Browsing by Author "Kamal, Ayesha"

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    Development and Validation of a Machine Learning-based, Point-of-Care Risk Calculator for Post-ERCP Pancreatitis and Prophylaxis Selection
    (Elsevier, 2024) Brenner, Todd; Kuo, Albert; Sperna Weiland, Christina J.; Kamal, Ayesha; Elmunzer, B. Joseph; Luo, Hui; Buxbaum, James; Gardner, Timothy B.; Mok, Shaffer S.; Fogel, Evan S.; Phillip, Veit; Choi, Jun-Ho; Lua, Guan W.; Lin, Ching-Chung; Reddy, D. Nageshwar; Lakhtakia, Sundeep; Goenka, Mahesh K.; Kochhar, Rakesh; Khashab, Mouen A.; van Geenen, Erwin J. M.; Singh, Vikesh K.; Tomasetti, Cristian; Akshintala, Venkata S.; Medicine, School of Medicine
    Background and Aims A robust model of post-ERCP pancreatitis (PEP) risk is not currently available. We aimed to develop a machine learning–based tool for PEP risk prediction to aid in clinical decision making related to periprocedural prophylaxis selection and postprocedural monitoring. Methods Feature selection, model training, and validation were performed using patient-level data from 12 randomized controlled trials. A gradient-boosted machine (GBM) model was trained to estimate PEP risk, and the performance of the resulting model was evaluated using the area under the receiver operating curve (AUC) with 5-fold cross-validation. A web-based clinical decision-making tool was created, and a prospective pilot study was performed using data from ERCPs performed at the Johns Hopkins Hospital over a 1-month period. Results A total of 7389 patients were included in the GBM with an 8.6% rate of PEP. The model was trained on 20 PEP risk factors and 5 prophylactic interventions (rectal nonsteroidal anti-inflammatory drugs [NSAIDs], aggressive hydration, combined rectal NSAIDs and aggressive hydration, pancreatic duct stenting, and combined rectal NSAIDs and pancreatic duct stenting). The resulting GBM model had an AUC of 0.70 (65% specificity, 65% sensitivity, 95% negative predictive value, and 15% positive predictive value). A total of 135 patients were included in the prospective pilot study, resulting in an AUC of 0.74. Conclusions This study demonstrates the feasibility and utility of a novel machine learning–based PEP risk estimation tool with high negative predictive value to aid in prophylaxis selection and identify patients at low risk who may not require extended postprocedure monitoring.
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    Digestive Manifestations in Patients Hospitalized With Coronavirus Disease 2019
    (Elsevier, 2020-10-01) Elmunzer, B. Joseph; Spitzer, Rebecca L.; Foster, Lydia D.; Merchant, Ambreen A.; Howard, Eric F.; Patel, Vaishali A.; West, Mary K.; Qayed, Emad; Nustas, Rosemary; Zakaria, Ali; Piper, Marc S.; Taylor, Jason R.; Jaza, Lujain; Forbes, Nauzer; Chau, Millie; Lara, Luis F.; Papachristou, Georgios I.; Volk, Michael L.; Hilson, Liam G.; Zhou, Selena; Kushnir, Vladimir M.; Lenyo, Alexandria M.; McLeod, Caroline G.; Amin, Sunil; Kuftinec, Gabriela N.; Yadav, Dhiraj; Fox, Charlie; Kolb, Jennifer M.; Pawa, Swati; Pawa, Rishi; Canakis, Andrew; Huang, Christopher; Jamil, Laith H.; Aneese, Andrew M.; Glamour, Benita K.; Smith, Zachary L.; Hanley, Katherine A.; Wood, Jordan; Patel, Harsh K.; Shah, Janak N.; Agarunov, Emil; Sethi, Amrita; Fogel, Evan L.; McNulty, Gail; Haseeb, Abdul; Trieu, Judy A.; Dixon, Rebekah E.; Yang, Jeong Yun; Mendelsohn, Robin B.; Calo, Delia; Aroniadis, Olga C.; LaComb, Joseph F.; Scheiman, James M.; Sauer, Bryan G.; Dang, Duyen T.; Piraka, Cyrus R.; Shah, Eric D.; Pohl, Heiko; Tierney, William M.; Mitchell, Stephanie; Condon, Ashwinee; Lenhart, Adrienne; Dua, Kulwinder S.; Kanagala, Vikram S.; Kamal, Ayesha; Singh, Vikesh K.; Pinto-Sanchez, Maria Ines; Hutchinson, Joy M.; Kwon, Richard S.; Korsnes, Sheryl J.; Singh, Harminder; Solati, Zahra; Willingham, Field F.; Yachimski, Patrick S.; Conwell, Darwin L.; Mosier, Evan; Azab, Mohamed; Patel, Anish; Buxbaum, James; Wani, Sachin; Chak, Amitabh; Hosmer, Amy E.; Keswani, Rajesh N.; DiMaio, Christopher J.; Bronze, Michael S.; Muthusamy, Raman; Canto, Marcia I.; Gjeorgjievski, V. Mihajlo; Imam, Zaid; Odish, Fadi; Edhi, Ahmed I.; Orosey, Molly; Tiwari, Abhinav; Patwardhan, Soumil; Brown, Nicholas G.; Patel, Anish A.; Ordiah, Collins O.; Sloan, Ian P.; Cruz, Lilian; Koza, Casey L.; Okafor, Uchechi; Hollander, Thomas; Furey, Nancy; Reykhart, Olga; Zbib, Natalia H.; Damianos, John A.; Esteban, James; Hajidiacos, Nick; Saul, Melissa; Mays, Melanie; Anderson, Gulsum; Wood, Kelley; Mathews, Laura; Diakova, Galina; Caisse, Molly; Wakefield, Lauren; Nitchie, Haley; Waljee, Akbar K.; Tang, Weijing; Zhang, Yueyang; Zhu, Ji; Deshpande, Amar R.; Rockey, Don C.; Alford, Teldon B.; Durkalski, Valerie; Medicine, School of Medicine
    Background & Aims The prevalence and significance of digestive manifestations in coronavirus disease 2019 (COVID-19) remain uncertain. We aimed to assess the prevalence, spectrum, severity, and significance of digestive manifestations in patients hospitalized with COVID-19. Methods Consecutive patients hospitalized with COVID-19 were identified across a geographically diverse alliance of medical centers in North America. Data pertaining to baseline characteristics, symptomatology, laboratory assessment, imaging, and endoscopic findings from the time of symptom onset until discharge or death were abstracted manually from electronic health records to characterize the prevalence, spectrum, and severity of digestive manifestations. Regression analyses were performed to evaluate the association between digestive manifestations and severe outcomes related to COVID-19. Results A total of 1992 patients across 36 centers met eligibility criteria and were included. Overall, 53% of patients experienced at least 1 gastrointestinal symptom at any time during their illness, most commonly diarrhea (34%), nausea (27%), vomiting (16%), and abdominal pain (11%). In 74% of cases, gastrointestinal symptoms were judged to be mild. In total, 35% of patients developed an abnormal alanine aminotransferase or total bilirubin level; these were increased to less than 5 times the upper limit of normal in 77% of cases. After adjusting for potential confounders, the presence of gastrointestinal symptoms at any time (odds ratio, 0.93; 95% CI, 0.76–1.15) or liver test abnormalities on admission (odds ratio, 1.31; 95% CI, 0.80–2.12) were not associated independently with mechanical ventilation or death. Conclusions Among patients hospitalized with COVID-19, gastrointestinal symptoms and liver test abnormalities were common, but the majority were mild and their presence was not associated with a more severe clinical course.
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    Digestive Manifestations in Patients Hospitalized With Coronavirus Disease 2019
    (Elsevier, 2021-07) Elmunzer, B. Joseph; Spitzer, Rebecca L.; Foster, Lydia D.; Merchant, Ambreen A.; Howard, Eric F.; Patel, Vaishali A.; West, Mary K.; Qayed, Emad; Nustas, Rosemary; Zakaria, Ali; Piper, Marc S.; Taylor, Jason R.; Jaza, Lujain; Forbes, Nauzer; Chau, Millie; Lara, Luis F.; Papachristou, Georgios I.; Volk, Michael L.; Hilson, Liam G.; Zhou, Selena; Kushnir, Vladimir M.; Lenyo, Alexandria M.; McLeod, Caroline G.; Amin, Sunil; Kuftinec, Gabriela N.; Yadav, Dhiraj; Fox, Charlie; Kolb, Jennifer M.; Pawa, Swati; Pawa, Rishi; Canakis, Andrew; Huang, Christopher; Jamil, Laith H.; Aneese, Andrew M.; Glamour, Benita K.; Smith, Zachary L.; Hanley, Katherine A.; Wood, Jordan; Patel, Harsh K.; Shah, Janak N.; Agarunov, Emil; Sethi, Amrita; Fogel, Evan L.; McNulty, Gail; Haseeb, Abdul; Trieu, Judy A.; Dixon, Rebekah E.; Yang, Jeong Yun; Mendelsohn, Robin B.; Calo, Delia; Aroniadis, Olga C.; LaComb, Joseph F.; Scheiman, James M.; Sauer, Bryan G.; Dang, Duyen T.; Piraka, Cyrus R.; Shah, Eric D.; Pohl, Heiko; Tierney, William M.; Mitchell, Stephanie; Condon, Ashwinee; Lenhart, Adrienne; Dua, Kulwinder S.; Kanagala, Vikram S.; Kamal, Ayesha; Singh, Vikesh K.; Pinto-Sanchez, Maria Ines; Hutchinson, Joy M.; Kwon, Richard S.; Korsnes, Sheryl J.; Singh, Harminder; Solati, Zahra; Willingham, Field F.; Yachimski, Patrick S.; Conwell, Darwin L.; Mosier, Evan; Azab, Mohamed; Patel, Anish; Buxbaum, James; Wani, Sachin; Chak, Amitabh; Hosmer, Amy E.; Keswani, Rajesh N.; DiMaio, Christopher J.; Bronze, Michael S.; Muthusamy, Raman; Canto, Marcia I.; Gjeorgjievski, V. Mihajlo; Imam, Zaid; Odish, Fadi; Edhi, Ahmed I.; Orosey, Molly; Tiwari, Abhinav; Patwardhan, Soumil; Brown, Nicholas G.; Patel, Anish A.; Ordiah, Collins O.; Sloan, Ian P.; Cruz, Lilian; Koza, Casey L.; Okafor, Uchechi; Hollander, Thomas; Furey, Nancy; Reykhart, Olga; Zbib, Natalia H.; Damianos, John A.; Esteban, James; Hajidiacos, Nick; Saul, Melissa; Mays, Melanie; Anderson, Gulsum; Wood, Kelley; Mathews, Laura; Diakova, Galina; Caisse, Molly; Wakefield, Lauren; Nitchie, Haley; Waljee, Akbar K.; Tang, Weijing; Zhang, Yueyang; Zhu, Ji; Deshpande, Amar R.; Rockey, Don C.; Alford, Teldon B.; Durkalski, Valerie; North American Alliance for the Study of Digestive Manifestations of COVID-19; Medicine, School of Medicine
    BACKGROUND & AIMS: The prevalence and significance of digestive manifestations in coronavirus disease 2019 (COVID-19) remain uncertain. We aimed to assess the prevalence, spectrum, severity, and significance of digestive manifestations in patients hospitalized with COVID-19. METHODS: Consecutive patients hospitalized with COVID-19 were identified across a geographically diverse alliance of medical centers in North America. Data pertaining to baseline characteristics, symptomatology, laboratory assessment, imaging, and endoscopic findings from the time of symptom onset until discharge or death were abstracted manually from electronic health records to characterize the prevalence, spectrum, and severity of digestive manifestations. Regression analyses were performed to evaluate the association between digestive manifestations and severe outcomes related to COVID-19. RESULTS: A total of 1992 patients across 36 centers met eligibility criteria and were included. Overall, 53% of patients experienced at least 1 gastrointestinal symptom at any time during their illness, most commonly diarrhea (34%), nausea (27%), vomiting (16%), and abdominal pain (11%). In 74% of cases, gastrointestinal symptoms were judged to be mild. In total, 35% of patients developed an abnormal alanine aminotransferase or total bilirubin level; these were increased to less than 5 times the upper limit of normal in 77% of cases. After adjusting for potential confounders, the presence of gastrointestinal symptoms at any time (odds ratio, 0.93; 95% CI, 0.76-1.15) or liver test abnormalities on admission (odds ratio, 1.31; 95% CI, 0.80-2.12) were not associated independently with mechanical ventilation or death. CONCLUSIONS: Among patients hospitalized with COVID-19, gastrointestinal symptoms and liver test abnormalities were common, but the majority were mild and their presence was not associated with a more severe clinical course.
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    Dynamic changes in the pancreatitis activity scoring system during hospital course in a multicenter, prospective cohort
    (Wiley, 2021) Paragomi, Pedram; Tuft, Marie; Pothoulakis, loannis; Singh, Vikesh K.; Stevens, Tyler; Nawaz, Haq; Easler, Jeffrey J.; Thakkar, Shyam; Cote, Gregory A.; Lee, Peter J.; Akshintala, Venkata; Kamal, Ayesha; Gougol, Amir; Evans Phillips, Anna; Machicado, Jorge D.; Whitcomb, David C.; Greer, Phil J.; Buxbaum, James L.; Hart, Phil; Conwell, Darwin; Tang, Gong; Wu, Bechien U.; Papachristou, Georgios I.; Medicine, School of Medicine
    Background and aim: The primary aim was to validate the Pancreatitis Activity Scoring System (PASS) in a multicenter prospectively ascertained acute pancreatitis (AP) cohort. Second, we investigated the association of early PASS trajectories with disease severity and length of hospital stay (LOS). Methods: Data were prospectively collected through the APPRENTICE consortium (2015-2018). AP severity was categorized based on revised Atlanta classification. Delta PASS (ΔPASS) was calculated by subtracting activity score from baseline value. PASS trajectories were compared between severity subsets. Subsequently, the cohort was subdivided into three LOS subgroups as short (S-LOS): 2-3 days; intermediate (I-LOS): 3-7 days; and long (L-LOS): ≥7 days. The generalized estimating equations model was implemented to compare PASS trajectories. Results: There were 434 subjects analyzed including 322 (74%) mild, 86 (20%) moderately severe, and 26 (6%) severe AP. Severe AP subjects had the highest activity levels and the slowest rate of decline in activity (P = 0.039). Focusing on mild AP, L-LOS subjects (34%) had 28 points per day slower decline; whereas, S-LOS group (13%) showed 34 points per day sharper decrease compared with I-LOS (53%; P < 0.001). We noticed an outlier subset with a median admission-PASS of 466 compared with 140 in the rest. Morphine equivalent dose constituted 80% of the total PASS in the outliers (median morphine equivalent dose score = 392), compared with only 25% in normal-range subjects (score = 33, P value < 0.001). Conclusions: This study highlighted that PASS can quantify AP activity. Significant differences in PASS trajectories were found both in revised Atlanta classification severity and LOS groups, which can be harnessed in AP monitoring/management (ClincialTrials.gov number, NCT03075618).