitted between January 2020 and October 2024 in a quaternary referral hospital network within the United States and underwent at least two transthoracic echocardiograms (TTEs) after intubation. Using 1:2 propensity score matching, we adjusted for baseline comorbidities, baseline hemoglobin, lactate, and worst PaO 2 /FiO 2 ratio (P/F). Longitudinal echocardiographic changes were analyzed with a cumulative link mixed model (CLMM), evaluating RV size and function as ordinal outcomes. Within 408 patients (112 received ECMO support), propensity matching identified 55 ECMO and 110 non-ECMO patients with balanced baseline characteristics. Among 469 serial echocardiograms, RV size and function worsened more frequently in ECMO patients. In longitudinal modeling, ECMO use alone was not associated with RV dilation ( p = 0.23) or dysfunction ( p = 0.43). However, longer ECMO duration was associated with RV dilation (OR: 1.04 per day, p = 0.004) and dysfunction (odds ratio [OR]: 1.04 per day, p < 0.001). Higher ECMO circuit flow had a trend toward progressive RV dilation and dysfunction but did not reach statistical significance. These findings highlight the need for vigilant RV monitoring during ECMO support.

ABSTRACT Background Treating Mycobacterium avium complex (MAC) infection pre‐lung transplant (LT) can be challenging to treat, given prolonged therapy and side effects. The impact of pre‐transplant MAC treatment on recurrence and outcomes post‐LT remains unclear, especially in patients with interstitial lung disease (ILD) who have a median survival of less than 2 years. Methods We performed a retrospective cohort study of adult LT patients at the Mayo Clinic who had positive MAC sputum cultures pre‐LT. The cohort was stratified and compared based on the type of treatment (complete, partial, or no treatment) for MAC pulmonary infection. The primary outcome was MAC recurrence post‐LT, and secondary outcomes were mortality, FEV‐1, and FVC at 1‐year post‐LT. Results Among the cohort of 47 patients, 9 (19.1%) were partially treated and 11 (23.4%) were completely treated for MAC infection pre‐LT. Post‐transplant MAC pulmonary infection recurrence occurred in eight (17%) of the total cohort, with four (14.8%) in the non‐treated, four (44.4%) in the partially‐treated, and none (0%) in the completely treated patients ( p = 0.026). There was no difference in mortality in patients who had MAC recurrence post‐transplantation (13% vs. 9.7%, p > 0.9) and those who were completely or partially treated, compared to non‐treated (0% vs. 13% vs. 13%, p > 0.9). The FEV1 and FVC at 1‐year post‐LT did not differ by the pre‐transplant treatment or post‐transplant MAC recurrence status. Conclusion The role of treatment for MAC infection pre‐transplant is questionable, especially in patients with diseases like ILD who may not have enough wait time to complete therapy.

Backround: Atrial fibrillation (AF) is a common complication following veno-venous extracorporeal membrane oxygenation (VV-ECMO), leading to further complications from anticoagulation or stroke. The Artificial Intelligence AF Prediction Dashboard developed at Mayo Clinic generates two predictive outputs: (1) a continuous probability score and (2) a binary threshold-based signal to predict the likelihood of AF at an individual level after 12-lead electrocardiogram (ECG) is obtained. Using both continuous risk (%) and binary (yes/no) likelihood, we present a novel method to understand AF risk after VV-ECMO cannulation based on pre-ECMO 12-lead ECG. Methods: We reviewed a total of 147 patients on ECMO between 2018 and 2024, from which 85 VV-ECMO patients with complete data were included. AI Dashboard outputs were quantified as binary (1/0) or percent likelihood for AF. R was utilized for statistical analysis. Results: 85 patients met our inclusion criteria from which AF after cannulation occurred in 31 (36%). 17 patients had a history of AF prior to VV-ECMO initiation. The mean age of our cohort was 49 years with a mean BMI of 29.3. Baseline AI Dashboard continuous assessment identified 39 patients (46%) compared to the binary assessment identifying 31 patients (36%). Logistic regression in the binary assessment demonstrated an odds ratio of 1.08 (95% CI 1.04 – 1.12) with a p value of <0.001. The binary AF Prediction yielded a 58% sensitivity, 76% specificity, 58% PPV, and 76% NPV, with an accuracy of 67%. The continuous AF Probability score achieved 72% balanced accuracy with sensitivity 74%, specificity 70%, PPV 59% and NPV 83%, indicating fair overall performance and suggesting good utility for ruling out AF in low-risk patients. Although both outputs provided moderate predictive accuracy, the continuous score reported before ECMO cannulation demonstrated stronger overall performance with fewer false negatives and higher rule-out value. Conclusions: We demonstrate the novel use of an AI predictive model in the VV-ECMO population for the prediction of AF risk with both continuous and binary risk cutoffs from baseline ECG. This data highlights the need for further development in ECMO-specific AI models to help mitigate risk after the onset of atrial arrhythmias. As AI-driven tools become increasingly integrated into care, their performance must be continuously validated and recalibrated for specific populations to ensure their safe and effective use.

Problem Statement: The prognostic value of troponin elevation in septic ICU patients without known history of cardiac disease remains unclear, particularly after accounting for overall illness severity. Background: Minor troponin rises are frequent during sepsis, yet clinicians still lack a clear cut-point that signals danger once cardiac disease is ruled out. We asked whether a modest increase in troponin-T predicts in-hospital death beyond global illness severity. Methods: We studied 1 221 adult first ICU stays labelled “sepsis” in the eICU Collaborative Research Database and removed any case with a cardiac admission diagnosis. Implausible or missing laboratory values were imputed by multiple imputation. Hospital mortality was modelled with logistic regression that included troponin (a continuous and a binary model with threshold > 0.04 ng/mL) together with age, sex, lactate, albumin, BUN, creatinine, intubation status, vasopressor use, dialysis requirement and APACHE-IV predicted mortality. A natural-spline model explored non-linear behavior. Findings were checked in a 1:1 propensity-matched cohort. Results: Overall mortality was 11.7%. Troponin exceeded 0.04 ng/mL in 38% of patients. After adjustment for APACHE-IV probability and other covariates, a troponin level > 0.04 ng/mL was associated with almost twice the odds of death (OR ≈ 1.9), whereas the continuous model suggested only a modest trend (OR ≈ 1.1 per ng/mL). The spline curve rose steeply between 0 and 0.10 ng/mL and flattened thereafter, pinpointing an inflection near 0.05 ng/mL. Matching on all measured confounders confirmed that high-troponin patients had about three-fold greater mortality (OR ≈ 2.8, 1.55-5.05; p<0.001), highlighting that even modest troponin elevation is an independent risk marker for death in septic ICU patients. A bedside heat-map combining troponin, albumin and need for intubation illustrated a simple gradient: risk climbs from 2 % in low-troponin, well-albuminised, non-intubated patients to nearly 7 % when troponin exceeds 0.10 ng/mL in intubated, hypo-albuminemic patients. Conclusions: Even modest troponin elevations (> 0.04 ng/mL) independently predict mortality in sepsis after rigorous adjustment and matching on APACHE-IV physiology, lactate, and organ-support variables. This biologic threshold supports incorporating troponin into bedside triage and future septic cardiomyopathy trials.

ABSTRACTThis report details a severe complication of phenol neurolysis in a diabetic patient, where phenol induced tissue necrosis can lead to severe cellulitis with ulceration that may prove difficult to treat. It emphasizes the importance of considering comorbidities when selecting phenol neurolysis for treatment of chronic pain.