Citations

Background: The outcomes of leadless pacemaker (LP) implantation after transvenous lead removal (TLR) of infected cardiac implantable electronic devices (CIED) are not well-established. Objective: This study sought to describe the outcomes of LP implantation following TLR of infected CIED. Method: We conducted a literature search using PubMed and Embase for a combination of term including leadless pacemaker implantation, transvenous lead extraction, transvenous lead removal , transvenous lead explant , infected cardiac implantable electronic device . The inclusion criterion was LP implantation after TLR of infected CIED. The exclusion criterion was TLR for non-infectious reason. Study end-points were procedural complications and LP infection. Result: Of 132 publications reviewed, 13 studies with a total of 253 patients (74 ± 14 years of age, 69% males) were included. Amongst, 56.8% had systemic CIED infection and 43.2% had isolated pocket infection. Staphylococcus Aureus was the most common causative organism in 33% of the reported patients. Of 253 patients included, 105 patients (41.5%) underwent concomitant LP implantation during TLR procedure, and 36 patients (14.2%) had transvenous pacing as a bridge from TLR to LP implantation. During the LP implantation, 1 patient (0.4%) had an intra-procedural complication requiring sternotomy. Post-LP implantation, 2 patients (0.8%) developed groin hematoma, 2 patients (0.8%) developed femoral arteriovenous fistula, and 1 patient (0.4%) developed pericardial effusion requiring pericardiocentesis. During a mean follow-up of 11.3 ±10.6 months, 3 patients (1.2%) developed pacemaker syndrome, 1 patient (0.4%) developed acute on chronic heart failure exacerbation, and only 1 patient (0.4%) developed LP-related infection requiring LP retrieval. Conclusion: This study suggests that LP implant is feasible and safe post-removal of infected CIED with cumulative adverse events at 4% and a reinfection rate of 0.4%.

Introduction: Incident cardiac arrhythmias are common in hospitalized COVID-19 patients, but the impact of a second incident cardiac arrhythmia during hospitalization on clinical outcomes remain unclear. Hypothesis: The aim of this study was to assess the frequency and prognostic implications of a second incident arrhythmia in hospitalized COVID-19 patients over the pandemic course till vaccine availability. Methods: The multicenter COVID-RHYTHM Registry enrolled hospitalized COVID-19 patients from 3/8/2020 to 1/24/2021. Cardiac arrhythmia included documented atrial fibrillation (AF), atrial flutter (AFL), ventricular tachycardia (VT), severe sinus bradycardia (<40 bpm) or AV block. Outcomes were compared between patients with single vs. more than one incident arrhythmias adjusting for baseline variables. Results: Of 6299 hospitalized COVID-19 patients, 4398 had an had an incident cardiac arrhythmia during hospitalization, of which 822 (19%) had a second incident arrhythmia. Those with >1 incident arrhythmia had a higher baseline prevalence of heart failure, chronic kidney disease, coronary artery disease and sleep apnea (Table). Those with >1 incident arrhythmia had higher in-hospital mortality, need for ICU admission and need for rehab upon discharge. Length of stay was similar between the groups. Conclusions: In hospitalized COVID-19 patients with incident cardiac arrhythmias, a second incident arrhythmia during hospitalization was seen in 19%. Having >1 incident arrhythmia was associated with increased need for ICU admission and reduced survival.

Background: While cardiac involvement in sarcoidosis could be significant, data assessing geographical disparities in cardiovascular deaths (CVDs) among patients with sarcoidosis are limited. Objective: This study aims to determine the mortality attributed to CVDs with comorbid sarcoidosis in different geographic locations in the United States. Methods: We queried the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research database and performed serial cross-sectional analyses of national death certificate data for CVDs with comorbid sarcoidosis among patients aged 25 and above. Diseases of the circulatory system (ICD-10 I00-I99) were listed as the underlying cause of death, and sarcoidosis (ICD-10 D86) as contributing cause of death. We calculated age-adjusted mortality rates (AAMRs) per 1,000,000 individuals and compared the mortality among census regions and states. Results: In the 22-year study period, 5,630 CVDs with comorbid sarcoidosis in the United States were identified between 1999 and 2020. The South region had the highest AAMRs for CVDs with comorbid sarcoidosis (1.32 [95% CI, 1.26-1.37] per 1,000,000 individuals), followed by Northeast region (1.25 [95% CI, 1.18-1.32] per 1,000,000 individuals), Midwest region (1.24 [95% CI, 1.17-1.30] per 1,000,000 individuals), and West Region (0.92 [95% CI, 0.86-0.98] per 1,000,000 individuals). The AAMRs for CVDs with comorbid sarcoidosis were between 0.57 [95% CI, 0.43-0.75] per 1,000,000 individuals and 1.96 [95% CI, 1.73-2.19] per 1,000,000 individuals throughout the States, except Maryland and the District of Columbia, which recorded 2.79 [95% CI, 2.44-3.14] and 6.01 [95% CI, 4.44-7.94], respectively. Conclusion: The South region, particularly Maryland recorded the highest CVDs in sarcoidosis. Geographical disparities observed in CVDs with comorbid sarcoidosis highlight the need to improve public health measures at state-level.

Background: Sarcoidosis is a multisystem inflammatory disease that could result in debilitating cardiac manifestations. Despites, data on the cardiovascular deaths (CVDs) among patients with sarcoidosis are limited. Objective: This study sought to determine the longitudinal trends in mortality attributed to CVDs with comorbid sarcoidosis by age, sex, and race in the United States. Methods: We queried the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research database and performed serial cross-sectional analyses of national death certificate data for CVDs with comorbid sarcoidosis among patients aged 25 and above. Diseases of the circulatory system (ICD-10 I00-I99) were listed as the underlying cause of death, and sarcoidosis (ICD-10 D86) as contributing cause of death. We calculated age-adjusted mortality rates (AAMRs) per 1,000,000 individuals and determined the trends over time by estimating the annual percent change using the Joinpoint Regression Program. Results: In the 22-year study period, 5,630 CVDs with comorbid sarcoidosis in the United States were identified between 1999 and 2020. The AAMRs from CVDs with comorbid sarcoidosis increased from 1.03 (95% CI, 0.88-1.17) in 1999 to 1.38 (95% CI, 1.24-1.52) in 2020. Overall, women recorded a higher AAMRs compared to men (1.25 [95% CI, 1.21-1.30] vs. 1.10 [95% CI, 1.06-1.15]). Black individuals had higher AAMRs than White individuals (5.17 [95% CI, 4.97-5.37] vs. 0.68 [95% CI, 0.66-0.71]). A higher percentage of CVDs with comorbid sarcoidosis was seen in the age groups of 55-64 in men (24.68%) and 65-74 in women (22.62%). Conclusion: The CVDs in sarcoidosis have increased over the last two decades, with disparities seen in women and Black individuals. Most CVDs with comorbid sarcoidosis occurred at a younger age compared to general population. This highlights the importance of early screening for cardiovascular diseases in sarcoidosis individuals.

Introduction: The effect of obesity on physiologic aging has not been completely established. We previously developed an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm that predicts age and determines that the difference between AI-ECG age and chronological age (Age-Gap) may reflect accelerated aging, as it is associated with increased total and cardiovascular (CV) mortality. Hypothesis: Obesity is associated with an increased Age-Gap reflecting morbidity and accelerated aging. Methods: We included adults undergoing a wellness evaluation including, body fat percentage (BF%) determination by air displacement plethysmography (Bod-Pod®) and a 12-lead ECG within 2 years. We excluded those with coronary artery disease, congestive heart failure, stroke or being underweight defined as having a BMI<18.5 kg/m2. Logistic regression models tested the association between obesity by BMI (≥30 kg/m2) or BF% quartiles (≥35% for men and ≥25 in women) and being older by AI-ECG. Results: We included 1295 subjects (70% women), mean chronological age 46.7 ± 13.1 years. Mean Age-gap positive difference compared to those with BMI<25 was 1.39, 2.06 and 2.83 for those with BMI 25-29.9, 30-34.9, and >35 respectively (p<0.05). In the BF% group, Age-gap difference compared to those in the 1st quartile was 0.008, 0.37 and 1.52 for those in the 2nd, 3rd, and 4th quartile (p<0.05). Those>3 years older by ECG were more likely to have obesity by BMI and BF%, see figure. Conclusions: Obesity, either by BMI or BF%, is associated with increased physiologic age as measured by AI-ECG, highlighting the importance of obesity as a health threat.

Clinical prediction models for spine surgery applications are on the rise, with an increasing reliance on machine learning (ML) and deep learning (DL). Many of the predicted outcomes are uncommon; therefore, to ensure the models’ effectiveness in clinical practice it is crucial to properly evaluate them. This systematic review aims to identify and evaluate current research-based ML and DL models applied for spine surgery, specifically those predicting binary outcomes with a focus on their evaluation metrics. Overall, 60 papers were included, and the findings were reported according to the PRISMA guidelines. A total of 13 papers focused on lengths of stay (LOS), 12 on readmissions, 12 on non-home discharge, 6 on mortality, and 5 on reoperations. The target outcomes exhibited data imbalances ranging from 0.44% to 42.4%. A total of 59 papers reported the model’s area under the receiver operating characteristic (AUROC), 28 mentioned accuracies, 33 provided sensitivity, 29 discussed specificity, 28 addressed positive predictive value (PPV), 24 included the negative predictive value (NPV), 25 indicated the Brier score with 10 providing a null model Brier, and 8 detailed the F1 score. Additionally, data visualization varied among the included papers. This review discusses the use of appropriate evaluation schemes in ML and identifies several common errors and potential bias sources in the literature. Embracing these recommendations as the field advances may facilitate the integration of reliable and effective ML models in clinical settings.

The NCCN Guidelines for Cervical Cancer provide recommendations for all aspects of management for cervical cancer, including the diagnostic workup, staging, pathology, and treatment. The guidelines also include details on histopathologic classification of cervical cancer regarding diagnostic features, molecular profiles, and clinical outcomes. The treatment landscape of advanced cervical cancer is evolving constantly. These NCCN Guidelines Insights provide a summary of recent updates regarding the systemic therapy recommendations for recurrent or metastatic disease.