Mookadam, Farouk

Mohave rattlesnakes ( Crotalus scutulatus ) are known to inhabit the deserts of southwestern United States, with their territory extending into southern Mexico. Envenomation can impart dramatic local and systemic effects on the body, ranging from local skin necrosis to neurotoxicity, depending on the protein complex in the venom. Kounis syndrome, or allergic angina, is an allergic response to a specific insult that results in myocardial injury often in the form of coronary artery vasospasm but can include myocardial infarction and coronary stent thrombosis. To our knowledge, there have not been any reports associating C scutulatus envenomation with Kounis syndrome. We describe a patient who developed Kounis syndrome presenting as an allergic myocardial infarction following envenomation by a Mohave rattlesnake. A second unique feature of this patient's envenomation is that he experienced respiratory failure secondary to right hemidiaphragmatic paralysis. Severe neurotoxicity from Mohave rattlesnake bites in humans has been reported rarely in the literature.

Heart failure with preserved ejection fraction (HFpEF) includes almost half of heart failure cases typified by a specific clinical syndrome. Despite diagnostic and management advances, HFpEF still presents a diagnostic challenge and a paucity of therapies specifically aimed at enhancing survival and improving quality of life is still lacking. This review elucidates the diagnostic complexity of HFpEF, highlighting the use of both subjective and objective criteria within algorithmic frameworks. It also examines the significant impact of comorbidities on the progression of HFpEF. Additionally, we explore the latest evidence on targeting these comorbidities therapeutically, although the benefits to mortality are still limited.

Introduction: Pectus excavatum (PE) is the most common anterior chest wall deformity with dorsal deviation into the thoracic cavity. Depending on the severity, PE can cause minor cosmetic problem to significant cardiac compression in severe cases. This compression most frequently affects right heart chambers causing symptoms such as dyspnea, palpitations, fatigue, exercise intolerance, and difficulty with keeping up with peers. Previously, we reported the change in these symptoms with positon associated with change in right heart hemodynamics. Further, we are comparing the changes in right heart hemodynamics with position in pectus patients to normal healthy adults. Methods: A prospective cohort of 40 pectus excavatum patients (mean Haller index: 5.4±2) undergoing evaluation at Mayo clinic underwent 2-D transthoracic echo (TTE) with Doppler assessment of Right Ventricular Outflow Tract (RVOT) Velocity Time Integral (VTI). A cohort of 8 healthy adults without chest wall abnormality who had clinically indicated echocardiogram was used as control (Table). Additional assessment of the RVOT VTI was performed in sitting position in either group. A two-sample t-test was performed to assess significance between cohorts. Results: There is a significant difference in RVOT VTI between case and control cohorts in both supine and sitting positions (p=0.03 & p=0.001 respectively). Also, there is a significant decrease in RVOT VTI from supine to sitting position in PE patients compared to healthy adults (Table). Conclusion: This is the 1 st prospective cohort study in PE patients vs healthy adults showing the feasibility and utility of dynamic echocardiography in assessing the right ventricular hemodynamics. This study demonstrates a significant decrease in right sided hemodynamic changes with change in position in patients with PE which might explain their symptoms.

ABSTRACT Background Randomized controlled trials have highlighted the importance of exercise training on the severity of obstructive sleep apnea (OSA). The primary objective of this meta-analysis was to analyze the data from these studies on the severity of OSA indices as measured by formal polysomnography. The secondary objective was to evaluate the effect of exercise on oxygen desaturation index, body mass index and several metabolic parameters associated with OSA. Methods Two independent reviewers and an experienced librarian searched MEDLINE, EMBASE, COCHRANE, and Scopus and SPORTDiscus databases from January 1, 2000, to October 21, 2021 to identify randomized controlled trials that evaluated the impact of exercise training on OSA severity. Pre-exercise and postexercise training data on the primary and secondary objectives were extracted. Results A total of 11 randomized controlled trials (533 study participants) were identified based on the inclusion criteria. The mean pre-exercise and postexercise reduction in apnea hypopnea index was −6.94 event per hour (95% confidence interval [CI]: −10.74 to −3.13, I2 = 84%). The mean changes in oxygen desaturation index and body mass index were −5.32 events per hour (95% CI: −9.65 to −0.99, I2 = 73%) and −1.21 kg·m−2 (95% CI: −1.80 to −0.62, I2 = 49%) respectively. Conclusion In adult patients with OSA, exercise training was associated with statistically significant reduction in OSA severity.

Background: Pectus excavatum (PE) deformity involves posterior depression of the sternum and adjacent costal cartilages. The relationship of CT/MRI chest cardiac compression indices used as indications for surgical repair of PE with echocardiographic findings and with improvement in cardiac chamber compression and function post PE repair is unknown. Methods: We evaluated right atrial (RA) size, tricuspid annulus (TA size, right ventricular (RV) outflow tract size as well as RV 2D strain on intra-operative trans-esophageal echocardiography (TEE) immediately pre and post surgical PE repair. Inspiratory and expiratory Haller Index (HI) and cardiac compression indices (CCI) were measured on pre op CT/MR scans (Figure). Offline measurement of chamber dimensions on TEE images was performed and Speckle tracking strain measurements were made using Syngo US Workplace software (Siemens). P<0.05 was considered significant. Results: 60 patients, 73% male, 27% female, age 33.6±10.3 yrs underwent PE repair following CT/MRI from 2010-2014 (Figure). There was a strong correlation between expiratory CT/MRI chest AP diameter and pre-op RA size (panel A). Pre op RA and TA compression on TEE inversely correlated with pre op RV global longitudinal strain rate(RVGLSR) (panels B & C). CCI predicted improvement in RA size post PE repair (panels D & E). In addition pre op RA size on TEE correlated with improvement in RVGLSR post PE repair surgery (panel F). Conclusion: In patients with PE deformity, pre surgical CCI correlated with right-sided cardiac chamber compression on pre op TEE. Severity of chest and cardiac compression also predicted magnitude of improvement in right-sided chamber size and RV longitudinal deformation post PE repair. Our findings provide insight regarding the beneficial effects of PE surgery on right heart chamber compression and improvement in RV function and the important role of intraoperative TEE for patients undergoing PE repair surgery.

Introduction: Ischemic stroke (IS) causes substantial morbidity and mortality in patients undergoing percutaneous coronary intervention (PCI) with a 5 yr incidence ~ 3%. We sought the test the accuracy of Machine learning (ML) algorithms in predicting IS in patients undergoing PCI. Methods: Mayo Clinic CathPCI registry data were retrospectively analyzed from Jan 2003 - June 2018 including 21,872 patients who underwent PCI. The cohort was randomly divided into a training sample (75%, n=16404) and a unique test sample (25%, n=5468) prior to model generation. The risk prediction model was generated utilizing a random forest algorithm (RF model) on 188 unique variables to predict the risk of IS at 6-month, 1, 2, and 5-year post PCI. Conventional risk factors for stroke were used for logistic regression. The receiver operating characteristic (ROC) curve and area under the curve for the RF and logistic regression models were compared for the test cohort. Results: The mean age was 66.9 ± 12.4 years, and 71% were male. Patient demographics and outcomes are shown in Table 1 . The ROC area under the curve for the RF model was superior compared to the logistic regression model in predicting IS at 6 months, 1,2 and 5 yrs for the test cohort ( Figure 1 .) Conclusions: The RF model accurately predicts short and long term risk of IS and outperforms logistic regression analysis in patients undergoing PCI.

Background: Identifying patients at a high risk of mortality post percutaneous coronary intervention (PCI) is of vital clinical importance. We investigated the utility of machine learning algorithms to predict short and intermediate-term risk of all-cause mortality in patients undergoing PCI. Methods: Patient-level demographics, clinical, electrocardiographic ,echocardiographic and angiographic data from January 2006 to December 2017 were extracted from the Mayo Clinic CathPCI registry and clinical records. For patients with multiple PCI events, data collected at the time of the index PCI was used for analysis. Patients who underwent bailout coronary artery bypass graft surgery (CABG) prior to discharge were excluded. 306 variables were incorporated into random forest machine learning model (RF) to predict all-cause mortality at 6 months and 1 year after PCI. Ten-fold cross-validation repeated five times was used to optimize the hyperparameters and estimate its external performance. The National Cardiovascular Data Registry (NCDR) based logistic regression model was used for comparison. The area under receiver operator characteristic curves (AUC) was calculated to assess the ability of the models to predict all-cause mortality. Results: A total of 17356 unique patients were included for the final analysis after excluding 165 patients who underwent CABG surgery during the index hospitalization. The mean age was 66.9 ± 12.5 years;71% were male. Indications for PCI were ST-elevation myocardial infarction (9.4%), non-ST elevation myocardial infarction (12.9%), unstable angina (17.7%), and stable angina (52.8%) in the cohort. In-hospital, 6-month & 1 year mortality rates were 1.9%,4.2% & 5.8% respectively. The RF model was superior to the NCDR model in predicting inhospital, 6-month, 1 year mortality (p<0.0001) ( Figure 1 ). Conclusion: Machine learning is superior to NCDR model in predicting short and intermediate risk of all-cause mortality post PCI.