SARS-CoV-2 Slows Brain Rhythms with more Severe Effects in Younger Individuals

Coronavirus disease secondary to infection by SARS-CoV-2 (COVID19 or C19) causes respiratory illness, as well as severe neurological symptoms that have not been fully characterized. In a previous study, we developed a computational pipeline for the automated, rapid, high-throughput and objective analysis of brain encephalography (EEG) rhythms. In this retrospective study, we used this pipeline to define the quantitative EEG changes in patients with a PCR-positive diagnosis of C19 (n=31) in the intensive care unit (ICU) of Cleveland Clinic, compared to a group of age-matched PCR-negative (n=38) control patients in the same ICU setting. Qualitative assessment of EEG by two independent teams of electroencephalographers confirmed prior reports with regards to the high prevalence of diffuse encephalopathy in C19 patients, although the diagnosis of encephalopathy was inconsistent between teams. Quantitative analysis of EEG showed distinct slowing of brain rhythms in C19 patients compared to control (enhanced delta power and attenuated alpha-beta power). Surprisingly, these C19-related changes in EEG power were more prominent in patients below age 70. Moreover, machine learning algorithms showed consistently higher accuracy in the binary classification of patients as C19 versus control using EEG power for subjects below age 70 compared to older ones, providing further evidence for the more severe impact of SARS-CoV-2 on brain rhythms in younger individuals irrespective of PCR diagnosis or symptomatology, and raising concerns over potential long-term effects of C19 on brain physiology in the adult population and the utility of EEG monitoring in C19 patients.

Computer-Aided Diagnostics of Heart Disease Risk Prediction Using Boosting Support Vector Machine

Heart diseases are a leading cause of death worldwide, and they have sparked a lot of interest in the scientific community. Because of the high number of impulsive deaths associated with it, early detection is critical. This study proposes a boosting Support Vector Machine (SVM) technique as the backbone of computer-aided diagnostic tools for more accurately forecasting heart disease risk levels. The datasets which contain 13 attributes such as gender, age, blood pressure, and chest pain are taken from the Cleveland clinic. In total, there were 303 records with 6 tuples having missing values. To clean the data, we deleted the 6 missing records through the listwise technique. The size of data, and the fact that it is a purely random subset, made this approach have no significant effect for the experiment because there were no biases. Salient features are selected using the boosting technique to speed up and improve accuracies. Using the train/test split approach, the data is then partitioned into training and testing. SVM is then used to train and test the data. The C parameter is set at 0.05 and the linear kernel function is used. Logistic regression, Nave Bayes, decision trees, Multilayer Perceptron, and random forest were used to compare the results. The proposed boosting SVM performed exceptionally well, making it a better tool than the existing techniques.

External Validation of the Cardiac Surgery Score in a Quaternary Hospital in the United States of America

Background The Cardiac Surgery Score (CASUS) was developed to assist in predicting post-cardiac surgery mortality using parameters measured in the intensive care unit. It is calculated by assigning points to ten physiologic variables and adding them to obtain a score (additive CASUS), or by logistic regression to weight the variables and estimate the probability of mortality (logistic CASUS). Both additive and logistic CASUS have been externally validated elsewhere, but not yet in the United States of America (USA). This study aims to validate CASUS in a quaternary hospital in the USA and compare the predictive performance of additive to logistic CASUS in this setting. Methods Additive and logistic CASUS (postoperative days 1-5) were calculated for 7098 patients at Cleveland Clinic from January 2015 to February 2017. 30-day mortality data were abstracted from institutional records and the Death Registries for Ohio State and the Centers for Disease Control. Given a low event rate, model discrimination was assessed by area under the curve (AUROC), partial AUROC (pAUC), and average precision (AP). Calibration was assessed by curves and quantified using Harrell's Emax, and Integrated Calibration Index (ICI). Results 30-day mortality rate was 1.37%. For additive CASUS, odds ratio for mortality was 1.41 (1.35-1.46, P <0.001). Additive and logistic CASUS had comparable pAUC and AUROC (all >0.83). However, additive CASUS had greater AP, especially on postoperative day 1 (0.22 vs. 0.11). Additive CASUS had better calibration curves, and lower Emax, and ICI on all days. Conclusions Additive and logistic CASUS discriminated well for postoperative 30-day mortality in our quaternary center in the USA, however logistic CASUS under-predicted mortality in our cohort. Given its ease of calculation, and better predictive accuracy, additive CASUS may be the preferred model for postoperative use. Validation in more typical cardiac surgery centers in the USA is recommended.

Characterization of Patients With Type 2 Diabetes and Chronic Kidney Disease in a Large Integrated Health System

Background: Chronic kidney disease (CKD) poses substantial clinical, economic, and humanistic burden in patients with type 2 diabetes (T2D). Understanding of how to optimize patient care and slow disease progression is warranted.Objective: To compare the prevalence, clinical characteristics, treatment patterns, and healthcare utilization among patients with CKD, T2D, or CKD associated with T2D.Design: Retrospective cross-sectional analysis. Patients: Adult patients with CKD, T2D, or CKD+T2D in the Cleveland Clinic Health System.Main Measures: Clinical characteristics, laboratory measures, medication utilization, cardiometabolic management and healthcare resource utilization.Key Results: In 2019, 122,276 patients were identified as CKD, 63,643 were identified as T2D, and 35,255 were identified as having CKD associated with T2D. Patients with CKD and CKD+T2D were observed to be older than those with T2D alone, 72.6, 72.2, and 63.0 years, respectively. T2D and T2D+CKD cohorts contained a higher percentage of males vs. those with CKD alone, 49.3%, 50.8%, 43.6%, respectively. ACEi/ARB therapy was observed in 27.7%, 42.4%, and 31.5% patients with CKD, T2D+CKD, and T2D, respectively. SGLT-2i therapy was only prescribed to a minority of patients with T2D (5.8%) and T2D+CKD (4.7%). Emergency department visits and hospital admissions were more prevalent in the group with CKD (26.5%, 52.9%) or CKD+T2D (28.8%, 54.9%) vs. T2D alone (18.6%, 41.8%), respectively. The majority of patients with CKD (90.4%), CKD+T2D (60.0%) or T2D (69.1%) did not have an assessment of urine protein.Conclusions: Patients with CKD+T2D or CKD have higher healthcare resource utilization than those with T2D alone. The majority of patients with CKD, CKD+T2D or T2D do not undergo assessment of urine protein and are under prescribed ACEi/ARB therapy. SGLT-2i therapy was prescribed to only a small minority of patients with T2D or CKD+T2D. An opportunity exists to improve the care of patients with CKD, both with and without T2D.

What’s in Your Nomogram? Personalized Prognostication of Verbal Memory Decline after Temporal Lobe Resection in Adults With Epilepsy

Objective This study aims to develop and externally validate models to predict the probability of postoperative verbal memory decline in adults following temporal lobe resection (TLR) for epilepsy using easily accessible preoperative clinical predictors. Methods Multivariable models were developed to predict delayed verbal memory outcome on 3 commonly used measures: Rey Auditory Verbal Learning Test (RAVLT), and Logical Memory (LM), and Verbal Paired Associates (VPA) subtests from Wechsler Memory Scale-Third Edition. Using Harrell’s step-down procedure for variable selection, models were developed in 359 adults who underwent TLR at Cleveland Clinic and validated in 290 adults at 1 of 5 epilepsy surgery centers in the United States or Canada. Results Twenty-nine percent of the development cohort and 26% of the validation cohort demonstrated significant decline on at least 1 verbal memory measure. Initial models had good-to-excellent predictive accuracy (calibration (c) statistic range = .77–.80) in identifying patients with memory decline; however, models slightly underestimated decline in the validation cohort. Model coefficients were updated using data from both cohorts to improve stability. The model for RAVLT included surgery side, baseline memory score, and hippocampal resection. The models for LM and VPA included surgery side, baseline score, and education. Updated model performance was good to excellent (RAVLT c = .81, LM c = .76, VPA c = .78). Model calibration was very good, indicating no systematic over- or under-estimation of risk. Conclusions Nomograms are provided in 2 easy-to-use formats to assist clinicians in estimating the probability of verbal memory decline in adults considering TLR for treatment of epilepsy.

Assessing Rectocele Depth and Its Association with Symptoms of Pelvic Floor Disorders Using Transperineal Ultrasound

Aim We investigated the clinical features of symptomatic rectoceles, as measured by transperineal ultrasound (TPUS), and evaluated the association between rectocele size and the clinical symptoms of pelvic floor disorders. Method This was a retrospective study using data obtained at a pelvic floor centre between August 2020 and January 2021. A total of 125 patients with defaecation disorders, such as constipation and faecal incontinence, were included. The preoperative questionnaire included the Cleveland Clinic Constipation Scoring System (CCCS, Wexner constipation score), Cleveland Clinic Incontinence Score (CCIS, Wexner incontinence score), faecal incontinence severity index (FISI), and faecal incontinence quality of life (FIQOL) scale. The size of the rectocele was measured on the trans-perineal 2D images. Patients were assigned to three groups based on rectocele size: no rectocele (<10 mm), ≥10 mm rectocele, and ≥15 mm rectocele. Results In the study population, 43 participants (34.4%) had no rectocele, 50 (40.0%) had ≥10 mm rectocele, and 32 (25.6%) had ≥15 mm rectocele. From the no rectocele to ≥15 mm rectocele group, the scores for the symptoms of incontinence and constipation increased, and the quality of life worsened. The CCIS (6.00±4.95 vs 8.62±5.77 vs 11.08±5.63, P = 0.004), FIQOL (13.72±4.19 vs 13.42±4.35 vs 10.38±3.88, P = 0.006), FISI (18.83±17.67 vs 25.15±17.34 vs 33.42±15.49, P = 0.010), and CCCS (7.50±6.26 vs 8.65±5.31 vs 13.11±5.90, P = 0.006), respectively. Conclusion The TPUS was a valuable method for the anatomical evaluation of symptomatic rectocele. The larger the size of the symptomatic rectocele measured using TPUS, the more severe the clinical symptoms.

Utilization of glucocorticoids among White and Black patients with systemic lupus erythematosus: Observations from the enrollment visit of a prospective registry

Background Black patients with systemic lupus erythematosus (SLE) face higher rates of morbidity and mortality compared to White patients. Long-term glucocorticoid use has been associated with worse health outcomes among patients with SLE. We sought to quantify chronic glucocorticoid use among Black and White patients with SLE within a prospective registry. Methods Using enrollment data from a registry at a large academic institution, we compared glucocorticoid use among Black and White patients with SLE. Multivariable logistic regression of race and glucocorticoid use was performed, adjusting for covariates exhibiting a bivariate association with glucocorticoids at significance level p < 0.10. Results 114 White participants (mean age 45; standard deviation (SD) 15) and 59 Black participants (mean age 42; SD 14) were analyzed. White participants had mean SLEDAI-2K score of 3.7 (SD 5.2). Black participants had mean SLEDAI-2K scores of 6.3 (SD 6.0). Among Black participants, 43 (72%) utilized glucocorticoids compared to White participants 39 (34%) (unadjusted odds ratio (OR) 5.17; 95% confidence interval (CI) 2.59–10.33). We did not observe differences between unadjusted hydroxychloroquine (OR 0.69; 95% CI 0.28–1.65) or conventional disease-modifying anti-rheumatic drug (cDMARD) (OR 1.07; 95% CI 0.57–2.01) utilization among Black and White participants. SLEDAI-2K, disability, recent hospitalization, and past or present hydroxychloroquine or cDMARD use were included in a logistic regression model. Adjusting for covariates, Black participants were more likely to be on glucocorticoids (adjusted OR 5.69; 95% CI 2.17–14.96); p = 0.0004). Conclusion Adjusting for disease activity and other medications, Black patients had more exposure to chronic glucocorticoids than White patients in the Cleveland Clinic SLE registry. These patients may face increased glucocorticoid-related morbidity, which could contribute significantly to long-term health outcomes and utilization of health care resources. Future research in larger, more diverse registries should be conducted to further characterize patterns of glucocorticoid use.

Abstract 12933: Myocardial Dysfunction After In-Hospital Cardiac Arrest in COVID-19 Patients

Introduction: Post resuscitation myocardial dysfunction (PRMD) is common after out-of-hospital cardiac arrest. While PRMD is a known cause of post-resuscitation circulatory failure, few studies have reported associations between PRMD and neurologic outcome or survival. Further, little is known about PRMD after in-hospital cardiac arrest (IHCA) nor on the incidence and prognosis of PRMD in COVID-19 IHCA. We sought to evaluate the incidence of PRMD in a multicenter cohort of resuscitated COVID-19 IHCA patients. Study Population and Methods: We included adult patients (≥18 y) admitted to multiple hospitals of Cleveland Clinic Health System. Patients who attained ROSC with an initial echocardiogram (EC) in the 72 hours post-arrest were included. Data were extracted from a data registry and electronic medical records. Results: From 03/2020-10/2020, 58 patients with COVID-19 had IHCA. ROSC was noted in 35 patients (60.3%), 27 (46.6%) were alive at 24 h and 13 patients (22.4%) survived to hospital discharge. Of the 35 patients who had ROSC, 14 patients (40%) had an EC within 72 h. The median age of this cohort was 67 y (IQR 47 - 73); 71% were male, and median BMI of 28 (IQR 27 - 34), and admission APACHE II score was 13 (IQR 11 - 19). One third of the patients (36%) were mechanically ventilated before arrest and 43% were on vasopressors. Initial arrest rhythms were: PEA/Asystole, 79%; and VF/VT, 21%. Most patients (93%) received manual chest compression with median CPR duration of 5 min (IQR 2 - 10). The median time of obtaining first EC post-ROSC in these 14 patients was 22 hours (IQR 6 - 62). 7/14 (50%) of the patient had systolic dysfunction on initial EC (6 had global dysfunction, 1 with regional wall motion abnormality, and 4/7 had combined LV and RV systolic dysfunction). 5/14 patients had a follow up EC with a median time of 43 days. 2/5 had normal initial EC and 3 out of these 5 patients who initially had PMRD showed complete recovery in their LV and RV systolic function. Conclusion: We report a case series of PRMD in COVID-19 patients who experienced IHCA. We found that PMRD is seen in half of the patients. Most patients with PMRD recovered to normal RV and LV function, consistent with prior studies of non-COVID-19 arrest EC.