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4. Patient Cognitive Status and Physician Recommendations for Cardiovascular Disease Treatment: Results of Two Nationwide, Randomized Survey Studies

Author

Levine, Deborah A., Whitney, Rachael T., Galecki, Andrzej T., Fagerlin, Angela, Wallner, Lauren P., Shore, Supriya, Langa, Kenneth M., Nallamothu, Brahmajee K., Morgenstern, Lewis B., Giordani, Bruno, Reale, Bailey K., Blair, Emilie M., Sharma, Anupriya, Kabeto, Mohammed U., Plassman, Brenda L., and Zahuranec, Darin B.

Published
2023
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9. Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study

Author

Kamran, Fahad, Tang, Shengpu, Otles, Erkin, McEvoy, Dustin S, Saleh, Sameh N, Gong, Jen, Li, Benjamin Y, Dutta, Sayon, Liu, Xinran, Medford, Richard J, Valley, Thomas S, West, Lauren R, Singh, Karandeep, Blumberg, Seth, Donnelly, John P, Shenoy, Erica S, Ayanian, John Z, Nallamothu, Brahmajee K, Sjoding, Michael W, and Wiens, Jenna

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Clinical Research, Patient Safety, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, Area Under Curve, COVID-19, Clinical Decision Rules, Clinical Deterioration, Electronic Health Records, Female, Hospitalization, Hospitals, Humans, Linear Models, Machine Learning, Male, Middle Aged, Predictive Value of Tests, Prognosis, ROC Curve, Retrospective Studies, Risk Assessment, SARS-CoV-2, Young Adult, Public Health and Health Services, General & Internal Medicine, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

ObjectiveTo create and validate a simple and transferable machine learning model from electronic health record data to accurately predict clinical deterioration in patients with covid-19 across institutions, through use of a novel paradigm for model development and code sharing.DesignRetrospective cohort study.SettingOne US hospital during 2015-21 was used for model training and internal validation. External validation was conducted on patients admitted to hospital with covid-19 at 12 other US medical centers during 2020-21.Participants33 119 adults (≥18 years) admitted to hospital with respiratory distress or covid-19.Main outcome measuresAn ensemble of linear models was trained on the development cohort to predict a composite outcome of clinical deterioration within the first five days of hospital admission, defined as in-hospital mortality or any of three treatments indicating severe illness: mechanical ventilation, heated high flow nasal cannula, or intravenous vasopressors. The model was based on nine clinical and personal characteristic variables selected from 2686 variables available in the electronic health record. Internal and external validation performance was measured using the area under the receiver operating characteristic curve (AUROC) and the expected calibration error-the difference between predicted risk and actual risk. Potential bed day savings were estimated by calculating how many bed days hospitals could save per patient if low risk patients identified by the model were discharged early.Results9291 covid-19 related hospital admissions at 13 medical centers were used for model validation, of which 1510 (16.3%) were related to the primary outcome. When the model was applied to the internal validation cohort, it achieved an AUROC of 0.80 (95% confidence interval 0.77 to 0.84) and an expected calibration error of 0.01 (95% confidence interval 0.00 to 0.02). Performance was consistent when validated in the 12 external medical centers (AUROC range 0.77-0.84), across subgroups of sex, age, race, and ethnicity (AUROC range 0.78-0.84), and across quarters (AUROC range 0.73-0.83). Using the model to triage low risk patients could potentially save up to 7.8 bed days per patient resulting from early discharge.ConclusionA model to predict clinical deterioration was developed rapidly in response to the covid-19 pandemic at a single hospital, was applied externally without the sharing of data, and performed well across multiple medical centers, patient subgroups, and time periods, showing its potential as a tool for use in optimizing healthcare resources.

Published
2022

10. Ten Steps Toward Improving In-Hospital Cardiac Arrest Quality of Care and Outcomes

Author

Chan, Paul S., Greif, Robert, Anderson, Theresa, Atiq, Huba, Bittencourt Couto, Thomaz, Considine, Julie, De Caen, Allan R., Djärv, Therese, Doll, Ann, Douma, Matthew J., Edelson, Dana P., Xu, Feng, Finn, Judith C., Firestone, Grace, Girotra, Saket, Lauridsen, Kasper G., Kah-Lai Leong, Carrie, Lim, Swee Han, Morley, Peter T., Morrison, Laurie J., Moskowitz, Ari, Mullasari Sankardas, Ajit, Mustafa Mohamed, Mahmoud Tageldin, Myburgh, Michelle Christy, Nadkarni, Vinay M., Neumar, Robert W., Nolan, Jerry P., Odakha, Justine Athieno, Olasveengen, Theresa M., Orosz, Judit, Perkins, Gavin D., Previdi, Jeanette K., Vaillancourt, Christian, Montgomery, William H., Sasson, Comilla, and Nallamothu, Brahmajee K.

Published
2023
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17. Anatomical Variations in Pulmonary Arterial Branches in Patients Undergoing Evaluation for Chronic Thromboembolic Pulmonary Hypertension

Author

Michaud, Erinleigh, Pan, Michael, Lakhter, Vladimir, Reddy Maligireddy, Anand, Hyder, Syed N., Patel, Nimai, Moles, Victor M., McLaughlin, Vallerie V., Agarwal, Prachi P., Visovatti, Scott H., Cascino, Thomas M., Haft, Jonathan, Rosenfield, Kenneth, Nallamothu, Brahmajee K., Giri, Jay S., Bashir, Riyaz, and Aggarwal, Vikas

Published
2023
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19. Abstract 18199: Relationship Between Hospital Care Team Segregation Index and Cardiovascular Care for Black and White Patients

Author

Johnson, Adedoyin, Knapp, Shannon, Quintero Bisono, Janina, Trabue, Dalancee, Yee, Ryan, Williamson, Francesca, Watty, Stephen, Pool, Natalie, Thomas Hebdon, Megan, Moore, Wanda F, Yankah, Ekoh, Ezema, Nneamaka, Kimbrough, Nia, Washington, Johnnie, Lightbourne, Karen, Edmonds, Brownsyne, Capers, Quinn, Brown, David, Johnson, Denee, Evans, Jalynn, Foree, Brandi, Holman, Anastasia, Blount, Courtland, Nallamothu, Brahmajee K, Hollingsworth, John, and Breathett, Khadijah

Published
2023
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20. Abstract 17918: Provider Care Team Segregation and Ischemic Heart Disease Outcomes by Race

Author

Mwansa, Hunter, Johnson, Adedoyin, Knapp, Shannon, Bisono, Janina Q, Trabue, Dalancee, Yee, Ryan, Williamson, Francesca, Watty, Stephen, Pool, Natalie, Thomas Hebdon, Megan, Moore, Wanda, Yankah, Ekoh, Ezema, Nneamaka, Kimbrough, Nia, Washington, Johnnie, Lightbourne, Karen, Edmonds, Brownsyne, Capers, Quinn, Brown, David, Johnson, Denee, Evans, Jalynn, Foree, Brandi, Holman, Anastasia, Blount, Courtland, Nallamothu, Brahmajee K, Hollingsworth, John, and Breathett, Khadijah

Published
2023
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23. Ten Steps Toward Improving In-Hospital Cardiac Arrest Quality of Care and Outcomes

Author

Nallamothu, Brahmajee K., Greif, Robert, Anderson, Theresa, Atiq, Huba, Couto, Thomaz Bittencourt, Considine, Julie, De Caen, Allan R., Djärv, Therese, Doll, Ann, Douma, Matthew J., Edelson, Dana P., Xu, Feng, Finn, Judith C., Firestone, Grace, Girotra, Saket, Lauridsen, Kasper G., Leong, Carrie Kah-Lai, Lim, Swee Han, Morley, Peter T., Morrison, Laurie J., Moskowitz, Ari, Mullasari Sankardas, Ajit, Mohamed, Mahmoud Tageldin Mustafa, Myburgh, Michelle Christy, Nadkarni, Vinay M., Neumar, Robert W., Nolan, Jerry P., Athieno Odakha, Justine, Olasveengen, Theresa M., Orosz, Judit, Perkins, Gavin D., Previdi, Jeanette K., Vaillancourt, Christian, Montgomery, William H., Sasson, Comilla, and Chan, Paul S.

Published
2023
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29. Vessel Segmentation and Catheter Detection in X-Ray Angiograms Using Superpixels

Author

Fazlali, Hamid R., Karimi, Nader, Soroushmehr, S. M. Reza, Shirani, Shahram, Nallamothu, Brahmajee. K., Ward, Kevin R., Samavi, Shadrokh, and Najarian, Kayvan

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Coronary artery disease (CAD) is the leading causes of death around the world. One of the most common imaging methods for diagnosing this disease is X-ray angiography. Diagnosing using these images is usually challenging due to non-uniform illumination, low contrast, presence of other body tissues, presence of catheter etc. These challenges make the diagnoses task of cardiologists tougher and more prone to misdiagnosis. In this paper we propose a new automated framework for coronary arteries segmentation, catheter detection and center-line extraction in x-ray angiography images. Our proposed segmentation method is based on superpixels. In this method at first three different superpixel scales are exploited and a measure for vesselness probability of each superpixel is determined. A majority voting is used for obtaining an initial segmentation map from these three superpixel scales. This initial segmentation is refined by finding the orthogonal line on each ridge pixel of vessel region. In this framework we use our catheter detection and tracking method which detects the catheter by finding its ridge in the first frame and traces in other frames by fitting a second order polynomial on it. Also we use the image ridges for extracting the coronary arteries centerlines. We evaluated our method qualitatively and quantitatively on two different challenging datasets and compared it with one of the previous well-known coronary arteries segmentation methods. Our method could detect the catheter and reduced the false positive rate in addition to achieving better segmentation results. The evaluation results prove that our method performs better in a much shorter time., Comment: 14 Pages, 19 figures, 2 tables

Published
2017

31. Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention.

Author

Golbus, Jessica R., Shi, Jieru, Gupta, Kashvi, Stevens, Rachel, Jeganathan, V. Swetha E., Luff, Evan, Boyden, Thomas, Mukherjee, Bhramar, Kohnstamm, Sarah, Taralunga, Vlad, Kheterpal, Vik, Kheterpal, Sachin, Resnicow, Kenneth, Murphy, Susan, Dempsey, Walter, Klasnja, Predrag, and Nallamothu, Brahmajee K.

Abstract

BACKGROUND: Text messages may enhance physical activity levels in patients with cardiovascular disease, including those enrolled in cardiac rehabilitation. However, the independent and long-term effects of text messages remain uncertain. METHODS: The VALENTINE study (Virtual Application-supported Environment to Increase Exercise) was a micro-randomized trial that delivered text messages through a smartwatch (Apple Watch or Fitbit Versa) to participants initiating cardiac rehabilitation. Participants were randomized 4× per day over 6-months to receive no text message or a message encouraging low-level physical activity. Text messages were tailored on contextual factors (eg, weather). Our primary outcome was step count 60 minutes following a text message, and we used a centered and weighted least squares mean method to estimate causal effects. Given potential measurement differences between devices determined a priori, data were assessed separately for Apple Watch and Fitbit Versa users over 3 time periods corresponding to the initiation (0-30 days), maintenance (31-120 days), and completion (121-182 days) of cardiac rehabilitation. RESULTS: One hundred eight participants were included with 70 552 randomizations over 6 months; mean age was 59.5 (SD, 10.7) years with 36 (32.4%) female and 68 (63.0%) Apple Watch participants. For Apple Watch participants, text messages led to a trend in increased step count by 10% in the 60-minutes following a message during days 1 to 30 (95% CI, -1% to +20%), with no effect from days 31 to 120 (+1% [95% CI, -4% to +5%]), and a significant 6% increase during days 121 to 182 (95% CI, +0% to +11%). For Fitbit users, text messages significantly increased step count by 17% (95% CI, +7% to +28%) in the 60-minutes following a message in the first 30 days of the study with no effect subsequently. CONCLUSIONS: In patients undergoing cardiac rehabilitation, contextually tailored text messages may increase physical activity, but this effect varies over time and by device. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Hospital-cardiologist integration often occurs without a practice acquisition

Author

Post, Brady, Nallamothu, Brahmajee K., and Hollenbeck, Brent

Subjects
Medicine -- Practice, Cardiologists -- Employment -- Research, Vertical integration -- Research, Hospitals -- Human resource management -- Research -- United States, Company personnel management, Business, Health care industry
Abstract

Objective: To describe how much of the recent increase in hospital-cardiologist integration has come from acquisitions of physician practices compared to individual employment decisions. While the role of physician practice acquisitions has received considerable attention in the news, integration may also be driven by individual physicians accepting employment at hospital-based practices. Data Sources: American Medical Association Physician Masterfile and Medicare data. Study Design: Analysis of changes in hospital-cardiologist integration from 2011 to 2018. We measured increases in integration and changes in the number of independent and hospital-owned practices. Data Collection/Extraction Methods: Not applicable. Principal Findings: In 2011, 18% of cardiologists were integrated, rising to 25% in 2016. Of this rise, 48% occurred with no acquisitions. Physicians who had completed residencies in the past 5 years (early career physicians) had higher rates of integration that also increased over time: the percentage of early career physicians joining hospital systems rose from 25% to 32%, indicating rapid growth in the number of physicians who began their careers working in hospital-based sites. Conclusions: A large and growing portion of hospital-cardiologist integration came from hospital employment at the individual physician level. Future policies focused on preserving competition and affordability may benefit from better understanding this form of consolidation. KEYWORDS delivery system organization, hospital workforce, hospital-physician integration, outpatient care delivery, physician employment, physician practice organization, vertical integration, 1 | INTRODUCTION Hospitals and physicians have become increasingly integrated in recent years. (1-3) This trend, in which hospitals employ physicians either directly or indirectly through ownership of physician practices, [...]

Published
2022
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33. In-hospital cardiac arrest in critically ill patients with covid-19 : multicenter cohort study

Author

STOP-COVID Investigators, Hayek, Salim S, Brenner, Samantha K, Azam, Tariq U, Shadid, Husam R, Anderson, Elizabeth, Berlin, Hanna, Pan, Michael, Meloche, Chelsea, Feroz, Rafey, O’Hayer, Patrick, Kaakati, Rayan, Bitar, Abbas, Padalia, Kishan, Perry, Daniel, Blakely, Pennelope, Gupta, Shruti, Shaefi, Shahzad, Srivastava, Anand, Charytan, David M, Bansal, Anip, Mallappallil, Mary, Melamed, Michal L, Shehata, Alexandre M, Sunderram, Jag, Mathews, Kusum S, Sutherland, Anne K, Nallamothu, Brahmajee K, and Leaf, David E

Published
2020

40. Resource Requirements for Participant Enrollment From a University Health System and a Federally Qualified Health Center Network in a Mobile Health Study: The myBPmyLife Trial

Author

Skolarus, Lesli E., primary, Farhan, Zahera, additional, Mishra, Sonali R., additional, Rao, Nikhila, additional, Bowie, Kaitlyn, additional, Bailey, Sarah, additional, Dorsch, Michael P., additional, Newman, Mark W., additional, Nallamothu, Brahmajee K., additional, and Golbus, Jessica R., additional

Published
2024
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41. Challenge of Optimizing Medical Therapy in Heart Failure: Unlocking the Potential of Digital Health and Patient Engagement

Author

Azizi, Zahra, primary, Golbus, Jessica R., additional, Spaulding, Erin M., additional, Hwang, Phillip H., additional, Ciminelli, Ana L. A., additional, Lacar, Kathleen, additional, Hernandez, Mario Funes, additional, Gilotra, Nisha A., additional, Din, Natasha, additional, Brant, Luisa C. C., additional, Au, Rhoda, additional, Beaton, Andrea, additional, Nallamothu, Brahmajee K., additional, Longenecker, Chris T., additional, Martin, Seth S., additional, Dorsch, Michael P., additional, and Sandhu, Alexander T., additional

Published
2024
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43. A Physical Activity and Diet Just‐in‐Time Adaptive Intervention to Reduce Blood Pressure: The myBPmyLife Study Rationale and Design

Author

Golbus, Jessica R., primary, Jeganathan, V. Swetha E., additional, Stevens, Rachel, additional, Ekechukwu, Weena, additional, Farhan, Zahera, additional, Contreras, Rocio, additional, Rao, Nikhila, additional, Trumpower, Brad, additional, Basu, Tanima, additional, Luff, Evan, additional, Skolarus, Lesli E., additional, Newman, Mark W., additional, Nallamothu, Brahmajee K., additional, and Dorsch, Michael P., additional

Published
2024
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48. A Community Participatory Approach to Creating Contextually Tailored mHealth Notifications: myBPmyLife Project.

Author

Hellem, Abby Katherine, Casetti, Amanda, Bowie, Kaitlyn, Golbus, Jessica R., Merid, Beza, Nallamothu, Brahmajee K., Dorsch, Michael P., Newman, Mark W., and Skolarus, Lesli

Subjects
MEDICAL care research, SALT-free diet, TELEMEDICINE, THEMATIC analysis, BLOOD pressure, PHYSICAL activity
Abstract

Just-in-time adaptive interventions (JITAIs) are a novel approach to mobile health (mHealth) interventions, sending contextually tailored behavior change notifications to participants when they are more likely to engage, determined by data from wearable devices. We describe a community participatory approach to JITAI notification development for the myBPmyLife Project, a JITAI focused on decreasing sodium consumption and increasing physical activity to reduce blood pressure. Eighty-six participants were interviewed, 50 at a federally qualified health center (FQHC) and 36 at a university clinic. Participants were asked to provide encouraging physical activity and low-sodium diet notifications and provided feedback on researcher-generated notifications to inform revisions. Participant notifications were thematically analyzed using an inductive approach. Participants noted challenging vocabulary, phrasing, and culturally incongruent suggestions in some of the researcher-generated notifications. Community-generated notifications were more direct, used colloquial language, and contained themes of grace. The FQHC participants' notifications expressed more compassion, religiosity, and addressed health-related social needs. University clinic participants' notifications frequently focused on office environments. In summary, our participatory approach to notification development embedded a distinctive community voice within our notifications. Our approach may be generalizable to other communities and serve as a model to create tailored mHealth notifications to their focus population. [ABSTRACT FROM AUTHOR]

Published
2024
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