Kalinoski-DuBose, Victoria

Diverticular disease is a major cause of hospitalizations, especially in the elderly. Although diverticulosis and its complications predominately affect the colon, the formation of diverticula in the small intestine, most commonly in the duodenum, is well characterized in the literature. Although small bowel diverticula are typically asymptomatic, and diagnosed incidentally, a complication of periampullary duodenal diverticulum is Lemmel syndrome. Lemmel syndrome is an extremely rare condition whereby periampullary duodenal diverticula, most commonly without diverticulitis, leads to obstruction of the common bile duct due to mass effect and associated complications including acute cholangitis and pancreatitis. Here, we present the first case, to our knowledge, of periampullary duodenal diverticulitis complicated by Lemmel syndrome with concomitant colonic diverticulitis with colovesical fistula. Our case and literature review emphasizes that Lemmel syndrome can present with or without suggestions of obstructive jaundice and can most often be managed conservatively if caught early, except in the setting of emergent complications.

Introduction: Recently, an artificial intelligence (AI) algorithm was validated for identifying ECG signatures of atrial fibrillation (AF) risk during normal sinus rhythm. Traditionally, socioeconomically disadvantaged populations are less likely to receive novel or guideline-recommended treatments, and have high chronic disease burden, including cardiovascular diseases. There have also been concerns about new technologies creating a digital divide, worsening existing health disparities. Hypothesis: An AI algorithm will detect AF risk unequally across patients with different levels of social determinants of health (SDOH). Methods: The initial prospective, non-randomized, interventional study leveraged EHR and digital technologies to prospectively enroll 1004 patients with a broad range of AI-ECG risks of AF, who received continuous cardiac rhythm monitoring for up to 30 days. The Area Deprivation Index (ADI) was used as a composite measure of SDOH which is comprised of indicators spanning four domains: income, education, employment, and house quality. 904 intervention patients linked to the ADI data were matched to 904 real-world control patients derived from eligible but unenrolled patients. Those with ADI under 33% were defined as having better SODH; and patients with ADI above 33% were defined as having worse SODH. Results: Median age was 74 years and 38% were women. After matching, the intervention and control arms were balanced in all baseline characteristics, including HF, HTN, diabetes, stroke, CAD and ADI. A hazard ratio of 3.11 (P<0.001) was computed when comparing intervention to control for primary AF diagnosis outcome. In patients with worse SDOH, the intervention increased AF detection from 2.6% to 8.8% (HR 3.63 [2.09, 6.32]); in the better SDOH, the intervention increased AF detection from 3.9% to 9.3% (2.41 [1.23, 4.74]). Conclusions: An AI-guided AF screening program increased the detection of AF in both patients with better or worse SDOH. The current study validates the use of AI in historically disadvantaged populations displaying the possibility for broad implementation with decreased possibility of perpetuating disparities.

Background The American College of Cardiology and American Heart Association periodically revise clinical practice guidelines. We evaluated changes in the evidence underlying guidelines published over a 10‐year period. Methods and Results Thirty‐five American College of Cardiology/American Heart Association guidelines were divided into 2 time periods: 2008 to 2012 and 2013 to 2017. Guidelines were categorized into the following topic areas: arrhythmias, prevention, acute and stable ischemia, heart failure, valvular heart disease, and vascular medicine. Changes in recommendations were assessed for each topic area. American College of Cardiology/American Heart Association designated class of recommendation as level I, II , or III (I represented “strongly recommended”) and levels of evidence ( LOE ) as A, C, or C (A represented “highest quality”). The median number of recommendations per each topic area was 281 (198–536, interquartile range) in 2008 to 2012 versus 247 (190–451.3, interquartile range) in 2013 to 2017. The median proportion of class of recommendation I was 49.3% and 44.4% in the 2 time periods, 38.0% and 44.5% for class of recommendation II , and 12.5% and 11.2% for class of recommendation III . Median proportions for LOE A were 15.7% and 14.1%, 41.0% and 52.8% for LOE B, and 46.9% and 32.5% for LOE C. The decrease in the proportion of LOE C was highest in heart failure (24.8%), valvular heart disease (22.3%), and arrhythmia (19.2%). An increase in the proportion of LOE B was observed for these same areas: 31.8%, 23.8%, and 19.2%, respectively. Conclusions There has been a decrease in American College of Cardiology/American Heart Association guidelines recommendations, driven by removal of recommendations based on lower quality of evidence, although there was no corresponding increase in the highest quality of evidence.