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3,271 results on '"Krumholz, Harlan M."'

1. Heart Failure Epidemiology and Outcomes Statistics: A Report of the Heart Failure Society of America

Author

Bozkurt, Biykem, Ahmad, Tariq, Alexander, Kevin M, Baker, William L, Bosak, Kelly, Breathett, Khadijah, Fonarow, Gregg C, Heidenreich, Paul, Ho, Jennifer E, Hsich, Eileen, Ibrahim, Nasrien E, Jones, Lenette M, Khan, Sadiya S, Khazanie, Prateeti, Koelling, Todd, Krumholz, Harlan M, Khush, Kiran K, Lee, Christopher, Morris, Alanna A, Page, Robert L, Pandey, Ambarish, Piano, Mariann R, Stehlik, Josef, Stevenson, Lynne Warner, Teerlink, John R, Vaduganathan, Muthiah, Ziaeian, Boback, and Members, Writing Committee

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Humans, Heart Failure, Hospitalization, Prevalence, Incidence, Writing Committee Members, Heart failure, epidemiology, incidence, mortality, outcomes, prevalence, Cardiorespiratory Medicine and Haematology, Nursing, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Published
2023

4. Distinguishing features of long COVID identified through immune profiling

Author

Klein, Jon, Wood, Jamie, Jaycox, Jillian R., Dhodapkar, Rahul M., Lu, Peiwen, Gehlhausen, Jeff R., Tabachnikova, Alexandra, Greene, Kerrie, Tabacof, Laura, Malik, Amyn A., Silva Monteiro, Valter, Silva, Julio, Kamath, Kathy, Zhang, Minlu, Dhal, Abhilash, Ott, Isabel M., Valle, Gabrielee, Peña-Hernández, Mario, Mao, Tianyang, Bhattacharjee, Bornali, Takahashi, Takehiro, Lucas, Carolina, Song, Eric, McCarthy, Dayna, Breyman, Erica, Tosto-Mancuso, Jenna, Dai, Yile, Perotti, Emily, Akduman, Koray, Tzeng, Tiffany J., Xu, Lan, Geraghty, Anna C., Monje, Michelle, Yildirim, Inci, Shon, John, Medzhitov, Ruslan, Lutchmansingh, Denyse, Possick, Jennifer D., Kaminski, Naftali, Omer, Saad B., Krumholz, Harlan M., Guan, Leying, Dela Cruz, Charles S., van Dijk, David, Ring, Aaron M., Putrino, David, and Iwasaki, Akiko

Published
2023
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5. Gene Sequencing Identifies Perturbation in Nitric Oxide Signaling as a Nonlipid Molecular Subtype of Coronary Artery Disease

Author

Khera, Amit V, Wang, Minxian, Chaffin, Mark, Emdin, Connor A, Samani, Nilesh J, Schunkert, Heribert, Watkins, Hugh, McPherson, Ruth, Erdmann, Jeanette, Elosua, Roberto, Boerwinkle, Eric, Ardissino, Diego, Butterworth, Adam S, Di Angelantonio, Emanuele, Naheed, Aliya, Danesh, John, Chowdhury, Rajiv, Krumholz, Harlan M, Sheu, Wayne H-H, Rich, Stephen S, Rotter, Jerome I, Chen, Yii-der Ida, Gabriel, Stacey, Lander, Eric S, Saleheen, Danish, and Kathiresan, Sekar

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Heart Disease - Coronary Heart Disease, Genetics, Prevention, Cardiovascular, Atherosclerosis, Heart Disease, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Humans, Coronary Artery Disease, Polymorphism, Genetic, Nitric Oxide, Cholesterol, Hypercholesterolemia, atherosclerosis, coronary artery disease, genetic association studies, nitric oxide synthase type III, precision medicine, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundA key goal of precision medicine is to disaggregate common, complex diseases into discrete molecular subtypes. Rare coding variants in the low-density lipoprotein receptor gene (LDLR) are identified in 1% to 2% of coronary artery disease (CAD) patients, defining a molecular subtype with risk driven by hypercholesterolemia.MethodsTo search for additional subtypes, we compared the frequency of rare, predicted loss-of-function and damaging missense variants aggregated within a given gene in 41 081 CAD cases versus 217 115 controls.ResultsRare variants in LDLR were most strongly associated with CAD, present in 1% of cases and associated with 4.4-fold increased CAD risk. A second subtype was characterized by variants in endothelial nitric oxide synthase gene (NOS3), a key enzyme regulating vascular tone, endothelial function, and platelet aggregation. A rare predicted loss-of-function or damaging missense variants in NOS3 was present in 0.6% of cases and associated with 2.42-fold increased risk of CAD (95% CI, 1.80-3.26; P=5.50×10-9). These variants were associated with higher systolic blood pressure (+3.25 mm Hg; [95% CI, 1.86-4.65]; P=5.00×10-6) and increased risk of hypertension (adjusted odds ratio 1.31; [95% CI, 1.14-1.51]; P=2.00×10-4) but not circulating cholesterol concentrations, suggesting that, beyond lipid pathways, nitric oxide synthesis is a key nonlipid driver of CAD risk.ConclusionsBeyond LDLR, we identified an additional nonlipid molecular subtype of CAD characterized by rare variants in the NOS3 gene.

Published
2022

7. Large-scale evidence generation and evaluation across a network of databases for type 2 diabetes mellitus (LEGEND-T2DM): a protocol for a series of multinational, real-world comparative cardiovascular effectiveness and safety studies

Author

Khera, Rohan, Schuemie, Martijn J, Lu, Yuan, Ostropolets, Anna, Chen, RuiJun, Hripcsak, George, Ryan, Patrick B, Krumholz, Harlan M, and Suchard, Marc A

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Patient Safety, Clinical Research, Comparative Effectiveness Research, Diabetes, Cardiovascular, Generic health relevance, Metabolic and endocrine, Good Health and Well Being, Adult, Diabetes Mellitus, Type 2, Dipeptidyl-Peptidase IV Inhibitors, Humans, Hypoglycemic Agents, Reproducibility of Results, Sodium-Glucose Transporter 2 Inhibitors, Sulfonylurea Compounds, Health informatics, DIABETES & ENDOCRINOLOGY, Cardiology, Clinical Sciences, Public Health and Health Services, Other Medical and Health Sciences, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

IntroductionTherapeutic options for type 2 diabetes mellitus (T2DM) have expanded over the last decade with the emergence of cardioprotective novel agents, but without such data for older drugs, leaving a critical gap in our understanding of the relative effects of T2DM agents on cardiovascular risk.Methods and analysisThe large-scale evidence generations across a network of databases for T2DM (LEGEND-T2DM) initiative is a series of systematic, large-scale, multinational, real-world comparative cardiovascular effectiveness and safety studies of all four major second-line anti-hyperglycaemic agents, including sodium-glucose co-transporter-2 inhibitor, glucagon-like peptide-1 receptor agonist, dipeptidyl peptidase-4 inhibitor and sulfonylureas. LEGEND-T2DM will leverage the Observational Health Data Sciences and Informatics (OHDSI) community that provides access to a global network of administrative claims and electronic health record data sources, representing 190 million patients in the USA and about 50 million internationally. LEGEND-T2DM will identify all adult, patients with T2DM who newly initiate a traditionally second-line T2DM agent. Using an active comparator, new-user cohort design, LEGEND-T2DM will execute all pairwise class-versus-class and drug-versus-drug comparisons in each data source, producing extensive study diagnostics that assess reliability and generalisability through cohort balance and equipoise to examine the relative risk of cardiovascular and safety outcomes. The primary cardiovascular outcomes include a composite of major adverse cardiovascular events and a series of safety outcomes. The study will pursue data-driven, large-scale propensity adjustment for measured confounding, a large set of negative control outcome experiments to address unmeasured and systematic bias.Ethics and disseminationThe study ensures data safety through a federated analytic approach and follows research best practices, including prespecification and full disclosure of results. LEGEND-T2DM is dedicated to open science and transparency and will publicly share all analytic code from reproducible cohort definitions through turn-key software, enabling other research groups to leverage our methods, data and results to verify and extend our findings.

Published
2022

16. Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review

Author

Li, Irene, Pan, Jessica, Goldwasser, Jeremy, Verma, Neha, Wong, Wai Pan, Nuzumlalı, Muhammed Yavuz, Rosand, Benjamin, Li, Yixin, Zhang, Matthew, Chang, David, Taylor, R. Andrew, Krumholz, Harlan M., and Radev, Dragomir

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, 68T50, I.2.7
Abstract

Electronic health records (EHRs), digital collections of patient healthcare events and observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and research. Despite this central role, EHRs are notoriously difficult to process automatically. Well over half of the information stored within EHRs is in the form of unstructured text (e.g. provider notes, operation reports) and remains largely untapped for secondary use. Recently, however, newer neural network and deep learning approaches to Natural Language Processing (NLP) have made considerable advances, outperforming traditional statistical and rule-based systems on a variety of tasks. In this survey paper, we summarize current neural NLP methods for EHR applications. We focus on a broad scope of tasks, namely, classification and prediction, word embeddings, extraction, generation, and other topics such as question answering, phenotyping, knowledge graphs, medical dialogue, multilinguality, interpretability, etc., Comment: 33 pages, 11 figures

Published
2021

18. Study protocol for the Innovative Support for Patients with SARS-COV-2 Infections Registry (INSPIRE): A longitudinal study of the medium and long-term sequelae of SARS-CoV-2 infection

Author

O’Laughlin, Kelli N, Thompson, Matthew, Hota, Bala, Gottlieb, Michael, Plumb, Ian D, Chang, Anna Marie, Wisk, Lauren E, Hall, Aron J, Wang, Ralph C, Spatz, Erica S, Stephens, Kari A, Huebinger, Ryan M, McDonald, Samuel A, Venkatesh, Arjun, Gentile, Nikki, Slovis, Benjamin H, Hill, Mandy, Saydah, Sharon, Idris, Ahamed H, Rodriguez, Robert, Krumholz, Harlan M, Elmore, Joann G, Weinstein, Robert A, and Nichol, Graham

Subjects
Patient Safety, HIV/AIDS, Clinical Trials and Supportive Activities, Prevention, Emerging Infectious Diseases, Vaccine Related, Biodefense, Infectious Diseases, Clinical Research, Lung, Pneumonia, Cancer, Infection, Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, COVID-19, Case-Control Studies, Cohort Studies, Female, Humans, Longitudinal Studies, Male, Middle Aged, Palliative Care, Patient Reported Outcome Measures, Prognosis, Registries, SARS-CoV-2, Social Determinants of Health, Therapies, Investigational, Time Factors, Young Adult, INSPIRE Investigators, General Science & Technology
Abstract

BackgroundReports on medium and long-term sequelae of SARS-CoV-2 infections largely lack quantification of incidence and relative risk. We describe the rationale and methods of the Innovative Support for Patients with SARS-CoV-2 Registry (INSPIRE) that combines patient-reported outcomes with data from digital health records to understand predictors and impacts of SARS-CoV-2 infection.MethodsINSPIRE is a prospective, multicenter, longitudinal study of individuals with symptoms of SARS-CoV-2 infection in eight regions across the US. Adults are eligible for enrollment if they are fluent in English or Spanish, reported symptoms suggestive of acute SARS-CoV-2 infection, and if they are within 42 days of having a SARS-CoV-2 viral test (i.e., nucleic acid amplification test or antigen test), regardless of test results. Recruitment occurs in-person, by phone or email, and through online advertisement. A secure online platform is used to facilitate the collation of consent-related materials, digital health records, and responses to self-administered surveys. Participants are followed for up to 18 months, with patient-reported outcomes collected every three months via survey and linked to concurrent digital health data; follow-up includes no in-person involvement. Our planned enrollment is 4,800 participants, including 2,400 SARS-CoV-2 positive and 2,400 SARS-CoV-2 negative participants (as a concurrent comparison group). These data will allow assessment of longitudinal outcomes from SARS-CoV-2 infection and comparison of the relative risk of outcomes in individuals with and without infection. Patient-reported outcomes include self-reported health function and status, as well as clinical outcomes including health system encounters and new diagnoses.ResultsParticipating sites obtained institutional review board approval. Enrollment and follow-up are ongoing.ConclusionsThis study will characterize medium and long-term sequelae of SARS-CoV-2 infection among a diverse population, predictors of sequelae, and their relative risk compared to persons with similar symptomatology but without SARS-CoV-2 infection. These data may inform clinical interventions for individuals with sequelae of SARS-CoV-2 infection.

Published
2022

19. Association of STEMI regionalization of care with de facto NSTEMI regionalization

Author

Montoy, Juan Carlos C, Shen, Yu-Chu, Krumholz, Harlan M, and Hsia, Renee Y

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Heart Disease, Heart Disease - Coronary Heart Disease, Patient Safety, Cardiovascular, Hospital Planning, Humans, Non-ST Elevated Myocardial Infarction, Percutaneous Coronary Intervention, ST Elevation Myocardial Infarction, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

The regionalization of care for ST elevation myocardial infarction (STEMI) may unintentionally concentrate patients with non-ST elevation myocardial infarction (NSTEMI) into percutaneous coronary intervention (PCI) capable hospitals. This could lead to benefits such as increased access to PCI-capable hospitals, but could cause harms such as crowding in some hospitals with decreased patient volume and revenue in others. We set out to assess whether STEMI regionalization programs concentrated patients with NSTEMI at STEMI-receiving hospitals.

Published
2021

20. Comparative First-Line Effectiveness and Safety of ACE (Angiotensin-Converting Enzyme) Inhibitors and Angiotensin Receptor Blockers: A Multinational Cohort Study.

Author

Chen, RuiJun, Suchard, Marc A, Krumholz, Harlan M, Schuemie, Martijn J, Shea, Steven, Duke, Jon, Pratt, Nicole, Reich, Christian G, Madigan, David, You, Seng Chan, Ryan, Patrick B, and Hripcsak, George

Subjects
Humans, Hypertension, Antihypertensive Agents, Angiotensin-Converting Enzyme Inhibitors, Treatment Outcome, Retrospective Studies, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Child, Preschool, Infant, Female, Male, Young Adult, Angiotensin Receptor Antagonists, angiotensin receptor, angiotensin receptor blocker, cardiovascular outcomes, hypertension, safety, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

[Figure: see text].

Published
2021

21. When Direct Oral Anticoagulants Should Not Be Standard Treatment: JACC State-of-the-Art Review

Author

Bejjani, Antoine, Khairani, Candrika D., Assi, Ali, Piazza, Gregory, Sadeghipour, Parham, Talasaz, Azita H., Fanikos, John, Connors, Jean M., Siegal, Deborah M., Barnes, Geoffrey D., Martin, Karlyn A., Angiolillo, Dominick J., Kleindorfer, Dawn, Monreal, Manuel, Jimenez, David, Middeldorp, Saskia, Elkind, Mitchell S.V., Ruff, Christian T., Goldhaber, Samuel Z., Krumholz, Harlan M., Mehran, Roxana, Cushman, Mary, Eikelboom, John W., Lip, Gregory Y.H., Weitz, Jeffrey I., Lopes, Renato D., and Bikdeli, Behnood

Published
2024
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23. Long COVID Characteristics and Experience: A Descriptive Study From the Yale LISTEN Research Cohort

Author

Sawano, Mitsuaki, Wu, Yilun, Shah, Rishi M., Zhou, Tianna, Arun, Adith S., Khosla, Pavan, Kaleem, Shayaan, Vashist, Anushree, Bhattacharjee, Bornali, Ding, Qinglan, Lu, Yuan, Caraballo, César, Warner, Frederick, Huang, Chenxi, Herrin, Jeph, Putrino, David, Michelsen, Teresa, Fisher, Liza, Adinig, Cynthia, Iwasaki, Akiko, and Krumholz, Harlan M.

Published
2024
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24. The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-Blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID

Author

Krumholz, Harlan M., Sawano, Mitsuaki, Bhattacharjee, Bornali, Caraballo, César, Khera, Rohan, Li, Shu-Xia, Herrin, Jeph, Coppi, Andreas, Holub, Julie, Henriquez, Yashira, Johnson, Maria A., Goddard, Theresa B., Rocco, Erica, Hummel, Amy C., AL Mouslmani, Mohammad, Putrino, David F., Carr, Kevin D., Carvajal-Gonzalez, Santos, Charnas, Lawrence, De Jesus, Magdia, Ziegler, Frank W., III, and Iwasaki, Akiko

Published
2024
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26. Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural Networks

Author

Zhang, Lida, Hurley, Nathan C., Ibrahim, Bassem, Spatz, Erica, Krumholz, Harlan M., Jafari, Roozbeh, and Mortazavi, Bobak J.

Subjects
Computer Science - Machine Learning, Computer Science - Human-Computer Interaction
Abstract

Blood pressure monitoring is an essential component of hypertension management and in the prediction of associated comorbidities. Blood pressure is a dynamic vital sign with frequent changes throughout a given day. Capturing blood pressure remotely and frequently (also known as ambulatory blood pressure monitoring) has traditionally been achieved by measuring blood pressure at discrete intervals using an inflatable cuff. However, there is growing interest in developing a cuffless ambulatory blood pressure monitoring system to measure blood pressure continuously. One such approach is by utilizing bioimpedance sensors to build regression models. A practical problem with this approach is that the amount of data required to confidently train such a regression model can be prohibitive. In this paper, we propose the application of the domain-adversarial training neural network (DANN) method on our multitask learning (MTL) blood pressure estimation model, allowing for knowledge transfer between subjects. Our proposed model obtains average root mean square error (RMSE) of $4.80 \pm 0.74$ mmHg for diastolic blood pressure and $7.34 \pm 1.88$ mmHg for systolic blood pressure when using three minutes of training data, $4.64 \pm 0.60$ mmHg and $7.10 \pm 1.79$ respectively when using four minutes of training data, and $4.48 \pm 0.57$ mmHg and $6.79 \pm 1.70$ respectively when using five minutes of training data. DANN improves training with minimal data in comparison to both directly training and to training with a pretrained model from another subject, decreasing RMSE by $0.19$ to $0.26$ mmHg (diastolic) and by $0.46$ to $0.67$ mmHg (systolic) in comparison to the best baseline models. We observe that four minutes of training data is the minimum requirement for our framework to exceed ISO standards within this cohort of patients., Comment: Published at MLHC 2020

Published
2020

27. Comprehensive Comparative Effectiveness and Safety of First-Line β-Blocker Monotherapy in Hypertensive Patients

Author

You, Seng Chan, Krumholz, Harlan M, Suchard, Marc A, Schuemie, Martijn J, Hripcsak, George, Chen, RuiJun, Shea, Steven, Duke, Jon, Pratt, Nicole, Reich, Christian G, Madigan, David, Ryan, Patrick B, Park, Rae Woong, and Park, Sungha

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Adrenergic beta-Antagonists, Adult, Antihypertensive Agents, Atenolol, Blood Pressure, Carvedilol, Databases, Factual, Female, Humans, Hypertension, Male, Middle Aged, Nebivolol, Treatment Outcome, antihypertensive agents, atenolol, blood pressure, hypertension, stroke, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

[Figure: see text].

Published
2021

29. Short- and longer-term all-cause mortality among SARS-CoV-2- infected individuals and the pull-forward phenomenon in Qatar: a national cohort study

Author

Chemaitelly, Hiam, Faust, Jeremy Samuel, Krumholz, Harlan M., Ayoub, Houssein H., Tang, Patrick, Coyle, Peter, Yassine, Hadi M., Al Thani, Asmaa A., Al-Khatib, Hebah A., Hasan, Mohammad R., Al-Kanaani, Zaina, Al-Kuwari, Einas, Jeremijenko, Andrew, Kaleeckal, Anvar Hassan, Latif, Ali Nizar, Shaik, Riyazuddin Mohammad, Abdul-Rahim, Hanan F., Nasrallah, Gheyath K., Al-Kuwari, Mohamed Ghaith, Butt, Adeel A., Al-Romaihi, Hamad Eid, Al-Thani, Mohamed H., Al-Khal, Abdullatif, Bertollini, Roberto, and Abu-Raddad, Laith J.

Published
2023
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30. Impact of ST‐Segment–Elevation Myocardial Infarction Regionalization Programs on the Treatment and Outcomes of Patients Diagnosed With Non–ST‐Segment–Elevation Myocardial Infarction

Author

Montoy, Juan Carlos C, Shen, Yu‐Chu, Brindis, Ralph G, Krumholz, Harlan M, and Hsia, Renee Y

Subjects
Heart Disease, Heart Disease - Coronary Heart Disease, Prevention, Clinical Research, Cardiovascular, Good Health and Well Being, Aged, Aged, 80 and over, California, Coronary Angiography, Early Diagnosis, Electrocardiography, Female, Follow-Up Studies, Hospitalization, Humans, Male, Middle Aged, Non-ST Elevated Myocardial Infarction, Percutaneous Coronary Intervention, Prognosis, Program Evaluation, Registries, Retrospective Studies, Risk Factors, ST Elevation Myocardial Infarction, Survival Rate, Treatment Outcome, angiography, mortality, non-ST segment-elevation myocardial infarction, ST-segment-elevation myocardial infarction, ST‐segment–elevation myocardial infarction, non–ST‐segment–elevation myocardial infarction, Cardiorespiratory Medicine and Haematology
Abstract

Background Many communities have implemented systems of regionalized care to improve access to timely care for patients with ST-segment-elevation myocardial infarction. However, patients who are ultimately diagnosed with non-ST-segment-elevation myocardial infarctions (NSTEMIs) may also be affected, and the impact of regionalization programs on NSTEMI treatment and outcomes is unknown. We set out to determine the effects of ST-segment-elevation myocardial infarction regionalization schemes on treatment and outcomes of patients diagnosed with NSTEMIs. Methods and Results The cohort included all patients receiving care in emergency departments diagnosed with an NSTEMI at all nonfederal hospitals in California from January 1, 2005 to September 30, 2015. Data were analyzed using a difference-in-differences approach. The main outcomes were 1-year mortality and angiography within 3 days of the index admission. A total of 293 589 patients with NSTEMIs received care in regionalized and nonregionalized communities. Over the study period, rates of early angiography increased by 0.5 and mortality decreased by 0.9 percentage points per year among the overall population (95% CI, 0.4-0.6 and -1.0 to -0.8, respectively). Regionalization was not associated with early angiography (-0.5%; 95% CI, -1.1 to 0.1) or death (0.2%; 95% CI, -0.3 to 0.8). Conclusions ST-segment-elevation myocardial infarction regionalization programs were not statistically associated with changes in guideline-recommended early angiography or changes in risk of death for patients with NSTEMI. Increases in the proportion of patients with NSTEMI who underwent guideline-directed angiography and decreases in risk of mortality were accounted for by secular trends unrelated to regionalization policies.

Published
2021

32. Association of Neighborhood-Level Marginalization With Health Care Use and Clinical Outcomes Following Hospital Discharge in Patients Who Underwent Coronary Catheterization for Acute Myocardial Infarction in a Single-Payer Health Care System

Author

Akioyamen, Leo E., Abdel-Qadir, Husam, Han, Lu, Sud, Maneesh, Mistry, Nikhil, Alter, David A., Atzema, Clare L., Austin, Peter C., Bhatia, R. Sacha, Booth, Gillian L., Dhalla, Irfan, Ha, Andrew C.T., Jackevicius, Cynthia A., Kapral, Moira K., Krumholz, Harlan M., Lee, Douglas S., McNaughton, Candace D., Roifman, Idan, Schull, Michael J., Sivaswamy, Atul, Tu, Karen, Udell, Jacob A., Wijeysundera, Harindra C., and Ko, Dennis T.

Published
2023
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36. Abstract 17709: ICD-10 Codes Have Low Sensitivity and Suboptimal Positive Predictive Value for Identifying Cases of Pulmonary Embolism With Cor Pulmonale in Electronic Healthcare Records

Author

Bejjani, Antoine, Khairani, Candrika D, Lo, Ying-Chih, Jimenez, David, Barco, Stefano, Mahajan, Shiwani, Caraballo, Cesar, Secemsky, Eric A, Klok, Erik, Hunsaker, Andetta, Aghayev, Ayaz, Muriel, Alfonso, Hussain, Mohamad A, Appah-Sampong, Abena, MOJIBIAN, HAMID, Lu, Yuan, Lin, Zhenqiu, Aneja, Sanjay, Khera, Rohan, Goldhaber, Samuel, Zhou, Li, Monreal, Manuel, Piazza, Gregory, Krumholz, Harlan M, and Bikdeli, Behnood

Published
2023
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37. Abstract 17700: Double Trouble With Identification of Isolated Sub-Segmental Pulmonary Embolism Using ICD-10 Discharge Diagnosis Codes: The PE-EHR+ Study

Author

Bejjani, Antoine, Khairani, Candrika D, Lo, Ying-Chih, Jimenez, David, Barco, Stefano, Mahajan, Shiwani, Caraballo, Cesar, Secemsky, Eric A, Klok, Erik, Hunsaker, Andetta, Aghayev, Ayaz, Muriel, Alfonso, Hussain, Mohamad A, Appah-Sampong, Abena, MOJIBIAN, HAMID, Lu, Yuan, Lin, Zhenqiu, Aneja, Sanjay, Khera, Rohan, Goldhaber, Samuel, Zhou, Li, Monreal, Manuel, Krumholz, Harlan M, Piazza, Gregory, and Bikdeli, Behnood

Published
2023
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43. Abstract 16342: Age- and Sex-Differences in Accuracy of ICD-10 Codes for Identifying Adults With Pulmonary Embolism: PE-EHR+ Study

Author

Mahajan, Shiwani, Lo, Ying-Chih, Bejjani, Antoine, Khairani, Candrika D, Jimenez, David, Barco, Stefano, Caraballo, Cesar, Secemsky, Eric A, Klok, Erik, Hunsaker, Andetta, Aghayev, Ayaz, Muriel, Alfonso, Hussain, Mohamad A, Appah-Sampong, Abena, MOJIBIAN, HAMID, Lu, Yuan, Lin, Zhenqiu, Aneja, Sanjay, Khera, Rohan, Goldhaber, Samuel, Zhou, Li, Monreal, Manuel, Piazza, Gregory, Krumholz, Harlan M, and Bikdeli, Behnood

Published
2023
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48. Abstract 14344: Pitfalls of ICD-10 Codes for Identifying Pulmonary Embolism in Electronic Records: Results From the Multicenter PE-EHR+ Study

Author

Bikdeli, Behnood, Bejjani, Antoine, Khairani, Candrika D, Lo, Ying-Chih, Jimenez, David, Barco, Stefano, Mahajan, Shiwani, Caraballo, Cesar, Secemsky, Eric A, Klok, Erik, Hunsaker, Andetta, Aghayev, Ayaz, Muriel, Alfonso, Hussain, Mohamad A, Appah-Sampong, Abena, MOJIBIAN, HAMID, Lu, Yuan, Lin, Zhenqiu, Aneja, Sanjay, Khera, Rohan, Goldhaber, Samuel, Zhou, Li, Monreal, Manuel, Piazza, Gregory, and Krumholz, Harlan M

Published
2023
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50. A Survey of Challenges and Opportunities in Sensing and Analytics for Cardiovascular Disorders

Author

Hurley, Nathan C., Spatz, Erica S., Krumholz, Harlan M., Jafari, Roozbeh, and Mortazavi, Bobak J.

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Computers and Society, Computer Science - Machine Learning
Abstract

Cardiovascular disorders account for nearly 1 in 3 deaths in the United States. Care for these disorders are often determined during visits to acute care facilities, such as hospitals. While the length of stay in these settings represents just a small proportion of patients' lives, they account for a disproportionately large amount of decision making. To overcome this bias towards data from acute care settings, there is a need for longitudinal monitoring in patients with cardiovascular disorders. Longitudinal monitoring can provide a more comprehensive picture of patient health, allowing for more informed decision making. This work surveys the current field of sensing technologies and machine learning analytics that exist in the field of remote monitoring for cardiovascular disorders. We highlight three primary needs in the design of new smart health technologies: 1) the need for sensing technology that can track longitudinal trends in signs and symptoms of the cardiovascular disorder despite potentially infrequent, noisy, or missing data measurements; 2) the need for new analytic techniques that model data captured in a longitudinal, continual fashion to aid in the development of new risk prediction techniques and in tracking disease progression; and 3) the need for machine learning techniques that are personalized and interpretable, allowing for advancements in shared clinical decision making. We highlight these needs based upon the current state-of-the-art in smart health technologies and analytics and discuss the ample opportunities that exist in addressing all three needs in the development of smart health technologies and analytics applied to the field of cardiovascular disorders and care., Comment: 32 pages, 3 figures, to be submitted to ACM Transactions on Computing for Healthcare (HEALTH), Special Issue on Wearable Technologies for Smart Health 2019

Published
2019

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