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1.
Public Health Rep ; 136(2): 143-147, 2021.
Article in English | MEDLINE | ID: covidwho-1088392

ABSTRACT

The first few months of the coronavirus disease 2019 (COVID-19) pandemic challenged health care facilities worldwide in many ways. Inpatient and intensive care unit (ICU) beds were at a premium, and personnel shortages occurred during the initial peak of the pandemic. New York State was the hardest hit of all US states, with a high concentration of cases in New York City and, in particular, Bronx County. The governor of New York and leadership of hospitals in New York City called upon all available personnel to provide support and patient care during this health care crisis. This case study highlights the efforts of Jacobi Medical Center, located in the northeast Bronx, from March 1 through May 31, 2020, and its use of nontraditional health care personnel, including Department of Dentistry/OMFS (Oral and Maxillofacial Surgery) staff members, to provide a wide range of health care services. Dental staff members including ancillary personnel, residents, and attendings were redeployed and functioned throughout the facility. Dental anesthesiology residents provided medical services in support of their colleagues in a step-down COVID-19-dedicated ICU, providing intubation, ventilator management, and critical and palliative care. (Step-down units provide an intermediate level of care between ICUs and the general medical-surgical wards.) Clear communication of an acute need, a well-articulated mission, creative use of personnel, and dedicated staff members were evident during this challenging time. Although not routinely called upon to provide support in the medical and surgical inpatient areas, dental staff members may provide additional health care personnel during times of need.


Subject(s)
/therapy , Dentists , Anesthesiologists , Hospitals , Humans , Intensive Care Units/organization & administration , New York City/epidemiology , Pandemics , Workforce
2.
Chron Respir Dis ; 18: 1479973120986806, 2021.
Article in English | MEDLINE | ID: covidwho-1069523

ABSTRACT

We examined the relative contribution of pulmonary diseases (chronic obstructive pulmonary disease, asthma and sleep apnea) to mortality risks associated with Coronavirus Disease (COVID-19) independent of other medical conditions, health risks, and sociodemographic factors. Data were derived from a large US-based case series of patients with COVID-19, captured from a quaternary academic health network covering New York City and Long Island. From March 2 to May 24, 2020, 11,512 patients who were hospitalized were tested for COVID-19, with 4,446 (38.62%) receiving a positive diagnosis for COVID-19. Among those who tested positive, 959 (21.57%) died of COVID-19-related complications at the hospital. Multivariate-adjusted Cox proportional hazards modeling showed mortality risks were strongly associated with greater age (HR = 1.05; 95% CI: 1.04-1.05), ethnic minority (Asians, Non-Hispanic blacks, and Hispanics) (HR = 1.26; 95% CI, 1.10-1.44), low household income (HR = 1.29; 95% CI: 1.11, 1.49), and male sex (HR = 0.85; 95% CI: 0.74, 0.97). Higher mortality risks were also associated with a history of COPD (HR = 1.27; 95% CI: 1.02-1.58), obesity (HR = 1.19; 95% CI: 1.04-1.37), and peripheral artery disease (HR = 1.33; 95% CI: 1.05-1.69). Findings indicate patients with COPD had the highest odds of COVID-19 mortality compared with patients with pre-existing metabolic conditions, such as obesity, diabetes and hypertension. Sociodemographic factors including increased age, male sex, low household income, ethnic minority status were also independently associated with greater mortality risks.


Subject(s)
Asthma/complications , Hospital Mortality , Pulmonary Disease, Chronic Obstructive/complications , Sleep Apnea Syndromes/complications , Urban Health/statistics & numerical data , Adult , Aged , Aged, 80 and over , /diagnosis , Female , Humans , Male , Middle Aged , New York City/epidemiology , Proportional Hazards Models , Risk Factors , Socioeconomic Factors
3.
J Invasive Cardiol ; 33(2): E71-E76, 2021 02.
Article in English | MEDLINE | ID: covidwho-1063668

ABSTRACT

In Spring 2020, the United States epicenter of COVID-19 was New York City, in which the borough of the Bronx was particularly affected. This Fall, there has been a resurgence of COVID-19 in Europe and the Midwestern United States. We describe our experience transforming our cardiac catheterization laboratories to accommodate an influx of COVID-19 patients so as to provide other hospitals with a potential blueprint. We transformed our pre/postprocedural patient care areas into COVID-19 intensive care and step-down units and maintained emergent invasive care for ST-segment elevation myocardial infarction using existing space and personnel.


Subject(s)
Cardiac Catheterization/methods , Cardiology Service, Hospital , Coronary Care Units , Critical Care , Infection Control , Laboratories, Hospital/organization & administration , Organizational Innovation , ST Elevation Myocardial Infarction , /epidemiology , Cardiology Service, Hospital/organization & administration , Cardiology Service, Hospital/trends , Coronary Care Units/methods , Coronary Care Units/organization & administration , Critical Care/methods , Critical Care/organization & administration , Critical Care/trends , Humans , Infection Control/methods , Infection Control/organization & administration , New York City/epidemiology , Patient Care Team/organization & administration , Perioperative Care/methods , ST Elevation Myocardial Infarction/epidemiology , ST Elevation Myocardial Infarction/therapy
4.
JMIR Public Health Surveill ; 7(1): e25538, 2021 01 15.
Article in English | MEDLINE | ID: covidwho-1067579

ABSTRACT

BACKGROUND: Nowcasting approaches enhance the utility of reportable disease data for trend monitoring by correcting for delays, but implementation details affect accuracy. OBJECTIVE: To support real-time COVID-19 situational awareness, the New York City Department of Health and Mental Hygiene used nowcasting to account for testing and reporting delays. We conducted an evaluation to determine which implementation details would yield the most accurate estimated case counts. METHODS: A time-correlated Bayesian approach called Nowcasting by Bayesian Smoothing (NobBS) was applied in real time to line lists of reportable disease surveillance data, accounting for the delay from diagnosis to reporting and the shape of the epidemic curve. We retrospectively evaluated nowcasting performance for confirmed case counts among residents diagnosed during the period from March to May 2020, a period when the median reporting delay was 2 days. RESULTS: Nowcasts with a 2-week moving window and a negative binomial distribution had lower mean absolute error, lower relative root mean square error, and higher 95% prediction interval coverage than nowcasts conducted with a 3-week moving window or with a Poisson distribution. Nowcasts conducted toward the end of the week outperformed nowcasts performed earlier in the week, given fewer patients diagnosed on weekends and lack of day-of-week adjustments. When estimating case counts for weekdays only, metrics were similar across days when the nowcasts were conducted, with Mondays having the lowest mean absolute error of 183 cases in the context of an average daily weekday case count of 2914. CONCLUSIONS: Nowcasting using NobBS can effectively support COVID-19 trend monitoring. Accounting for overdispersion, shortening the moving window, and suppressing diagnoses on weekends-when fewer patients submitted specimens for testing-improved the accuracy of estimated case counts. Nowcasting ensured that recent decreases in observed case counts were not overinterpreted as true declines and supported officials in anticipating the magnitude and timing of hospitalizations and deaths and allocating resources geographically.


Subject(s)
/epidemiology , Public Health Surveillance/methods , Bayes Theorem , Humans , New York City/epidemiology , Retrospective Studies
5.
PLoS One ; 16(1): e0245514, 2021.
Article in English | MEDLINE | ID: covidwho-1067417

ABSTRACT

A growing body of literature suggests that restrictive public health measures implemented to control COVID-19 have had negative impacts on physical activity. We examined how Stay Home orders in Houston, New York City, and Seattle impacted outdoor physical activity patterns, measured by daily bicycle and pedestrian count data. We assessed changes in activity levels between the period before and during Stay Home orders. Across all three cities, we found significant changes in bicycle and pedestrian counts from the period before to the period during Stay Home orders. The direction of change varied by location, likely due to differing local contexts and outbreak progression. These results can inform policy around the use of outdoor public infrastructure as the COVID-19 pandemic continues.


Subject(s)
Bicycling , /prevention & control , Communicable Disease Control , Walking , Cities/epidemiology , Exercise , Humans , New York City/epidemiology , United States/epidemiology
6.
BMC Infect Dis ; 21(1): 78, 2021 Jan 18.
Article in English | MEDLINE | ID: covidwho-1067196

ABSTRACT

BACKGROUND: African-Americans/Blacks have suffered higher morbidity and mortality from COVID-19 than all other racial groups. This study aims to identify the causes of this health disparity, determine prognostic indicators, and assess efficacy of treatment interventions. METHODS: We performed a retrospective cohort study of clinical features and laboratory data of COVID-19 patients admitted over a 52-day period at the height of the pandemic in the United States. This study was performed at an urban academic medical center in New York City, declared a COVID-only facility, serving a majority Black population. RESULTS: Of the 1103 consecutive patients who tested positive for COVID-19, 529 required hospitalization and were included in the study. 88% of patients were Black; and a majority (52%) were 61-80 years old with a mean body mass index in the "obese" range. 98% had one or more comorbidities. Hypertension was the most common (79%) pre-existing condition followed by diabetes mellitus (56%) and chronic kidney disease (17%). Patients with chronic kidney disease who received hemodialysis were found to have lower mortality, than those who did not receive it, suggesting benefit from hemodialysis Age > 60 years and coronary artery disease were independent predictors of mortality in multivariate analysis. Cox proportional hazards modeling for time to death demonstrated a significantly high ratio for COPD/Asthma, and favorable effects on outcomes for pre-admission ACE inhibitors and ARBs. CRP (180, 283 mg/L), LDH (551, 638 U/L), glucose (182, 163 mg/dL), procalcitonin (1.03, 1.68 ng/mL), and neutrophil:lymphocyte ratio (8.3:10.0) were predictive of mortality on admission and at 48-96 h. Of the 529 inpatients 48% died, and one third of them died within the first 3 days of admission. 159/529patients received invasive mechanical ventilation, of which 86% died and of the remaining 370 patients, 30% died. CONCLUSIONS: COVID-19 patients in our predominantly Black neighborhood had higher in-hospital mortality, likely due to higher prevalence of comorbidities. Early dialysis and pre-admission intake of ACE inhibitors/ARBs improved patient outcomes. Early escalation of care based on comorbidities and key laboratory indicators is critical for improving outcomes in African-American patients.


Subject(s)
African Americans/statistics & numerical data , /mortality , Adult , Aged , Aged, 80 and over , Angiotensin Receptor Antagonists , Angiotensin-Converting Enzyme Inhibitors , /therapy , Comorbidity , Diabetes Mellitus/epidemiology , Female , Hospital Mortality/ethnology , Hospitalization , Humans , Hypertension/epidemiology , Male , Middle Aged , New York City/epidemiology , Pandemics/statistics & numerical data , Respiration, Artificial/mortality , Retrospective Studies
7.
JAMA Netw Open ; 4(2): e2037069, 2021 02 01.
Article in English | MEDLINE | ID: covidwho-1061184

ABSTRACT

Importance: New York State has been an epicenter for both the US coronavirus disease 2019 (COVID-19) and HIV/AIDS epidemics. Persons living with diagnosed HIV may be more prone to COVID-19 infection and severe outcomes, yet few studies have assessed this possibility at a population level. Objective: To evaluate the association between HIV diagnosis and COVID-19 diagnosis, hospitalization, and in-hospital death in New York State. Design, Setting, and Participants: This cohort study, conducted in New York State, including New York City, between March 1 and June 15, 2020, matched data from HIV surveillance, COVID-19 laboratory-confirmed diagnoses, and hospitalization databases to provide a full population-level comparison of COVID-19 outcomes between persons living with diagnosed HIV and persons living without diagnosed HIV. Exposures: Diagnosis of HIV infection through December 31, 2019. Main Outcomes and Measures: The main outcomes were COVID-19 diagnosis, hospitalization, and in-hospital death. COVID-19 diagnoses, hospitalizations, and in-hospital death rates comparing persons living with diagnosed HIV with persons living without dianosed HIV were computed, with unadjusted rate ratios and indirect standardized rate ratios (sRR), adjusting for sex, age, and region. Adjusted rate ratios (aRRs) for outcomes specific to persons living with diagnosed HIV were assessed by age, sex, region, race/ethnicity, transmission risk, and CD4+ T-cell count-defined HIV disease stage, using Poisson regression models. Results: A total of 2988 persons living with diagnosed HIV (2109 men [70.6%]; 2409 living in New York City [80.6%]; mean [SD] age, 54.0 [13.3] years) received a diagnosis of COVID-19. Of these persons living with diagnosed HIV, 896 were hospitalized and 207 died in the hospital through June 15, 2020. After standardization, persons living with diagnosed HIV and persons living without diagnosed HIV had similar diagnosis rates (sRR, 0.94 [95% CI, 0.91-0.97]), but persons living with diagnosed HIV were hospitalized more than persons living without diagnosed HIV, per population (sRR, 1.38 [95% CI, 1.29-1.47]) and among those diagnosed (sRR, 1.47 [95% CI, 1.37-1.56]). Elevated mortality among persons living with diagnosed HIV was observed per population (sRR, 1.23 [95% CI, 1.07-1.40]) and among those diagnosed (sRR, 1.30 [95% CI, 1.13-1.48]) but not among those hospitalized (sRR, 0.96 [95% CI, 0.83-1.09]). Among persons living with diagnosed HIV, non-Hispanic Black individuals (aRR, 1.59 [95% CI, 1.40-1.81]) and Hispanic individuals (aRR, 2.08 [95% CI, 1.83-2.37]) were more likely to receive a diagnosis of COVID-19 than White individuals, but they were not more likely to be hospitalized once they received a diagnosis or to die once hospitalized. Hospitalization risk increased with disease progression to HIV stage 2 (aRR, 1.29 [95% CI, 1.11-1.49]) and stage 3 (aRR, 1.69 [95% CI, 1.38-2.07]) relative to stage 1. Conclusions and Relevance: In this cohort study, persons living with diagnosed HIV experienced poorer COVID-related outcomes relative to persons living without diagnosed HIV; Previous HIV diagnosis was associated with higher rates of severe disease requiring hospitalization, and hospitalization risk increased with progression of HIV disease stage.


Subject(s)
/epidemiology , Comorbidity , HIV Infections/epidemiology , Hospital Mortality , Hospitalization , Hospitals , Pandemics , Adult , African Americans , Aged , Cohort Studies , Epidemics , European Continental Ancestry Group , Female , HIV Infections/complications , Hispanic Americans , Humans , Male , Middle Aged , New York/epidemiology , New York City/epidemiology
8.
BMJ Open ; 11(1): e044526, 2021 01 31.
Article in English | MEDLINE | ID: covidwho-1060157

ABSTRACT

OBJECTIVES: To determine if obesity and diabetes are risk factors for severe outcomes in COVID-19 and to compare patient outcomes in those two conditions. DESIGN: Retrospective cohort study. SETTING: Urban tertiary care center in New York City. PARTICIPANTS: 302 patients admitted in an inpatient setting, ≥18 years old, with a laboratory-confirmed diagnosis of COVID-19 via nasal PCR swab were randomly selected. Patients were separated into two cohorts based on their body mass index and hemoglobin A1c. 150 patients were placed in the non-obese, non-diabetic cohort and 152 patients were placed in the corresponding cohort (obesity alone, obesity and diabetes, and diabetes alone). MEASUREMENTS: Primary outcomes were development of acute kidney injury, commencement of renal replacement therapy, aminotransferase elevation, troponin elevation, lactic acidosis, development of septic shock, use of vasopressors, presence of acute respiratory distress syndrome (ARDS) and intubation. The secondary outcomes were length of stay in days and mortality. RESULTS: Patients with obesity and/or diabetes were more likely to develop ARDS (79 patients vs 57 patients, p<0.0001) and to be intubated (71 patients vs 45 patients, p=0.0031). Patients with obesity and/or diabetes were more likely to require vasopressors (60 patients vs 41 patients, p=0.0284) and to develop lactic acidosis (median 3.15 mmol/L, IQR 1.8 to 5.2 mmol/L, p=0.0432). When comparing patients with diabetes with and without obesity against patients with obesity alone, they were more likely to develop ARDS (87.5%, p=0.0305). Despite these findings, there was no difference in mortality. CONCLUSIONS: In patients hospitalised with COVID-19, those with obesity and/or diabetes were more likely to suffer severe complications, but had negligible differences in mortality. This highlights the importance of close monitoring of patients with these conditions and additional areas of research needed to explain the mortality findings.


Subject(s)
Diabetes Mellitus , Glycated Hemoglobin A/analysis , Obesity , /isolation & purification , Acute Kidney Injury/diagnosis , Acute Kidney Injury/etiology , Body Mass Index , /complications , /therapy , Comorbidity , Diabetes Mellitus/diagnosis , Diabetes Mellitus/epidemiology , Female , Humans , Male , Middle Aged , Mortality , New York City/epidemiology , Obesity/diagnosis , Obesity/epidemiology , Outcome and Process Assessment, Health Care , Random Allocation , Respiration, Artificial/statistics & numerical data , Retrospective Studies , Risk Assessment/methods , Risk Assessment/statistics & numerical data , Risk Factors
9.
J Zoo Wildl Med ; 51(4): 733-744, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-1041161

ABSTRACT

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged as the cause of a global pandemic in 2019-2020. In March 2020, New York City became the epicenter in the United States for the pandemic. On 27 March 2020, a Malayan tiger (Panthera tigris jacksoni) at the Bronx Zoo in New York City developed a cough and wheezing with subsequent inappetence. Over the next week, an additional Malayan tiger and two Amur tigers (Panthera tigris altaica) in the same building and three lions (Panthera leo krugeri) in a separate building also became ill. The index case was anesthetized for diagnostic workup. Physical examination and bloodwork results were unremarkable. Thoracic radiography and ultrasonography revealed a bronchial pattern with peribronchial cuffing and mild lung consolidation with alveolar-interstitial syndrome, respectively. SARS-CoV-2 RNA was identified by real-time, reverse transcriptase PCR (rRT-PCR) on oropharyngeal and nasal swabs and tracheal wash fluid. Cytologic examination of tracheal wash fluid revealed necrosis, and viral RNA was detected in necrotic cells by in situ hybridization, confirming virus-associated tissue damage. SARS-CoV-2 was isolated from the tracheal wash fluid of the index case, as well as the feces from one Amur tiger and one lion. Fecal viral RNA shedding was confirmed in all seven clinical cases and an asymptomatic Amur tiger. Respiratory signs abated within 1-5 days for most animals, although they persisted intermittently for 16 days in the index case. Fecal RNA shedding persisted for as long as 35 days beyond cessation of respiratory signs. This case series describes the clinical presentation, diagnostic evaluation, and management of tigers and lions infected with SARS-CoV-2 and describes the duration of viral RNA fecal shedding in these cases. This report documents the first known natural transmission of SARS-CoV-2 from humans to nondomestic felids.


Subject(s)
/veterinary , Feces/virology , Lions/virology , Tigers/virology , Animals , Animals, Zoo , Bacterial Proteins/genetics , Bacterial Proteins/isolation & purification , /epidemiology , DNA-Binding Proteins/genetics , DNA-Binding Proteins/isolation & purification , New York City/epidemiology , Transcription Factors/genetics , Transcription Factors/isolation & purification
10.
Heart Rhythm ; 18(2): 215-218, 2021 02.
Article in English | MEDLINE | ID: covidwho-1032446

ABSTRACT

BACKGROUND: Increased incidence of out-of-hospital sudden death (OHSD) has been reported during the coronavirus 2019 (COVID-19) pandemic. New York City (NYC) represents a unique opportunity to examine the epidemiologic association between the two given the variable regional distribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in its highly diverse neighborhoods. OBJECTIVE: The purpose of this study was to examine the association between OHSD and SARS-CoV-2 epidemiologic burden during the first COVID-19 pandemic across the highly diverse neighborhoods of NYC. METHODS: The incidences of OHSD between March 20 and April 22, 2019, and between March 20 and April 22, 2020, as reported by the Fire Department of New York were obtained. As a surrogate for viral epidemiologic burden, we used percentage of positive SARS-CoV-2 antibody tests performed between March 3 and August 20, 2020. Data were reported separately for the 176 zip codes of NYC. Correlation analysis and regression analysis were performed between the 2 measures to examine association. RESULTS: Incidence of OHSD per 10,000 inhabitants and percentage of SARS-CoV-2 seroconversion were highly variable across NYC neighborhoods, varying from 0.0 to 22.9 and 12.4% to 50.9%, respectively. Correlation analysis showed a moderate positive correlation between neighborhood data on OHSD and percentage of positive antibody tests to SARS-CoV-2 (Spearman ρ 0.506; P <.001). Regression analysis showed that seroconversion to SARS-CoV-2 and OHSD in 2019 were independent predictors for OHSD during the first epidemic surge in NYC (R2 = 0.645). CONCLUSION: The association in geographic distribution between OHSD and SARS-CoV-2 epidemiologic burden suggests either a causality between the 2 syndromes or the presence of local determinants affecting both measures in a similar fashion.


Subject(s)
/immunology , Death, Sudden/epidemiology , Seroconversion , /epidemiology , Female , Humans , Incidence , Male , New York City/epidemiology , Pandemics
11.
Int J Obes (Lond) ; 44(9): 1832-1837, 2020 09.
Article in English | MEDLINE | ID: covidwho-1023848

ABSTRACT

BACKGROUND: Obesity is an epidemic in New York City, the global epicenter of the coronavirus pandemic. Previous studies suggest that obesity is a possible risk factor for adverse outcomes in COVID-19. OBJECTIVE: To elucidate the association between obesity and COVID-19 outcomes. DESIGN: Retrospective cohort study of COVID-19 hospitalized patients tested between March 10 and April 13, 2020. SETTING: SUNY Downstate Health Sciences University, a COVID-only hospital in New York. PARTICIPANTS: In total, 684 patients were tested for COVID-19 and 504 were analyzed. Patients were categorized into three groups by BMI: normal (BMI 18.50-24.99), overweight (BMI 25.00-29.99), and obese (BMI ≥ 30.00). MEASUREMENTS: Primary outcome was 30-day in-hospital mortality, and secondary outcomes were intubation, acute kidney injury (AKI), acute respiratory distress syndrome (ARDS), and acute cardiac injury (ACI). RESULTS: There were 139 patients (27%) with normal BMI, 150 patients who were overweight (30%), and 215 patients with obesity (43%). After controlling for age, gender, diabetes, hypertension, and qSOFA score, there was a significantly increased risk of mortality in the overweight (RR 1.4, 95% CI 1.1-1.9) and obese groups (RR 1.3, 95% CI 1.0-1.7) compared with those with normal BMI. Similarly, there was a significantly increased relative risk for intubation in the overweight (RR 2.0, 95% CI 1.2-3.3) and obese groups (RR 2.4, 95% CI 1.5-4.0) compared with those with normal BMI. Obesity did not affect rates of AKI, ACI, or ARDS. Furthermore, obesity appears to significantly increase the risk of mortality in males (RR 1.4, 95% CI 1.0-2.0, P = 0.03), but not in females (RR 1.2, 95% CI 0.77-1.9, P = 0.40). CONCLUSION: This study reveals that patients with overweight and obesity who have COVID-19 are at increased risk for mortality and intubation compared to those with normal BMI. These findings support the hypothesis that obesity is a risk factor for COVID-19 complications and should be a consideration in management of COVID-19.


Subject(s)
Coronavirus Infections , Obesity/epidemiology , Pandemics , Pneumonia, Viral , Acute Kidney Injury/epidemiology , Adult , Aged , Betacoronavirus , Body Mass Index , Comorbidity , Coronavirus Infections/complications , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Diabetes Mellitus, Type 2/epidemiology , Female , Humans , Hypertension/epidemiology , Intubation, Intratracheal/statistics & numerical data , Male , Middle Aged , New York City/epidemiology , Overweight/epidemiology , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , Retrospective Studies , Risk Factors
13.
J Grad Med Educ ; 12(6): 682-685, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-1005985

ABSTRACT

Background: Montefiore Medical Center (MMC) is a large tertiary care center in the Bronx, New York City, with 245 internal medicine residents. Beginning on February 29, 2020, residents became ill with COVID-19-like illness (CLI), which required absence from work. There was initially a shortage of personal protective equipment and delays in SARS-CoV-2 testing, which gradually improved during March and April 2020. Objective: We evaluated the relationship between CLI-related work absence rates of internal medicine residents and MMC's COVID-19 hospital census over time. Methods: Data on resident work absence between February 29 and May 22 were reviewed along with MMC's COVID-19 hospital census data. To determine the effect of patient exposure on resident CLI incidence, we compared the mean incidence of CLI per patient exposure days (PED = daily hospital census × days pre- or post-peak) before and after peak COVID-19 hospital census. Results: Forty-two percent (103 of 245) of internal medicine residents were absent from work, resulting in 875 missed workdays. At the peak of resident work absence, 16% (38 of 245) were out sick. Residents were absent for a median of 7 days (IQR 6-9.5 days). Mean resident CLI incidence per PED (CLI/PED) was 13.9-fold lower post-peak compared to pre-peak (P = .003). Conclusions: At the beginning of the COVID-19 pandemic in New York City, a large portion of internal medicine residents at this single center became ill. However, the incidence of CLI decreased over time, despite ongoing exposure to patients with COVID-19.


Subject(s)
/epidemiology , Internship and Residency/statistics & numerical data , Sick Leave/statistics & numerical data , Academic Medical Centers , Humans , Infectious Disease Transmission, Patient-to-Professional , Internal Medicine , Internship and Residency/methods , New York City/epidemiology , Occupational Exposure , Personnel Staffing and Scheduling , Retrospective Studies
14.
J Intensive Care Med ; 36(2): 233-240, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1004273

ABSTRACT

PURPOSE: Montefiore Medical Center (MMC) in the Bronx, New York, was subjected to an unprecedented surge of critically ill patients with COVID-19 disease during the initial outbreak of the pandemic in New York State in the spring of 2020. It is important to describe our experience in order to assist hospitals in other areas of the country that may soon be subjected to similar surges. MATERIALS AND METHODS: We retrospectively reviewed the expansion of critical care medicine services at Montefiore during the COVID-19 surge in terms of space, staff, stuff, and systems. In addition, we report on a debriefing session held with a multidisciplinary group of frontline CCM providers at Montefiore. FINDINGS: The surge of critically ill patients from COVID-19 disease necessitated a tripling of critical care bed capacity at (MMC), with attendant increased needs for staffing, equipment, and systematic innovations to increase efficiency and effectiveness. Feedback from a multidisciplinary group of frontline providers revealed multiple opportunities for improvement for the next potential surge at MMC as well as guidance for other hospitals. CONCLUSIONS: Given increasing cases and burden of critical illness from COVID-19 across the US, engineering safe and effective expansions of critical care capacity will be crucial. We hope that our description of what worked and what did not at MMC will help guide other hospitals in their pandemic preparedness.


Subject(s)
/epidemiology , Critical Care , Critical Illness/epidemiology , Critical Illness/therapy , Intensive Care Units/organization & administration , Female , Humans , Male , New York City/epidemiology , Pandemics , Retrospective Studies
15.
Sci Rep ; 10(1): 22380, 2020 12 24.
Article in English | MEDLINE | ID: covidwho-997945

ABSTRACT

The mental health effects of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the Coronavirus Disease 2019 (COVID-19) pandemic on postpartum women are of increasing concern among mental health practitioners. To date, only a handful of studies have explored the emotional impact of the pandemic surrounding pregnancy and none have investigated the consequence of pandemic-related social restrictions on the postpartum mood of those living among different socioeconomic status (SES). All postpartum patients appearing to the Mount Sinai Health System for their postpartum appointment between January 2, 2020 and June 30, 2020, corresponding to before and during pandemic imposed social restrictions, were screened for mood symptomatology using the Edinburgh Postnatal Depression Scale (EPDS). Each patient's socioeconomic status (high/low) was determined by their location of clinical service. A total of 516 postpartum patients were screened. While no differences in EPDS scores were observed by SES prior to social restrictions (U = 7956.0, z = - 1.05, p = .293), a significant change in mood symptomatology was observed following COVID-19 restrictions (U = 4895.0, z = - 3.48, p < .001), with patients living in lower SES reporting significantly less depression symptomatology (U = 9209.0, z = - 4.56, p < .001). There was no change in symptomatology among patients of higher SES (U = 4045.5, z = - 1.06, p = .288). Postpartum depression, the most common complication of childbearing, is a prevalent, cross-cultural disorder with significant morbidity. The observed differences in postpartum mood between patients of different SES in the context of temporarily imposed COVID-19-related social restrictions present a unique opportunity to better understand the specific health and social support needs of postpartum patients living in urban economic poverty. Given that maternal mental illness has negative long-term developmental implications for the offspring and that poor mental health reinforces the poverty cycle, future health policy specifically directed towards supporting postpartum women living in low SES by ameliorating some of the early maternal burdens associated with balancing employment-family-childcare demands may assist in interrupting this cycle while simultaneously improving the long-term outcomes of their offspring.


Subject(s)
Affect , /prevention & control , Depression, Postpartum/epidemiology , Pandemics/prevention & control , Postpartum Period/psychology , Quarantine/psychology , Social Class , Adolescent , Adult , Cohort Studies , Depression, Postpartum/diagnosis , Female , Humans , Mental Health , New York City/epidemiology , Prevalence , Psychiatric Status Rating Scales , Young Adult
16.
Pediatr Blood Cancer ; 68(3): e28857, 2021 03.
Article in English | MEDLINE | ID: covidwho-986385

ABSTRACT

Childhood cancer survivors are at increased risk for treatment-related late effects; data are lacking on how coronavirus disease 2019 (COVID-19) infection impacts this cohort. We assessed COVID-19-related symptoms, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgG seroprevalence, and rate of COVID-19-related hospitalization among 321 asymptomatic survivors of childhood cancer or transplantation seen for routine long-term follow-up between May and September 2020 in a New York City tertiary cancer center. While 10.9% (n = 35) reported possible COVID-19-related symptoms, 7.8% (n = 20) of those tested had positive SARS-CoV-2 IgG, and one patient (0.3%) required COVID-19-related hospitalization. This report suggests that childhood cancer survivors appear to be at relatively low risk for COVID-19 complications.


Subject(s)
Antibodies, Viral/blood , Cancer Survivors/statistics & numerical data , Hematologic Neoplasms/therapy , Adolescent , Child , Child, Preschool , Female , Hematopoietic Stem Cell Transplantation/statistics & numerical data , Humans , Immunoglobulin G/blood , Infant , Male , New York City/epidemiology , Retrospective Studies , Risk , /isolation & purification
17.
J Invasive Cardiol ; 33(2): E71-E76, 2021 02.
Article in English | MEDLINE | ID: covidwho-984012

ABSTRACT

In Spring 2020, the United States epicenter of COVID-19 was New York City, in which the borough of the Bronx was particularly affected. This Fall, there has been a resurgence of COVID-19 in Europe and the Midwestern United States. We describe our experience transforming our cardiac catheterization laboratories to accommodate an influx of COVID-19 patients so as to provide other hospitals with a potential blueprint. We transformed our pre/postprocedural patient care areas into COVID-19 intensive care and step-down units and maintained emergent invasive care for ST-segment elevation myocardial infarction using existing space and personnel.


Subject(s)
Cardiac Catheterization/methods , Cardiology Service, Hospital , Coronary Care Units , Critical Care , Infection Control , Laboratories, Hospital/organization & administration , Organizational Innovation , ST Elevation Myocardial Infarction , /epidemiology , Cardiology Service, Hospital/organization & administration , Cardiology Service, Hospital/trends , Coronary Care Units/methods , Coronary Care Units/organization & administration , Critical Care/methods , Critical Care/organization & administration , Critical Care/trends , Humans , Infection Control/methods , Infection Control/organization & administration , New York City/epidemiology , Patient Care Team/organization & administration , Perioperative Care/methods , ST Elevation Myocardial Infarction/epidemiology , ST Elevation Myocardial Infarction/therapy
19.
Obstet Gynecol ; 136(2): 291-299, 2020 08.
Article in English | MEDLINE | ID: covidwho-980830

ABSTRACT

OBJECTIVE: To characterize symptoms and disease severity among pregnant women with coronavirus disease 2019 (COVID-19) infection, along with laboratory findings, imaging, and clinical outcomes. METHODS: Pregnant women with COVID-19 infection were identified at two affiliated hospitals in New York City from March 13 to April 19, 2020, for this case series study. Women were diagnosed with COVID-19 infection based on either universal testing on admission or testing because of COVID-19-related symptoms. Disease was classified as either 1) asymptomatic or mild or 2) moderate or severe based on dyspnea, tachypnea, or hypoxia. Clinical and demographic risk factors for moderate or severe disease were analyzed and calculated as odds ratios (ORs) with 95% CIs. Laboratory findings and associated symptoms were compared between those with mild or asymptomatic and moderate or severe disease. The clinical courses and associated complications of women hospitalized with moderate and severe disease are described. RESULTS: Of 158 pregnant women with COVID-19 infection, 124 (78%) had mild or asymptomatic disease and 34 (22%) had moderate or severe disease. Of 15 hospitalized women with moderate or severe disease, 10 received respiratory support with supplemental oxygen and one required intubation. Women with moderate or severe disease had a higher likelihood of having an underlying medical comorbidity (50% vs 27%, OR 2.76, 95% CI 1.26-6.02). Asthma was more common among those with moderate or severe disease (24% vs 8%, OR 3.51, 95% CI 1.26-9.75). Women with moderate or severe disease were significantly more likely to have leukopenia and elevated aspartate transaminase and ferritin. Women with moderate or severe disease were at significantly higher risk for cough and chest pain and pressure. Nine women received ICU or step-down-level care, including four for 9 days or longer. Two women underwent preterm delivery because their clinical status deteriorated. CONCLUSION: One in five pregnant women who contracted COVID-19 infection developed moderate or severe disease, including a small proportion with prolonged critical illness who received ICU or step-down-level care.


Subject(s)
Coronavirus Infections/epidemiology , Critical Illness/therapy , Pneumonia, Viral/epidemiology , Pregnancy Complications, Infectious/epidemiology , Adult , Betacoronavirus , Comorbidity , Coronavirus Infections/physiopathology , Dyspnea/etiology , Female , Humans , Hypoxia/etiology , Intensive Care Units , New York City/epidemiology , Pandemics , Pneumonia, Viral/physiopathology , Pregnancy , Pregnancy Complications, Infectious/physiopathology , Pregnancy Complications, Infectious/virology , Premature Birth/epidemiology , Risk Factors , Severity of Illness Index , Tachypnea/etiology , Young Adult
20.
J Med Internet Res ; 22(11): e24018, 2020 11 06.
Article in English | MEDLINE | ID: covidwho-979821

ABSTRACT

BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. OBJECTIVE: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. METHODS: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. RESULTS: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. CONCLUSIONS: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.


Subject(s)
Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Machine Learning/standards , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Acute Kidney Injury/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , Betacoronavirus , Cohort Studies , Electronic Health Records , Female , Hospital Mortality , Hospitalization/statistics & numerical data , Hospitals , Humans , Male , Middle Aged , New York City/epidemiology , Pandemics , Prognosis , ROC Curve , Risk Assessment/methods , Risk Assessment/standards , Young Adult
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