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Development and validation of a machine learning model to predict mortality risk in patients with COVID-19

Stachel, Anna; Daniel, Kwesi; Ding, Dan; Francois, Fritz; Phillips, Michael; Lighter, Jennifer
New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in workload,which created a strain on the staff and limited resources. Further, methods to better understand and characterise the predictors of morbidity and mortality was needed. METHODS: We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3395 hospital admissions with COVID-19. Multiple methods were applied, and final model was selected based on performance. A variable importance algorithm was used for interpretability, and understanding of performance and predictors was applied to the best model. We built a model with an area under the receiver operating characteristic curve of 83-97 to identify predictors and patients with high risk of mortality due to COVID-19. Oximetry, respirations, blood urea nitrogen, lymphocyte per cent, calcium, troponin and neutrophil percentage were important features, and key ranges were identified that contributed to a 50% increase in patients' mortality prediction score. With an increasing negative predictive value starting 0.90 after the second day of admission suggests we might be able to more confidently identify likely survivors DISCUSSION: This study serves as a use case of a machine learning methods with visualisations to aide clinicians with a better understanding of the model and predictors of mortality. CONCLUSION: As we continue to understand COVID-19, computer assisted algorithms might be able to improve the care of patients.
PMCID:8108129
PMID: 33962987
ISSN: 2632-1009
CID: 4866902

Hospitalizations for Chronic Disease and Acute Conditions in the Time of COVID-19

Blecker, Saul; Jones, Simon A; Petrilli, Christopher M; Admon, Andrew J; Weerahandi, Himali; Francois, Fritz; Horwitz, Leora I
PMID: 33104158
ISSN: 2168-6114
CID: 4645722

Trends in COVID-19 Risk-Adjusted Mortality Rates

Horwitz, Leora I; Jones, Simon A; Cerfolio, Robert J; Francois, Fritz; Greco, Joseph; Rudy, Bret; Petrilli, Christopher M
Early reports showed high mortality from coronavirus disease 2019 (COVID-19). Mortality rates have recently been lower, raising hope that treatments have improved. However, patients are also now younger, with fewer comorbidities. We explored whether hospital mortality was associated with changing demographics at a 3-hospital academic health system in New York. We examined in-hospital mortality or discharge to hospice from March through August 2020, adjusted for demographic and clinical factors, including comorbidities, admission vital signs, and laboratory results. Among 5,121 hospitalizations, adjusted mortality dropped from 25.6% (95% CI, 23.2-28.1) in March to 7.6% (95% CI, 2.5-17.8) in August. The standardized mortality ratio dropped from 1.26 (95% CI, 1.15-1.39) in March to 0.38 (95% CI, 0.12-0.88) in August, at which time the average probability of death (average marginal effect) was 18.2 percentage points lower than in March. Data from one health system suggest that mortality from COVID-19 is decreasing even after accounting for patient characteristics.
PMID: 33147129
ISSN: 1553-5606
CID: 4664172

Assessment of Racial/Ethnic Disparities in Hospitalization and Mortality in Patients With COVID-19 in New York City

Ogedegbe, Gbenga; Ravenell, Joseph; Adhikari, Samrachana; Butler, Mark; Cook, Tiffany; Francois, Fritz; Iturrate, Eduardo; Jean-Louis, Girardin; Jones, Simon A; Onakomaiya, Deborah; Petrilli, Christopher M; Pulgarin, Claudia; Regan, Seann; Reynolds, Harmony; Seixas, Azizi; Volpicelli, Frank Michael; Horwitz, Leora Idit
Importance/UNASSIGNED:Black and Hispanic populations have higher rates of coronavirus disease 2019 (COVID-19) hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored. Objective/UNASSIGNED:To compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics. Design, Setting, and Participants/UNASSIGNED:This retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status. Exposures/UNASSIGNED:Race and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients). Main Outcomes and Measures/UNASSIGNED:The likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death). Results/UNASSIGNED:Among 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9). Conclusions and Relevance/UNASSIGNED:In this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have critical illness or die after adjustment for comorbidity and neighborhood characteristics. This supports the assertion that existing structural determinants pervasive in Black and Hispanic communities may explain the disproportionately higher out-of-hospital deaths due to COVID-19 infections in these populations.
PMID: 33275153
ISSN: 2574-3805
CID: 4694552

Obesity in patients younger than 60 years is a risk factor for Covid-19 hospital admission

Lighter, Jennifer; Phillips, Michael; Hochman, Sarah; Sterling, Stephanie; Johnson, Diane; Francois, Fritz; Stachel, Anna
PMID: 32271368
ISSN: 1537-6591
CID: 4373122

Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study

Petrilli, Christopher M; Jones, Simon A; Yang, Jie; Rajagopalan, Harish; O'Donnell, Luke; Chernyak, Yelena; Tobin, Katie A; Cerfolio, Robert J; Francois, Fritz; Horwitz, Leora I
OBJECTIVE:To describe outcomes of people admitted to hospital with coronavirus disease 2019 (covid-19) in the United States, and the clinical and laboratory characteristics associated with severity of illness. DESIGN/METHODS:Prospective cohort study. SETTING/METHODS:Single academic medical center in New York City and Long Island. PARTICIPANTS/METHODS:5279 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection between 1 March 2020 and 8 April 2020. The final date of follow up was 5 May 2020. MAIN OUTCOME MEASURES/METHODS:Outcomes were admission to hospital, critical illness (intensive care, mechanical ventilation, discharge to hospice care, or death), and discharge to hospice care or death. Predictors included patient characteristics, medical history, vital signs, and laboratory results. Multivariable logistic regression was conducted to identify risk factors for adverse outcomes, and competing risk survival analysis for mortality. RESULTS:Of 11 544 people tested for SARS-Cov-2, 5566 (48.2%) were positive. After exclusions, 5279 were included. 2741 of these 5279 (51.9%) were admitted to hospital, of whom 1904 (69.5%) were discharged alive without hospice care and 665 (24.3%) were discharged to hospice care or died. Of 647 (23.6%) patients requiring mechanical ventilation, 391 (60.4%) died and 170 (26.2%) were extubated or discharged. The strongest risk for hospital admission was associated with age, with an odds ratio of >2 for all age groups older than 44 years and 37.9 (95% confidence interval 26.1 to 56.0) for ages 75 years and older. Other risks were heart failure (4.4, 2.6 to 8.0), male sex (2.8, 2.4 to 3.2), chronic kidney disease (2.6, 1.9 to 3.6), and any increase in body mass index (BMI) (eg, for BMI >40: 2.5, 1.8 to 3.4). The strongest risks for critical illness besides age were associated with heart failure (1.9, 1.4 to 2.5), BMI >40 (1.5, 1.0 to 2.2), and male sex (1.5, 1.3 to 1.8). Admission oxygen saturation of <88% (3.7, 2.8 to 4.8), troponin level >1 (4.8, 2.1 to 10.9), C reactive protein level >200 (5.1, 2.8 to 9.2), and D-dimer level >2500 (3.9, 2.6 to 6.0) were, however, more strongly associated with critical illness than age or comorbidities. Risk of critical illness decreased significantly over the study period. Similar associations were found for mortality alone. CONCLUSIONS:Age and comorbidities were found to be strong predictors of hospital admission and to a lesser extent of critical illness and mortality in people with covid-19; however, impairment of oxygen on admission and markers of inflammation were most strongly associated with critical illness and mortality. Outcomes seem to be improving over time, potentially suggesting improvements in care.
PMID: 32444366
ISSN: 1756-1833
CID: 4447142

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients

Razavian, Narges; Major, Vincent J; Sudarshan, Mukund; Burk-Rafel, Jesse; Stella, Peter; Randhawa, Hardev; Bilaloglu, Seda; Chen, Ji; Nguy, Vuthy; Wang, Walter; Zhang, Hao; Reinstein, Ilan; Kudlowitz, David; Zenger, Cameron; Cao, Meng; Zhang, Ruina; Dogra, Siddhant; Harish, Keerthi B; Bosworth, Brian; Francois, Fritz; Horwitz, Leora I; Ranganath, Rajesh; Austrian, Jonathan; Aphinyanaphongs, Yindalon
The COVID-19 pandemic has challenged front-line clinical decision-making, leading to numerous published prognostic tools. However, few models have been prospectively validated and none report implementation in practice. Here, we use 3345 retrospective and 474 prospective hospitalizations to develop and validate a parsimonious model to identify patients with favorable outcomes within 96 h of a prediction, based on real-time lab values, vital signs, and oxygen support variables. In retrospective and prospective validation, the model achieves high average precision (88.6% 95% CI: [88.4-88.7] and 90.8% [90.8-90.8]) and discrimination (95.1% [95.1-95.2] and 86.8% [86.8-86.9]) respectively. We implemented and integrated the model into the EHR, achieving a positive predictive value of 93.3% with 41% sensitivity. Preliminary results suggest clinicians are adopting these scores into their clinical workflows.
PMCID:7538971
PMID: 33083565
ISSN: 2398-6352
CID: 4640992

Colorectal Cancer Among Gout Patients Undergoing Colonoscopy

Slobodnick, Anastasia; Krasnokutsky, Svetlana; Lehmann, Robert A; Keenan, Robert T; Quach, Jonathan; Francois, Fritz; Pillinger, Michael H
BACKGROUND/OBJECTIVE/OBJECTIVE:The connection between gout and various cancers remains unclear. We assessed the relationship between gout and colorectal cancer in a population of veterans. METHODS:We reviewed the Computerized Patient Record System of the VA New York Harbor Health Care System to assess the 10-year occurrence of colorectal cancer in patients with gout undergoing colonoscopy, versus patients with osteoarthritis but no gout. RESULTS:Gout and osteoarthritis subjects were similar in age, ethnicity, body mass index, and smoking history. Among 581 gout and 598 osteoarthritis subjects with documented colonoscopies, the 10-year prevalence of colorectal cancer was significantly lower in gout (0.8%) versus osteoarthritis (3.7%) (p = 0.0008) patients. Differences in colorectal cancer rates remained significant after stratifying for nonsteroidal anti-inflammatory drug use. Among gout subjects, use of colchicine and/or allopurinol, as well as the presence/absence of concomitant osteoarthritis, did not influence colorectal cancer occurrence. On subanalysis, differences in colorectal cancer occurrence between gout and osteoarthritis subjects persisted among those who underwent diagnostic (0.5% in gout vs 4.6% in osteoarthritis subjects, p < 0.001) but not screening (0.9% in gout subjects vs 1% in osteoarthritis subjects, p = 1.0) colonoscopy. There was no significant difference in nonmalignant colorectal polyp occurrence between gout and osteoarthritis subjects. CONCLUSIONS:Subjects with gout had decreased colonoscopy-documented occurrence of colorectal cancer compared with osteoarthritis subjects, suggesting a possible protective effect.
PMID: 31764494
ISSN: 1536-7355
CID: 4215622

Bending the cost curve: time series analysis of a value transformation programme at an academic medical centre

Chatfield, Steven C; Volpicelli, Frank M; Adler, Nicole M; Kim, Kunhee Lucy; Jones, Simon A; Francois, Fritz; Shah, Paresh C; Press, Robert A; Horwitz, Leora I
BACKGROUND:Reducing costs while increasing or maintaining quality is crucial to delivering high value care. OBJECTIVE:To assess the impact of a hospital value-based management programme on cost and quality. DESIGN/METHODS:Time series analysis of non-psychiatric, non-rehabilitation, non-newborn patients discharged between 1 September 2011 and 31 December 2017 from a US urban, academic medical centre. INTERVENTION/METHODS:NYU Langone Health instituted an institution-wide programme in April 2014 to increase value of healthcare, defined as health outcomes achieved per dollar spent. Key features included joint clinical and operational leadership; granular and transparent cost accounting; dedicated project support staff; information technology support; and a departmental shared savings programme. MEASUREMENTS/METHODS:Change in variable direct costs; secondary outcomes included changes in length of stay, readmission and in-hospital mortality. RESULTS:The programme chartered 74 projects targeting opportunities in supply chain management (eg, surgical trays), operational efficiency (eg, discharge optimisation), care of outlier patients (eg, those at end of life) and resource utilisation (eg, blood management). The study cohort included 160 434 hospitalisations. Adjusted variable costs decreased 7.7% over the study period. Admissions with medical diagnosis related groups (DRG) declined an average 0.20% per month relative to baseline. Admissions with surgical DRGs had an early increase in costs of 2.7% followed by 0.37% decrease in costs per month. Mean expense per hospitalisation improved from 13% above median for teaching hospitals to 2% above median. Length of stay decreased by 0.25% per month relative to prior trends (95% CI -0.34 to 0.17): approximately half a day by the end of the study period. There were no significant changes in 30-day same-hospital readmission or in-hospital mortality. Estimated institutional savings after intervention costs were approximately $53.9 million. LIMITATIONS/CONCLUSIONS:Observational analysis. CONCLUSION/CONCLUSIONS:A systematic programme to increase healthcare value by lowering the cost of care without compromising quality is achievable and sustainable over several years.
PMID: 30877149
ISSN: 2044-5423
CID: 3908602

Decreased colorectal atypia among a cohort of gout patients

Slobodnick, A; Krasnokutsky, S; Lehmann, R A; Keenan, R T; Quach, J; Francois, F; Pillinger, M H
PMID: 28649919
ISSN: 1502-7732
CID: 2614562