Bogojevic, Marija

Abstract Background CERTAIN (Checklist for Early Recognition and Treatment of Acute Illness and iNjury) has been shown to improve critical care process and patient outcomes in international ICUs with variable resources. Methods CERTAIN education program derived from this approach is designed, promoted, and implemented following the Logic model. Through the roadmap of the Logic model, we presented a dynamic, longitudinal implementation framework that had sufficient rigor yet offers flexibility to reach the need of the existing and emerging diversified medical education projects. Results Using the Logic model, the delivery of the CERTAIN education program is optimized to deliver relevant education content in various environments. During the COVID-19 outbreak, the implementational framework demonstrated that it could serve as an excellent template for effective response to global pandemics. Conclusions The Logical model is useful as a facilitation tool for planning and evaluating innovative education delivery and dissemination. The CERTAIN program provided an example for other continuous professional education projects.

Significance Statement A higher percentage of the kidney cortex area that exhibits interstitial fibrosis/tubular atrophy (IF/TA) is a feature of poor prognosis on biopsy. This study describes IF/TA density (the number of IF/TA foci per area of cortex) and shows it predicts progressive CKD, independent of both percentage IF/TA and clinical characteristics among patients who have undergone nephrectomy. Other patterns of IF/TA and inflammation were not predictive for progressive CKD and mortality beyond percentage IF/TA and clinical characteristics. At the same percentage IF/TA, a higher IF/TA density suggests more scattered and widespread damage to the nephrons, with a worse kidney prognosis. This information may be helpful for accurate interpretation of the severity of “chronic changes” observed on a kidney biopsy. Background Chronic tubulointerstitial injury on kidney biopsy is usually quantified by the percentage of cortex with interstitial fibrosis/tubular atrophy (IF/TA). Whether other patterns of IF/TA or inflammation in the tubulointerstitium have prognostic importance beyond percentage IF/TA is unclear. Methods We obtained, stained, and digitally scanned full cortical thickness wedge sections of renal parenchyma from patients who underwent a radical nephrectomy for a tumor over 2000–2015, and morphometrically analyzed the tubulointerstitium of the cortex for percentage IF/TA, IF/TA density (foci per mm 2 cortex), percentage subcapsular IF/TA, striped IF/TA, percentage inflammation (both within and outside IF/TA regions), and percentage subcapsular inflammation. Patients were followed with visits every 6–12 months. Progressive CKD was defined as dialysis, kidney transplantation, or 40% decline from the postnephrectomy eGFR. Cox models assessed the risk of CKD or noncancer mortality with morphometric measures of tubulointerstitial injury after adjustment for the percentage IF/TA and clinical characteristics. Results Among 936 patients (mean age, 64 years; postnephrectomy baseline eGFR, 48 ml/min per 1.73m 2 ), 117 progressive CKD events and 183 noncancer deaths occurred over a median 6.4 years. Higher IF/TA density predicted both progressive CKD and noncancer mortality after adjustment for percentage IF/TA and predicted progressive CKD after further adjustment for clinical characteristics. Independent of percentage IF/TA, age, and sex, higher IF/TA density correlated with lower eGFR, smaller nonsclerosed glomeruli, more global glomerulosclerosis, and smaller total cortical volume. Conclusions Higher density of IF/TA foci (a more scattered pattern with more and smaller foci) predicts higher risk of progressive CKD after radical nephrectomy compared with the same percentage of IF/TA but with fewer and larger foci.

ABSTRACT Objectives The objectives of this study were to test in real time a Trauma Triage, Treatment, and Training Decision Support (4TDS) machine learning (ML) model of shock detection in a prospective silent trial, and to evaluate specificity, sensitivity, and other estimates of diagnostic performance compared to the gold standard of electronic medical records (EMRs) review. Design We performed a single-center diagnostic performance study. Patients and setting A prospective cohort consisted of consecutive patients aged 18 years and older who were admitted from May 1 through September 30, 2020 to six Mayo Clinic intensive care units (ICUs) and five progressive care units. Measurements and main results During the study time, 5,384 out of 6,630 hospital admissions were eligible. During the same period, the 4TDS shock model sent 825 alerts and 632 were eligible. Among 632 hospital admissions with alerts, 287 were screened positive and 345 were negative. Among 4,752 hospital admissions without alerts, 78 were screened positive and 4,674 were negative. The area under the receiver operating characteristics curve for the 4TDS shock model was 0.86 (95% CI 0.85-0.87%). The 4TDS shock model demonstrated a sensitivity of 78.6% (95% CI 74.1-82.7%) and a specificity of 93.1% (95% CI 92.4-93.8%). The model showed a positive predictive value of 45.4% (95% CI 42.6-48.3%) and a negative predictive value of 98.4% (95% CI 98-98.6%). Conclusions We successfully validated an ML model to detect circulatory shock in a prospective observational study. The model used only vital signs and showed moderate performance compared to the gold standard of clinician EMR review when applied to an ICU patient cohort.