Faculty Bibliography
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department:Medicine. General Internal Medicine
recentyears:2
school:SOM
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Clinical and genomic signatures of SARS-CoV-2 Delta breakthrough infections in New York
BACKGROUND:In 2021, Delta became the predominant SARS-CoV-2 variant worldwide. While vaccines have effectively prevented COVID-19 hospitalization and death, vaccine breakthrough infections increasingly occurred. The precise role of clinical and genomic determinants in Delta infections is not known, and whether they contributed to increased rates of breakthrough infections compared to unvaccinated controls. METHODS:We studied SARS-CoV-2 variant distribution, dynamics, and adaptive selection over time in relation to vaccine status, phylogenetic relatedness of viruses, full genome mutation profiles, and associated clinical and demographic parameters. FINDINGS/RESULTS:We show a steep and near-complete replacement of circulating variants with Delta between May and August 2021 in metropolitan New York. We observed an increase of the Delta sublineage AY.25 (14% in vaccinated, 7% in unvaccinated), its spike mutation S112L, and AY.44 (8% in vaccinated, 2% in unvaccinated) with its nsp12 mutation F192V in breakthroughs. Delta infections were associated with younger age and lower hospitalization rates than Alpha. Delta breakthrough infections increased significantly with time since vaccination, and, after adjusting for confounders, they rose at similar rates as in unvaccinated individuals. INTERPRETATION/CONCLUSIONS:We observed a modest adaptation of Delta genomes in breakthrough infections in New York, suggesting an improved genomic framework to support Delta's epidemic growth in times of waning vaccine protection despite limited impact on vaccine escape. FUNDING/BACKGROUND:The study was supported by NYU institutional funds. The NYULH Genome Technology Center is partially supported by the Cancer Center Support Grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center.
PMCID:9323230
PMID: 35906172
ISSN: 2352-3964
CID: 5277042
[S.l.] : KevinMD.com, 2022
Getting an appointment with primary care is the Achilles’ heel of medicine
(Website)CID: 5284682
Journal of cardiovascular computed tomography. 2022:Conference:(Society).DOI: 10.1016/j.jcct.2022.06.031
426 Impact Of Visceral Abdominal Tissue On Coronary Artery Disease As Defined By Quantitative Computed Tomographic Angiography [Meeting Abstract]
Introduction: Obesity has long been associated with all-cause mortality and cardiovascular disease (CVD). Visceral abdominal tissue (VAT) has been proposed as an important CVD risk stratification metric given its independent correlation with myocardial infarction and stroke. This study aims to clarify the relationship between the presence and severity of VAT with the presence and severity of coronary artery plaque as defined by total plaque volume, calcified plaque volume, non-calcified plaque volume, and high risk low-density non-calcified plaque using quantitative coronary computed tomography atherosclerosis imaging (AI-QCT).
Method(s): CCTA was performed using single or dual source CT scanners of >64-detector rows. Coronary atherosclerosis evaluation by CCTA (AI-QCT) was performed. The AI-based approach to CCTA interpretation in this study was performed using an FDA-cleared software service (Cleerly Lab, Cleerly, New York, NY) that performs automated analysis of CCTA using a series of validated convolutional neural network models (including VGG19 network, 3D U-Net, and VGG Network Variant) for image quality assessment, coronary segmentation and labeling, lumen wall evaluation and vessel contour determination and plaque characterization. Coronary segments with a diameter >1.5 mm were included in the analysis using the modified 18-segment SCCT model. Plaque volume was categorized using Hounsfield unit (HU) ranges, with LD-NCP defined as plaques <30 HU, NCP defined as HU between -30 and +350, and CP defined as >350 HU12,13.
Result(s): The study cohort was comprised of 145 patients, 56.1 +/- 8.5 years, 84.0% male. Overall, 3.5% had a history of diabetes, 19% hypertension, 38% dyslipidemia, 8% current smokers, and 34% had a family history of CAD. At the time of the examination, 37% were taking statins, 21% anti-hypertension medications, and 11% non-stating lipid lowering medication. There was a stepwise progression of the median coronary plaque volume for each quartile of visceral fat including TPV (Q1: 19.8, Q2: 48.1, Q3: 86.4, and Q4: 136.6 mm3 (P=0.0098)), NCP (Q1: 15.7, Q2: 35.4, Q3: 86.4, and Q4: 136.6 mm3 (P=0.0032)) and LD-NCP (Q1: 0.6, Q2: 0.81, Q3: 2.0, and Q4: 5.0 mm3 (P<0.0001)). There was also a stepwise progression of the median maximum diameter stenosis for each quartile of visceral fat (Q1: 18.0, Q2: 27.0, Q3: 27.5, and Q4: 29.5% (P=0.0414)) as well as medial coronary plaque length (Q1: 12.8, Q2: 19.5, Q3: 26.4, and Q4: 27.5mm (P=0.0077))
Conclusion(s): Our findings represent the first demonstration of a stepwise progression with regards to visceral abdominal tissue and total plaque volume, non-calcified plaque volume, and low density non-calcified plaque volume. This relationship is particularly striking with regards to the progression and severity of VAT and the presence and amount of low density non-calcified plaque, which is known to be high risk for cardiovascular events.
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Method(s): CCTA was performed using single or dual source CT scanners of >64-detector rows. Coronary atherosclerosis evaluation by CCTA (AI-QCT) was performed. The AI-based approach to CCTA interpretation in this study was performed using an FDA-cleared software service (Cleerly Lab, Cleerly, New York, NY) that performs automated analysis of CCTA using a series of validated convolutional neural network models (including VGG19 network, 3D U-Net, and VGG Network Variant) for image quality assessment, coronary segmentation and labeling, lumen wall evaluation and vessel contour determination and plaque characterization. Coronary segments with a diameter >1.5 mm were included in the analysis using the modified 18-segment SCCT model. Plaque volume was categorized using Hounsfield unit (HU) ranges, with LD-NCP defined as plaques <30 HU, NCP defined as HU between -30 and +350, and CP defined as >350 HU12,13.
Result(s): The study cohort was comprised of 145 patients, 56.1 +/- 8.5 years, 84.0% male. Overall, 3.5% had a history of diabetes, 19% hypertension, 38% dyslipidemia, 8% current smokers, and 34% had a family history of CAD. At the time of the examination, 37% were taking statins, 21% anti-hypertension medications, and 11% non-stating lipid lowering medication. There was a stepwise progression of the median coronary plaque volume for each quartile of visceral fat including TPV (Q1: 19.8, Q2: 48.1, Q3: 86.4, and Q4: 136.6 mm3 (P=0.0098)), NCP (Q1: 15.7, Q2: 35.4, Q3: 86.4, and Q4: 136.6 mm3 (P=0.0032)) and LD-NCP (Q1: 0.6, Q2: 0.81, Q3: 2.0, and Q4: 5.0 mm3 (P<0.0001)). There was also a stepwise progression of the median maximum diameter stenosis for each quartile of visceral fat (Q1: 18.0, Q2: 27.0, Q3: 27.5, and Q4: 29.5% (P=0.0414)) as well as medial coronary plaque length (Q1: 12.8, Q2: 19.5, Q3: 26.4, and Q4: 27.5mm (P=0.0077))
Conclusion(s): Our findings represent the first demonstration of a stepwise progression with regards to visceral abdominal tissue and total plaque volume, non-calcified plaque volume, and low density non-calcified plaque volume. This relationship is particularly striking with regards to the progression and severity of VAT and the presence and amount of low density non-calcified plaque, which is known to be high risk for cardiovascular events.
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EMBASE:2019317971
ISSN: 1876-861x
CID: 5291842
Childcare Stress, Burnout, and Intent to Reduce Hours or Leave the Job During the COVID-19 Pandemic Among US Health Care Workers
IMPORTANCE:Childcare stress (CCS) is high during the COVID-19 pandemic because of remote learning and fear of illness transmission in health care workers (HCWs). Associations between CCS and burnout, intent to reduce (ITR) hours, and intent to leave (ITL) are not known. OBJECTIVE:To determine associations between CCS, anxiety and depression, burnout, ITR in 1 year, and ITL in 2 years. DESIGN, SETTING, AND PARTICIPANTS:This survey study, Coping with COVID, a brief work-life and wellness survey of US HCWs, was conducted between April and December 2020, assessing CCS, burnout, anxiety, depression, workload, and work intentions. The survey was distributed to clinicians and staff in participating health care organizations with more than 100 physicians. Data were analyzed from October 2021 to May 2022. MAIN OUTCOMES AND MEASURES:The survey asked, "due to…COVID-19, I am experiencing concerns about childcare," and the presence of CCS was considered as a score of 3 or 4 on a scale from 1, not at all, to 4, a great extent. The survey also asked about fear of exposure or transmission, anxiety, depression, workload, and single-item measures of burnout, ITR, and ITL. RESULTS:In 208 organizations, 58 408 HCWs (15 766 physicians [26.9%], 11 409 nurses [19.5%], 39 218 women [67.1%], and 33 817 White participants [57.9%]) responded with a median organizational response rate of 32%. CCS was present in 21% (12 197 respondents) of HCWs. CCS was more frequent among racial and ethnic minority individuals and those not identifying race or ethnicity vs White respondents (5028 respondents [25.2%] vs 6356 respondents [18.8%]; P < .001; proportional difference, -7.1; 95% CI, -7.8 to -6.3) and among women vs men (8281 respondents [21.1%] vs 2573 respondents [17.9%]; odds ratio [OR], 1.22; 95% CI, 1.17 to 1.29). Those with CCS had 115% greater odds of anxiety or depression (OR, 2.15; 95% CI, 2.04-2.26; P < .001), and 80% greater odds of burnout (OR, 1.80; 95% CI, 1.70-1.90; P < .001) vs indidivuals without CCS. High CCS was associated with 91% greater odds of ITR (OR, 1.91; 95% CI, 1.76 to 2.08; P < .001) and 28% greater odds of ITL (OR, 1.28; 95% CI, 1.17 to 1.40; P < .001). CONCLUSIONS AND RELEVANCE:In this survey study, CCS was disproportionately described across different subgroups of HCWs and was associated with anxiety, depression, burnout, ITR, and ITL. Addressing CCS may improve HCWs' quality of life and HCW retention and work participation.
PMCID:9294994
PMID: 35849398
ISSN: 2574-3805
CID: 5948662
Development and Validation of a Machine Learning Model for Automated Assessment of Resident Clinical Reasoning Documentation
BACKGROUND:Residents receive infrequent feedback on their clinical reasoning (CR) documentation. While machine learning (ML) and natural language processing (NLP) have been used to assess CR documentation in standardized cases, no studies have described similar use in the clinical environment. OBJECTIVE:The authors developed and validated using Kane's framework a ML model for automated assessment of CR documentation quality in residents' admission notes. DESIGN, PARTICIPANTS, MAIN MEASURES/UNASSIGNED:Internal medicine residents' and subspecialty fellows' admission notes at one medical center from July 2014 to March 2020 were extracted from the electronic health record. Using a validated CR documentation rubric, the authors rated 414 notes for the ML development dataset. Notes were truncated to isolate the relevant portion; an NLP software (cTAKES) extracted disease/disorder named entities and human review generated CR terms. The final model had three input variables and classified notes as demonstrating low- or high-quality CR documentation. The ML model was applied to a retrospective dataset (9591 notes) for human validation and data analysis. Reliability between human and ML ratings was assessed on 205 of these notes with Cohen's kappa. CR documentation quality by post-graduate year (PGY) was evaluated by the Mantel-Haenszel test of trend. KEY RESULTS/RESULTS:The top-performing logistic regression model had an area under the receiver operating characteristic curve of 0.88, a positive predictive value of 0.68, and an accuracy of 0.79. Cohen's kappa was 0.67. Of the 9591 notes, 31.1% demonstrated high-quality CR documentation; quality increased from 27.0% (PGY1) to 31.0% (PGY2) to 39.0% (PGY3) (p < .001 for trend). Validity evidence was collected in each domain of Kane's framework (scoring, generalization, extrapolation, and implications). CONCLUSIONS:The authors developed and validated a high-performing ML model that classifies CR documentation quality in resident admission notes in the clinical environment-a novel application of ML and NLP with many potential use cases.
PMCID:9296753
PMID: 35710676
ISSN: 1525-1497
CID: 5277902
"Should I stay or should I go?" Nurses' perspectives about working during the Covid-19 pandemic's first wave in the United States: A summative content analysis combined with topic modeling
BACKGROUND:The COVID-19 pandemic had its first peak in the United States between April and July of 2020, with incidence and prevalence rates of the virus the greatest in the northeastern coast of the country. At the time of study implementation, there were few studies capturing the perspectives of nurses working the frontlines of the pandemic in any setting as research output in the United States focused largely on treating the disease. OBJECTIVE:The purpose of this study was to capture the perspectives of nurses in the United States working the frontlines of the COVID-19 pandemic's first wave. We were specifically interested in examining the impact of the pandemic on nurses' roles, professional relationships, and the organizational cultures of their employers. DESIGN/METHODS:We conducted an online qualitative study with a pragmatic design to capture the perspectives of nurses working during the first wave of the United States COVID-19 pandemic. Through social networking recruitment, frontline nurses from across the country were invited to participate. Participants provided long form, text-based responses to four questions designed to capture their experiences. A combination of Latent Dirichlet Allocation--a natural language processing technique--along with traditional summative content analysis techniques were used to analyze the data. SETTING/METHODS:The United States during the COVID-19 pandemic's first wave between May and July of 2020. RESULTS:A total of 318 nurses participated from 29 out of 50 states, with 242 fully completing all questions. Findings suggested that the place of work mattered significantly in terms of the frontline working experience. It influenced role changes, risk assumption, interprofessional teamwork experiences, and ultimately, likelihood to leave their jobs or the profession altogether. Organizational culture and its influence on pandemic response implementation was a critical feature of their experiences. CONCLUSIONS:Findings suggest that organizational performance during the pandemic may be reflected in nursing workforce retention as the risk for workforce attrition appears high. It was also clear from the reports that nurses appear to have assumed higher occupational risks during the pandemic when compared to other providers. The 2020 data from this study also offered a number of signals about potential threats to the stability and sustainability of the US nursing workforce that are now manifesting. The findings underscore the importance of conducting health workforce research during a crisis in order to discern the signals of future problems or for long-term crisis response. TWEETABLE ABSTRACT/CONCLUSIONS:Healthcare leaders made the difference for nurses during the pandemic. How many nurses leave their employer in the next year will tell you who was good, who wasn't.
PMCID:9020864
PMID: 35544991
ISSN: 1873-491x
CID: 5249452
Palliative Care Needs and Clinical Outcomes of Patients with Advanced Cancer in the Emergency Department
PMID: 35559758
ISSN: 1557-7740
CID: 5214912
Pain, Analgesic Use, and Patient Satisfaction With Spinal Versus General Anesthesia for Hip Fracture Surgery : A Randomized Clinical Trial
BACKGROUND:The REGAIN (Regional versus General Anesthesia for Promoting Independence after Hip Fracture) trial found similar ambulation and survival at 60 days with spinal versus general anesthesia for hip fracture surgery. Trial outcomes evaluating pain, prescription analgesic use, and patient satisfaction have not yet been reported. OBJECTIVE:To compare pain, analgesic use, and satisfaction after hip fracture surgery with spinal versus general anesthesia. DESIGN:Preplanned secondary analysis of a pragmatic randomized trial. (ClinicalTrials.gov: NCT02507505). SETTING:46 U.S. and Canadian hospitals. PARTICIPANTS:Patients aged 50 years or older undergoing hip fracture surgery. INTERVENTION:Spinal or general anesthesia. MEASUREMENTS:Pain on postoperative days 1 through 3; 60-, 180-, and 365-day pain and prescription analgesic use; and satisfaction with care. RESULTS:A total of 1600 patients were enrolled. The average age was 78 years, and 77% were women. A total of 73.5% (1050 of 1428) of patients reported severe pain during the first 24 hours after surgery. Worst pain over the first 24 hours after surgery was greater with spinal anesthesia (rated from 0 [no pain] to 10 [worst pain imaginable]; mean difference, 0.40 [95% CI, 0.12 to 0.68]). Pain did not differ across groups at other time points. Prescription analgesic use at 60 days occurred in 25% (141 of 563) and 18.8% (108 of 574) of patients assigned to spinal and general anesthesia, respectively (relative risk, 1.33 [CI, 1.06 to 1.65]). Satisfaction was similar across groups. LIMITATION:Missing outcome data and multiple outcomes assessed. CONCLUSION:Severe pain is common after hip fracture. Spinal anesthesia was associated with more pain in the first 24 hours after surgery and more prescription analgesic use at 60 days compared with general anesthesia. PRIMARY FUNDING SOURCE:
PMID: 35696684
ISSN: 1539-3704
CID: 5277802
Preventing driveline infection during left ventricular assist device support by the HeartMate 3: A survey-based study
PURPOSE/OBJECTIVE:Driveline infection (DLI) is a significant source of morbidity and mortality during left ventricular assist device (LVAD) support yet limited studies are available to describe the center-level prevalence, preventive practices, and their potential effectiveness. METHODS:We surveyed LVAD centers in the United States to determine program burden and preventive practices for DLI during HeartMate (HM) 3 support. An online, anonymous, question-based survey was sent to expert providers at implanting centers. Only a single respondent completed the survey for each center. As an exploratory analysis, we compared specific DLI preventive practices between centers with low (≤10%) and high (>10%) reported prevalence of DLI. RESULTS:Seventy-eight centers responded to the survey (response rate: 50%). Respondents were comprised of 37 (47%) heart failure cardiologists, 27 (35%) LVAD coordinators, and 14 (18%) cardiothoracic surgeons. The prevalence of DLI during HM3 was reported as ≤10% by 27 (35%), 11%-25% by 36 (46%), and >25% by 16 (19%) centers. Thirteen (17%) centers had a body mass index threshold for device placement, 29 (37%) utilized a counter incision, 66 (81%) placed an anchor stitch, and 69 (88%) used an external device to stabilize the DL. Proportionally, more centers with a low DLI prevalence used a wound vacuum 6 (22%) versus 3 (6%, p = 0.03) than those with high DLI. CONCLUSION/CONCLUSIONS:Variation exists in reported prevalence and practices of preventing and managing driveline infections across centers during HM3 support. Further studies are warranted to develop and assess the effectiveness of standardized preventive strategies.
PMID: 35083754
ISSN: 1525-1594
CID: 5348432
Journal of obstetric, gynecologic, & neonatal nursing. 2022:51(4):388-401.DOI: 10.1016/j.jogn.2022.04.005
Dimensional Analysis of Shared Decision Making in Contraceptive Counseling
OBJECTIVE:To conduct a dimensional analysis to identify conceptual gaps around shared decision making (SDM) in reproductive health care and to refine the conceptual definition of SDM as related to contraceptive counseling. DATA SOURCES:We identified source data through systematic searches of the CINAHL and PubMed databases. STUDY SELECTION:We included peer-reviewed research and nonresearch articles that addressed contraceptive counseling for pregnancy prevention in the United States. We did not consider date of publication as an inclusion criterion. We included 35 articles in the final review. DATA EXTRACTION:Using dimensional analysis, we extracted data to clarify the definition of SDM as a socially constructed concept that varies by perspective and context. DATA SYNTHESIS:Data synthesis enabled us to compare SDM from patient and provider perspectives and to identify four primary dimensions of SDM that varied by context: Patient Preferences, Relationship, Provider Bias, and Clinical Suitability. CONCLUSION:The four dimensions we identified illustrate the complexity and depth of SDM in contraceptive counseling encounters and broaden the definition of SDM to more than an encounter in which decision making incorporates clinician expertise and patient participation. We identified several assumptions that indicate the need for improved understanding that SDM is not a universal concept across perspectives and contexts. Most researchers in the included articles addressed the Patient Preferences dimension. Fewer considered the patient-provider relationship, the effect of provider bias, and the effect of specific clinical circumstances on SDM. We propose a conceptual map and model that can be used to refine the concepts that inform SDM and guide providers and researchers. Future research is needed to address the remaining gaps.
PMID: 35605641
ISSN: 1552-6909
CID: 5388052
