Citations

Abstract Background Atherosclerotic cardiovascular disease (ASCVD), of which coronary artery disease (CAD) is the primary manifestation, is the leading cause of death worldwide. The AHA/ACC Pooled Cohort Equation (PCE) facilitates risk stratification and initiation of primary prevention of ASCVD, however their performance is suboptimal. Purpose We develop an artificial intelligence-based electrocardiogram (ECG) analysis (AI-ECG) algorithm to detect different stages of CAD and assessed the value of AI-ECG over PCE to predict incident myocardial infarction (MI) and survival over 3-years. Methods Using electronic health record data from approximately 7 million patients seen at over 70 hospitals and clinics across 5 states in the USA, we created independent AI-ECG models to identify elevated coronary artery calcium (CAC) by computer tomography, the presence of obstructive CAD by stress test or angiography, and left ventricular regional akinesis by echocardiogram, presumed to represent prior MI. Deep structured data, AI-enabled natural language processing of unstructured data were used to ensure cohort, and physician review of labeling were used to ensure cohort accuracy. These models were ensembled into a single model that was used to assess the utility of AI-ECG for predicting new occurrence MI in PCE- and age-stratified cohorts of patient with no prior history of ASCVD, over a 3-year timeframe using Cox’s proportional hazards analysis. Results A total of 6,080 patients (15,192 ECGs) were labeled positive for CAC ≥ 300, 12,561 patients (18,915 ECGs) positive for obstructive CAD, and 10,767 patients (23,870 ECGs) positive for regional akinesis. AI-ECG for identifying elevated CACS, obstructive CAD, and regional akinesis achieved AUROCs of 0.86, 0.80, and 0.93, respectively. All AI-ECG models identified increased 3-year risk for MI and death in AI-ECG positive versus AI-ECG negative patients and subgroups with 2 or 3 positive results had stepwise increased risk (Figure A). In a 3-year survival analysis of all-comer patients, the hazard ratio for those that tested positive on 1, 2, or 3 versus 0 positive disease-specific models were 1.61 (1.53-1.69). 2.40 (2.27-2.55), 3.42 (3.21-3.65), respectively. Risk stratification was also observed in cohorts without prior ASCVD stratified by low and high PCE-derived 10-year ASCVD risk (Figure B) and in cohorts stratified by age, including under the age of 40. Conclusions AI-ECG has potential to address unmet need for accessible risk stratification in patients in whom PCE under, over, or insufficiently estimate ASCVD risk, and in whom risk assessment over periods of time shorter than 10 years is desired.

ABSTRACT The rapid pace of name changes of medically important fungi is creating challenges for clinical laboratories and clinicians involved in patient care. We describe two sources of name change which have different drivers, at the species versus the genus level. Some suggestions are made here to reduce the number of name changes. We urge taxonomists to provide diagnostic markers of taxonomic novelties. Given the instability of phylogenetic trees due to variable taxon sampling, we advocate to maintain genera at the largest possible size. Reporting of identified species in complexes or series should where possible comprise both the name of the overarching species and that of the molecular sibling, often cryptic species. Because the use of different names for the same species will be unavoidable for many years to come, an open access online database of the names of all medically important fungi, with proper nomenclatural designation and synonymy, is essential. We further recommend that while taxonomic discovery continues, the adaptation of new name changes by clinical laboratories and clinicians be reviewed routinely by a standing committee for validation and stability over time, with reference to an open access database, wherein reasons for changes are listed in a transparent way.

Abstract Disclosure: B. Clarke: Advisory Board Member; Self; Ascendis Pharma, Takeda, Entera-Bio, Extend-Bio, Amolyt. Consulting Fee; Self; Ascendis Pharma, Takeda, Entera-Bio, Extend-Bio, Amolyt. Grant Recipient; Self; Ascendis Pharma, Takeda. Research Investigator; Self; Ascendis Pharma, Takeda. Other; Self; Ascendis Pharma, Takeda, Entera-Bio, Extend-Bio, Amolyt. A.A. Khan: Advisory Board Member; Self; Amgen Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma, Takeda, Ultragenyx. Consulting Fee; Self; Amgen Inc, Alexion Pharmaceuticals, Inc., Amolyt, Ascendis Pharma, Ultragenyx. Grant Recipient; Self; Amolyt. Research Investigator; Self; Radius Health, Inc, Takeda, Ultragenyx, Amolyt, Ascendis Pharma, Chugai. Speaker; Self; Amgen Inc. Other; Self; Amgen Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma, Takeda, Ultragenyx. M.R. Rubin: Research Investigator; Self; Chugai Pharma. P.E. Schwarz: Stock Owner; Self; Novo Nordisk, Genmab. T.J. Vokes: Consulting Fee; Self; Takeda, Ascendis Pharma. Research Investigator; Self; Ascendis Pharma, Radius Health, Inc. D.M. Shoback: Research Investigator; Self; Bone Health Tech. C. Gagnon: Advisory Board Member; Self; Novo Nordisk. Grant Recipient; Self; Shire, Takeda, Ascendis Pharma. Research Investigator; Self; Novo Nordisk. Other; Self; Amgen Inc. A. Palermo: Consulting Fee; Self; Theramex, Bruno, Farmaceutici, Amgen Inc. Grant Recipient; Self; Amgen Inc. Research Investigator; Self; Amgen Inc, Shire, Ascendis Pharma. Speaker; Self; UCB, Amgen Inc. L.G. Abbott: Advisory Board Member; Self; Ascendis. Research Investigator; Self; Takeda, Shire, Ascendis Pharma. Speaker; Self; Abbott Laboratories, Clarus. Other; Self; Ascendis. L.C. Hofbauer: Advisory Board Member; Self; Amgen Inc, UCB. Other; Self; Amgen Inc, UCB. L. Kohlmeier: Advisory Board Member; Self; Alexion Pharmaceuticals, Inc., Ascendis Pharma. Research Investigator; Self; Ascendis Pharma. Speaker; Self; Amgen Inc, Radius Health, Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma. Other; Self; Amgen Inc, Radius Health, Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma, MediMaps. F. Cetani: None. S. Phil: Employee; Self; Ascendis Pharma. X. An: Employee; Self; Ascendis Pharma. A.R. Smith: Employee; Self; Ascendis Pharma. B. Lai: Employee; Self; Ascendis Pharma. J. Le: Employee; Self; Ascendis Pharma. J. Ukena: Employee; Self; Ascendis Pharma. C. Sibley: Employee; Self; Ascendis Pharma. A. Shu: Employee; Self; Ascendis Pharma. L. Rejnmark: Advisory Board Member; Self; Takeda, Amolyt. Research Investigator; Self; Takeda, Kyowa Kirin International, Ascendis Pharma, Calcilytix Therapeutics. Other; Self; Calcilytix Therapeutics. Objective: Evaluate the long-term efficacy and safety of TransCon PTH as a potential hormone replacement therapy for hypoparathyroidism. Methods: PaTHway is a phase 3 trial of TransCon PTH with a placebo (PBO)-controlled 26-week blinded period and a 156-week open-label extension (OLE) period. Results through Week 52 (26 weeks blinded + 26 weeks OLE) are reported. Three-component efficacy endpoint: normal serum calcium (8.3-10.6 mg/dL) and independence from conventional therapy (≤600 mg/day of elemental calcium and no active vitamin D). Other endpoints: Hypoparathyroidism Patient Experience Scale (HPES); 36-Item Short Form Survey (SF-36); bone mineral density (BMD) by dual-energy X-ray absorptiometry (DXA); bone turnover markers (BTM) procollagen type 1 N-terminal propeptide (P1NP) and C-terminal telopeptide of type 1 collagen (CTx). Safety was assessed by 24-hour urine calcium and reported treatment-emergent adverse events (TEAEs). Results: Of the 82 participants given study drug, 79 completed blinded treatment and entered the OLE, and 78 (59 TransCon PTH/TransCon PTH, 19 PBO/TransCon PTH) completed Week 52. Overall at Week 52, 81% (63/78) met the efficacy endpoint, 95% (74/78) achieved independence from conventional therapy, and none required active vitamin D. Mean albumin-adjusted serum calcium was within the normal range at all time points in the OLE (8.9 mg/dL at Week 52). Mean Week 52 HPES scores showed sustained improvement from baseline in disease-related symptoms and the impact of hypoparathyroidism on physical functioning and daily life. Mean Week 52 SF-36 physical functioning scores also remained above baseline. In the TransCon PTH/TransCon PTH group, mean BMD corrected Z-scores trended toward norms from baseline to Weeks 26 and 52:1.5, 0.7, 0.7 at the lumbar spine (L1-L4); 0.8, 0.3, 0.3 at femoral neck; 0.9, 0.5, 0.4 at total hip; and 0.3, 0.3, 0.3 at distal 1/3 radius; P1NP peaked at Week 26 and CTx at Week 12. Smaller incremental changes were seen in BMD and BTM from Weeks 26 to 52 than baseline to Week 26. In the PBO/TransCon PTH group, changes in BMD and BTM from Week 26 to 52 resembled those in the TransCon PTH/TransCon PTH group from baseline to Week 26. Mean 24-hour urine calcium excretion decreased from 376 mg/day at baseline to 195 mg/day at Week 52. Most TEAEs were mild or moderate and none led to discontinuation of the study drug or trial. Conclusions: At Week 52 of the PaTHway trial, TransCon PTH showed a similar sustained efficacy, safety, and tolerability profile to that of Week 26, demonstrating its potential as a hormone replacement therapy for adults with hypoparathyroidism. Indices of skeletal dynamics trended toward age- and sex-matched norms in the TransCon/TransCon PTH group. TransCon PTH treatment in the PBO/TransCon PTH group showed rapid improvement in all outcomes in the first 26 weeks of the OLE consistent with the pattern in the TransCon PTH group during the blinded period. Presentation: Saturday, June 17, 2023

Abstract Background Carbapenem-resistant Acinetobacter baumannii (CRAb) is 1 of the most problematic antimicrobial-resistant bacteria. We sought to elucidate the international epidemiology and clinical impact of CRAb. Methods In a prospective observational cohort study, 842 hospitalized patients with a clinical CRAb culture were enrolled at 46 hospitals in five global regions between 2017 and 2019. The primary outcome was all-cause mortality at 30 days from the index culture. The strains underwent whole-genome analysis. Results Of 842 cases, 536 (64%) represented infection. By 30 days, 128 (24%) of the infected patients died, ranging from 1 (6%) of 18 in Australia-Singapore to 54 (25%) of 216 in the United States and 24 (49%) of 49 in South-Central America, whereas 42 (14%) of non-infected patients died. Bacteremia was associated with a higher risk of death compared with other types of infection (40 [42%] of 96 vs 88 [20%] of 440). In a multivariable logistic regression analysis, bloodstream infection and higher age-adjusted Charlson comorbidity index were independently associated with 30-day mortality. Clonal group 2 (CG2) strains predominated except in South-Central America, ranging from 216 (59%) of 369 in the United States to 282 (97%) of 291 in China. Acquired carbapenemase genes were carried by 769 (91%) of the 842 isolates. CG2 strains were significantly associated with higher levels of meropenem resistance, yet non-CG2 cases were over-represented among the deaths compared with CG2 cases. Conclusions CRAb infection types and clinical outcomes differed significantly across regions. Although CG2 strains remained predominant, non-CG2 strains were associated with higher mortality. Clinical Trials Registration. NCT03646227.

Purpose We reviewed all 64 articles ever published by The Congenital Heart Surgeons’ Society (CHSS) Data Center to estimate the academic impact of these peer-reviewed articles. Materials and Methods The Congenital Heart Surgeons’ Society has performed research based on 12 Diagnostic Inception Cohorts. The first cohort (Transposition) began enrolling patients on January 1, 1985. We queried PubMed to determine the number of publications that referenced each of the 64 journal articles generated by the datasets of the 12 Diagnostic Inception Cohorts that comprise the CHSS Database. Descriptive summaries of the data were tabulated using mean with standard deviation and median with range. Results Sixty-four peer-reviewed papers have been published based on the CHSS Database. Fifty-nine peer-reviewed articles have been published based on the 12 Diagnostic Inception Cohorts, and five additional articles have been published based on Data Science. Excluding the recently established Diagnostic Inception Cohort for patients with Ebstein malformation of tricuspid valve, the number of papers published per cohort ranged from 1 for coarctation to 11 for transposition of the great arteries. The 11 articles generated from the CHSS Transposition Cohort were referenced by a total of 111 articles (median number of references per journal article = 9 [range = 0-22, mean = 10.1]). Overall, individual articles were cited by an average of 11 (mean), and a maximum of 41 PubMed-listed publications. Overall, these 64 peer-reviewed articles based on the CHSS Database were cited 692 times in PubMed-listed publications. The first CHSS peer-reviewed article was published in 1987, and during the 35 years from 1987 to 2022, inclusive, the annual number of CHSS publications has ranged from 0 to 7, with a mean of 1.8 publications per year (median = 1, mode = 1). Conclusion Congenital Heart Surgeons’ Society studies are widely referenced in the pediatric cardiac surgical literature, with over 10 citations per published article. These cohorts provide unique information unavailable in other sources of data. A tool to access this analysis is available at: [ https://data-center.chss.org/multimedia/files/2022/CAI.pdf ].

Purpose To develop a machine learning model capable of identifying subscapularis tears before surgery based on imaging and physical examination findings. Methods Between 2010 and 2020, 202 consecutive shoulders underwent arthroscopic rotator cuff repair by a single surgeon. Patient demographics, physical examination findings (including range of motion, weakness with internal rotation, lift/push‐off test, belly press test, and bear hug test), and imaging (including direct and indirect signs of tearing, biceps status, fatty atrophy, cystic changes, and other similar findings) were included for model creation. Results Sixty percent of the shoulders had partial or full thickness tears of the subscapularis verified during surgery (83% of these were upper third). Using only preoperative imaging‐related parameters, the XGBoost model demonstrated excellent performance at predicting subscapularis tears (c‐statistic, 0.84; accuracy, 0.85; F1 score, 0.87). The top 5 features included direct signs related to the presence of tearing as evidenced on magnetic resonance imaging (MRI) (changes in tendon morphology and signal), as well as the quality of the MRI and biceps pathology. Conclusions In this study, machine learning was successful in predicting subscapularis tears by MRI alone in 85% of patients, and this accuracy did not decrease by isolating the model to the top features. The top five features included direct signs related to the presence of tearing as evidenced on MRI (changes in tendon morphology and signal), as well as the quality of the MRI and biceps pathology. Last, in advanced modeling, the addition of physical examination or patient characteristics did not make a significant difference in the predictive ability of this model. Level of Evidence Level III, diagnostic case‐control study.

Abstract Previous studies implicated protein arginine methyltransferase 5 (PRMT5) as a synthetic lethal target for MTAP-deleted (MTAP del) cancers; however, the pharmacologic characterization of small-molecule inhibitors that recapitulate the synthetic lethal phenotype has not been described. MRTX1719 selectively inhibited PRMT5 in the presence of MTA, which is elevated in MTAP del cancers, and inhibited PRMT5-dependent activity and cell viability with >70-fold selecti­vity in HCT116 MTAP del compared with HCT116 MTAP wild-type (WT) cells. MRTX1719 demonstrated dose-dependent antitumor activity and inhibition of PRMT5-dependent SDMA modification in MTAP del tumors. In contrast, MRTX1719 demonstrated minimal effects on SDMA and viability in MTAP WT tumor xenografts or hematopoietic cells. MRTX1719 demonstrated marked antitumor activity across a panel of xenograft models at well-tolerated doses. Early signs of clinical activity were observed including objective responses in patients with MTAP del melanoma, gallbladder adenocarcinoma, mesothelioma, non–small cell lung cancer, and malignant peripheral nerve sheath tumors from the phase I/II study. Significance: PRMT5 was identified as a synthetic lethal target for MTAP del cancers; however, previous PRMT5 inhibitors do not selectively target this genotype. The differentiated binding mode of MRTX1719 leverages the elevated MTA in MTAP del cancers and represents a promising therapy for the ∼10% of patients with cancer with this biomarker. See related commentary by Mulvaney, p. 2310. This article is featured in Selected Articles from This Issue, p. 2293