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1.
BMC Endocr Disord ; 22(1): 13, 2022 Jan 06.
Article in English | MEDLINE | ID: covidwho-1613234

ABSTRACT

BACKGROUND: Research regarding the association between severe obesity and in-hospital mortality is inconsistent. We evaluated the impact of body mass index (BMI) levels on mortality in the medical wards. The analysis was performed separately before and during the COVID-19 pandemic. METHODS: We retrospectively retrieved data of adult patients admitted to the medical wards at the Mount Sinai Health System in New York City. The study was conducted between January 1, 2011, to March 23, 2021. Patients were divided into two sub-cohorts: pre-COVID-19 and during-COVID-19. Patients were then clustered into groups based on BMI ranges. A multivariate logistic regression analysis compared the mortality rate among the BMI groups, before and during the pandemic. RESULTS: Overall, 179,288 patients were admitted to the medical wards and had a recorded BMI measurement. 149,098 were admitted before the COVID-19 pandemic and 30,190 during the pandemic. Pre-pandemic, multivariate analysis showed a "J curve" between BMI and mortality. Severe obesity (BMI > 40) had an aOR of 0.8 (95% CI:0.7-1.0, p = 0.018) compared to the normal BMI group. In contrast, during the pandemic, the analysis showed a "U curve" between BMI and mortality. Severe obesity had an aOR of 1.7 (95% CI:1.3-2.4, p < 0.001) compared to the normal BMI group. CONCLUSIONS: Medical ward patients with severe obesity have a lower risk for mortality compared to patients with normal BMI. However, this does not apply during COVID-19, where obesity was a leading risk factor for mortality in the medical wards. It is important for the internal medicine physician to understand the intricacies of the association between obesity and medical ward mortality.


Subject(s)
Body Mass Index , COVID-19/mortality , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Obesity/physiopathology , SARS-CoV-2/isolation & purification , Aged , COVID-19/epidemiology , COVID-19/pathology , COVID-19/virology , Case-Control Studies , Female , Humans , Male , Middle Aged , New York City/epidemiology , Prognosis , Retrospective Studies , Risk Factors , Survival Rate
2.
Clin J Am Soc Nephrol ; 16(8): 1158-1168, 2021 08.
Article in English | MEDLINE | ID: covidwho-1311348

ABSTRACT

BACKGROUND AND OBJECTIVES: AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Using data from adult patients hospitalized with COVID-19 from five hospitals from the Mount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to the Mount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission. RESULTS: A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93-0.98) and area under the precision-recall curve (AUPRC; range of 0.78-0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85-0.87, and AUPRC range of 0.27-0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model's prediction. CONCLUSIONS: An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_07_09_CJN17311120.mp3.


Subject(s)
Acute Kidney Injury/therapy , COVID-19/complications , Machine Learning , Renal Dialysis , SARS-CoV-2 , Acute Kidney Injury/mortality , COVID-19/mortality , Hospitalization , Humans
3.
Obesity (Silver Spring) ; 29(9): 1547-1553, 2021 09.
Article in English | MEDLINE | ID: covidwho-1212774

ABSTRACT

OBJECTIVE: Obesity is associated with severe coronavirus disease 2019 (COVID-19) infection. Disease severity is associated with a higher COVID-19 antibody titer. The COVID-19 antibody titer response of patients with obesity versus patients without obesity was compared. METHODS: The data of individuals tested for COVID-19 serology at the Mount Sinai Health System in New York City between March 1, 2020, and December 14, 2021, were retrospectively retrieved. The primary outcome was peak antibody titer, assessed as a binary variable (1:2,880, which was the highest detected titer, versus lower than 1:2,880). In patients with a positive serology test, peak titer rates were compared between BMI groups (<18.5, 18.5 to 25, 25 to 30, 30 to 40, and ≥40 kg/m2 ). A multivariable logistic regression model was used to analyze the independent association between different BMI groups and peak titer. RESULTS: Overall, 39,342 individuals underwent serology testing and had BMI measurements. A positive serology test was present in 12,314 patients. Peak titer rates were associated with obesity (BMI < 18.5 [34.5%], 18.5 to 25 [29.2%], 25 to 30 [37.7%], 30 to 40 [44.7%], ≥40 [52.0%]; p < 0.001). In a multivariable analysis, severe obesity had the highest adjusted odds ratio for peak titer (95% CI: 2.1-3.0). CONCLUSION: COVID-19 neutralizing antibody titer is associated with obesity. This has implications on the understanding of the role of obesity in COVID-19 severity.


Subject(s)
Antibodies, Viral/blood , COVID-19 , Obesity , Antibodies, Neutralizing/blood , COVID-19/immunology , Humans , Logistic Models , Obesity/complications , Retrospective Studies
5.
J Am Soc Nephrol ; 32(1): 151-160, 2021 01.
Article in English | MEDLINE | ID: covidwho-1080996

ABSTRACT

BACKGROUND: Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the United States is not well described. METHODS: This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. RESULTS: Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patients with AKI required dialysis. The proportions with stages 1, 2, or 3 AKI were 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. CONCLUSIONS: AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.


Subject(s)
Acute Kidney Injury/etiology , COVID-19/complications , SARS-CoV-2 , Acute Kidney Injury/epidemiology , Acute Kidney Injury/therapy , Acute Kidney Injury/urine , Aged , Aged, 80 and over , COVID-19/mortality , Female , Hematuria/etiology , Hospital Mortality , Hospitals, Private/statistics & numerical data , Hospitals, Urban/statistics & numerical data , Humans , Incidence , Inpatients , Leukocytes , Male , Middle Aged , New York City/epidemiology , Proteinuria/etiology , Renal Dialysis , Retrospective Studies , Treatment Outcome , Urine/cytology
6.
Lung ; 198(5): 771-775, 2020 10.
Article in English | MEDLINE | ID: covidwho-756086

ABSTRACT

PURPOSE: To investigate whether sarcoidosis patients infected with SARS-CoV-2 are at risk for adverse disease outcomes. STUDY DESIGN AND METHODS: This retrospective study was conducted in five hospitals within the Mount Sinai Health System during March 1, 2020 to July 29, 2020. All patients diagnosed with COVID-19 were included in the study. We identified sarcoidosis patients who met diagnostic criteria for sarcoidosis according to accepted guidelines. An adverse disease outcome was defined as the presence of intubation and mechanical ventilation or in-hospital mortality. In sarcoidosis patients, we reported (when available) the results of pulmonary function testing measured within 3 years prior to the time of SARS­CoV­2 infection. A multivariable logistic regression model was used to generate an adjusted odds ratio (aOR) to evaluate sarcoidosis as a risk factor for an adverse outcome. The same model was used to analyze sarcoidosis patients with moderate and/or severe impairment in pulmonary function. RESULTS: The study included 7337 patients, 37 of whom (0.5%) had sarcoidosis. The crude rate of developing an adverse outcome was significantly higher in patients with moderately and/or severely impaired pulmonary function (9/14 vs. 3/23, p = 0.003). While the diagnosis of sarcoidosis was not independently associated with risk of an adverse event, (aOR 1.8, 95% CI 0.9-3.6), the diagnosis of sarcoidosis in patients with moderately and/or severely impaired pulmonary function was associated with an adverse outcome (aOR 7.8, 95% CI 2.4-25.8). CONCLUSION: Moderate or severe impairment in pulmonary function is associated with mortality in sarcoidosis patients infected with SARS­CoV­2.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections , Pandemics , Pneumonia, Viral , Respiratory Function Tests/methods , Sarcoidosis, Pulmonary , COVID-19 , Comorbidity , Coronavirus Infections/mortality , Coronavirus Infections/physiopathology , Coronavirus Infections/therapy , Female , Hospital Mortality , Humans , Male , Middle Aged , Outcome and Process Assessment, Health Care , Pneumonia, Viral/mortality , Pneumonia, Viral/physiopathology , Pneumonia, Viral/therapy , Respiration, Artificial/statistics & numerical data , Retrospective Studies , Risk Factors , SARS-CoV-2 , Sarcoidosis, Pulmonary/diagnosis , Sarcoidosis, Pulmonary/epidemiology , Sarcoidosis, Pulmonary/physiopathology , United States/epidemiology
7.
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 , COVID-19 , 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 , SARS-CoV-2 , Young Adult
8.
BMJ Open ; 10(11): e040736, 2020 11 27.
Article in English | MEDLINE | ID: covidwho-947830

ABSTRACT

OBJECTIVE: The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive. DESIGN: Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive. SETTING: All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system. PARTICIPANTS: Participants over the age of 18 years were included. PRIMARY OUTCOMES: We investigated in-hospital mortality during the study period. RESULTS: A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 µg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 µg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL. CONCLUSIONS: In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.


Subject(s)
COVID-19/blood , Critical Care , Hospital Mortality , Hospitalization , Pandemics , Adolescent , Adult , Aged , Aged, 80 and over , C-Reactive Protein/metabolism , COVID-19/epidemiology , COVID-19/mortality , Comorbidity , Critical Care/statistics & numerical data , Female , Fibrin Fibrinogen Degradation Products/metabolism , Hospitals , Humans , Lymphocytes/metabolism , Male , Middle Aged , New York City/epidemiology , Procalcitonin/blood , Retrospective Studies , Risk Factors , SARS-CoV-2 , Young Adult
9.
Am J Emerg Med ; 46: 520-524, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-912013

ABSTRACT

BACKGROUND AND AIM: New York City (NYC) is an epicenter of the COVID-19 pandemic in the United States. Proper triage of patients with possible COVID-19 via chief complaint is critical but not fully optimized. This study aimed to investigate the association between presentation by chief complaints and COVID-19 status. METHODS: We retrospectively analyzed adult emergency department (ED) patient visits from five different NYC hospital campuses from March 1, 2020 to May 13, 2020 of patients who underwent nasopharyngeal COVID-19 RT-PCR testing. The positive and negative COVID-19 cohorts were then assessed for different chief complaints obtained from structured triage data. Sub-analysis was performed for patients older than 65 and within chief complaints with high mortality. RESULTS: Of 11,992 ED patient visits who received COVID-19 testing, 6524/11992 (54.4%) were COVID-19 positive. 73.5% of fever, 67.7% of shortness of breath, and 65% of cough had COVID-19, but others included 57.5% of weakness/fall/altered mental status, 55.5% of glycemic control, and 51.4% of gastrointestinal symptoms. In patients over 65, 76.7% of diarrhea, 73.7% of fatigue, and 69.3% of weakness had COVID-19. 45.5% of dehydration, 40.5% of altered mental status, 27% of fall, and 24.6% of hyperglycemia patients experienced mortality. CONCLUSION: A novel high risk COVID-19 patient population was identified from chief complaint data, which is different from current suggested CDC guidelines, and may help triage systems to better isolate COVID-19 patients. Older patients with COVID-19 infection presented with more atypical complaints warranting special consideration. COVID-19 was associated with higher mortality in a unique group of complaints also warranting special consideration.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , Emergency Service, Hospital/statistics & numerical data , Pandemics , Triage/methods , Adult , Aged , COVID-19/epidemiology , Female , Follow-Up Studies , Humans , Male , Middle Aged , New York City/epidemiology , Retrospective Studies
10.
Crit Care Explor ; 2(10): e0254, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-900567

ABSTRACT

OBJECTIVES: To examine whether increasing time between admission and intubation was associated with mortality in patients with coronavirus disease 2019 who underwent mechanical ventilation. DESIGN: Retrospective cohort study of patients with severe acute respiratory syndrome coronavirus 2 infection who were admitted between January 30, 2020, and April 30, 2020, and underwent intubation and mechanical ventilation prior to May 1, 2020. Patients were followed up through August 15, 2020. SETTING: Five hospitals within the Mount Sinai Health System in New York City, NY. PATIENTS: Adult patients with severe acute respiratory syndrome coronavirus 2 infection who underwent intubation and mechanical ventilation. INTERVENTIONS: Tracheal intubation and mechanical ventilation. MEASUREMENTS AND MAIN RESULTS: The primary outcome was in-hospital mortality. A hospital-stratified time-varying Cox model was used to evaluate the effect of time from admission to intubation on in-hospital death. A total of 755 adult patients out of 5,843 admitted with confirmed severe acute respiratory syndrome coronavirus 2 infection underwent tracheal intubation and mechanical ventilation during the study period. The median age of patients was 65 years (interquartile range, 56-72 yr) and 64% were male. As of the time of follow-up, 121 patients (16%) who were intubated and mechanically ventilated had been discharged home, 512 (68%) had died, 113 (15%) had been discharged to a skilled nursing facility, and 9 (1%) remained in the hospital. The median time from admission to intubation was 2.3 days (interquartile range, 0.6-6.3 d). Each additional day between hospital admission and intubation was significantly associated with higher in-hospital death (adjusted hazard ratio, 1.03; 95% CI, 1.01-1.05). CONCLUSIONS: Among patients with coronavirus disease 2019 who were intubated and mechanically ventilated, intubation earlier in the course of hospital admission may be associated with improved survival.

11.
J Am Coll Cardiol ; 76(20): 2334-2348, 2020 11 17.
Article in English | MEDLINE | ID: covidwho-899039

ABSTRACT

BACKGROUND: Patients with pre-existing heart failure (HF) are likely at higher risk for adverse outcomes in coronavirus disease-2019 (COVID-19), but data on this population are sparse. OBJECTIVES: This study described the clinical profile and associated outcomes among patients with HF hospitalized with COVID-19. METHODS: This study conducted a retrospective analysis of 6,439 patients admitted for COVID-19 at 1 of 5 Mount Sinai Health System hospitals in New York City between February 27 and June 26, 2020. Clinical characteristics and outcomes (length of stay, need for intensive care unit, mechanical ventilation, and in-hospital mortality) were captured from electronic health records. For patients identified as having a history of HF by International Classification of Diseases-9th and/or 10th Revisions codes, manual chart abstraction informed etiology, functional class, and left ventricular ejection fraction (LVEF). RESULTS: Mean age was 63.5 years, and 45% were women. Compared with patients without HF, those with previous HF experienced longer length of stay (8 days vs. 6 days; p < 0.001), increased risk of mechanical ventilation (22.8% vs. 11.9%; adjusted odds ratio: 3.64; 95% confidence interval: 2.56 to 5.16; p < 0.001), and mortality (40.0% vs. 24.9%; adjusted odds ratio: 1.88; 95% confidence interval: 1.27 to 2.78; p = 0.002). Outcomes among patients with HF were similar, regardless of LVEF or renin-angiotensin-aldosterone inhibitor use. CONCLUSIONS: History of HF was associated with higher risk of mechanical ventilation and mortality among patients hospitalized for COVID-19, regardless of LVEF.


Subject(s)
COVID-19/mortality , Heart Failure , Hospitalization , Aged , Aged, 80 and over , COVID-19/diagnosis , Cohort Studies , Female , Hospital Mortality , Humans , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Factors
12.
J Am Coll Cardiol ; 76(16): 1815-1826, 2020 10 20.
Article in English | MEDLINE | ID: covidwho-849705

ABSTRACT

BACKGROUND: Thromboembolic disease is common in coronavirus disease-2019 (COVID-19). There is limited evidence on the association of in-hospital anticoagulation (AC) with outcomes and postmortem findings. OBJECTIVES: The purpose of this study was to examine association of AC with in-hospital outcomes and describe thromboembolic findings on autopsies. METHODS: This retrospective analysis examined the association of AC with mortality, intubation, and major bleeding. Subanalyses were also conducted on the association of therapeutic versus prophylactic AC initiated ≤48 h from admission. Thromboembolic disease was contextualized by premortem AC among consecutive autopsies. RESULTS: Among 4,389 patients, median age was 65 years with 44% women. Compared with no AC (n = 1,530; 34.9%), therapeutic AC (n = 900; 20.5%) and prophylactic AC (n = 1,959; 44.6%) were associated with lower in-hospital mortality (adjusted hazard ratio [aHR]: 0.53; 95% confidence interval [CI]: 0.45 to 0.62 and aHR: 0.50; 95% CI: 0.45 to 0.57, respectively), and intubation (aHR: 0.69; 95% CI: 0.51 to 0.94 and aHR: 0.72; 95% CI: 0.58 to 0.89, respectively). When initiated ≤48 h from admission, there was no statistically significant difference between therapeutic (n = 766) versus prophylactic AC (n = 1,860) (aHR: 0.86; 95% CI: 0.73 to 1.02; p = 0.08). Overall, 89 patients (2%) had major bleeding adjudicated by clinician review, with 27 of 900 (3.0%) on therapeutic, 33 of 1,959 (1.7%) on prophylactic, and 29 of 1,530 (1.9%) on no AC. Of 26 autopsies, 11 (42%) had thromboembolic disease not clinically suspected and 3 of 11 (27%) were on therapeutic AC. CONCLUSIONS: AC was associated with lower mortality and intubation among hospitalized COVID-19 patients. Compared with prophylactic AC, therapeutic AC was associated with lower mortality, although not statistically significant. Autopsies revealed frequent thromboembolic disease. These data may inform trials to determine optimal AC regimens.


Subject(s)
Anticoagulants , Autopsy/statistics & numerical data , Coronavirus Infections , Hospitalization/statistics & numerical data , Pandemics , Pneumonia, Viral , Post-Exposure Prophylaxis , Thromboembolism , Aged , Anticoagulants/classification , Anticoagulants/therapeutic use , Betacoronavirus/isolation & purification , Blood Coagulation , COVID-19 , Coronavirus Infections/blood , Coronavirus Infections/complications , Coronavirus Infections/mortality , Coronavirus Infections/therapy , Female , Hemorrhage/chemically induced , Hemorrhage/prevention & control , Hospital Mortality , Humans , Male , New York City/epidemiology , Outcome and Process Assessment, Health Care , Pneumonia, Viral/blood , Pneumonia, Viral/complications , Pneumonia, Viral/mortality , Pneumonia, Viral/therapy , Post-Exposure Prophylaxis/methods , Post-Exposure Prophylaxis/statistics & numerical data , Risk Adjustment/methods , SARS-CoV-2 , Thromboembolism/drug therapy , Thromboembolism/mortality , Thromboembolism/prevention & control , Thromboembolism/virology
13.
J Anesth ; 35(3): 366-373, 2021 06.
Article in English | MEDLINE | ID: covidwho-812584

ABSTRACT

In March 2020, the New York City metropolitan area became the epicenter of the United States' SARS-CoV-2 pandemic and the surge of new cases threatened to overwhelm the area's hospital systems. This article describes how an anesthesiology department at a large urban academic hospital rapidly adapted and deployed to meet the threat head-on. Topics included are preparatory efforts, development of a team-based staffing model, and a new strategy for resource management. While still maintaining a fully functioning operating theater, discrete teams were deployed to both COVID-19 and non-COVID-19 intensive care units, rapid response/airway management team, the difficult airway response team, and labor and delivery. Additional topics include the creation of a temporary 'pop-up' anesthesiology-run COVID-19 intensive care unit utilizing anesthesia machines for monitoring and ventilatory support as well as the development of a simulation and innovation team that was instrumental in the rapid prototyping of a controlled split-ventilation system and conversion of readily available BIPAP units into emergency ventilators. As the course of the disease is uncertain, the goal of this article is to assist others in preparation for what may come next with COVID-19 as well as potential future pandemics.


Subject(s)
COVID-19 , Humans , Intensive Care Units , New York City , Pandemics , SARS-CoV-2 , United States
14.
Nat Med ; 26(11): 1708-1713, 2020 11.
Article in English | MEDLINE | ID: covidwho-772953

ABSTRACT

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a new human disease with few effective treatments1. Convalescent plasma, donated by persons who have recovered from COVID-19, is the acellular component of blood that contains antibodies, including those that specifically recognize SARS-CoV-2. These antibodies, when transfused into patients infected with SARS-CoV-2, are thought to exert an antiviral effect, suppressing virus replication before patients have mounted their own humoral immune responses2,3. Virus-specific antibodies from recovered persons are often the first available therapy for an emerging infectious disease, a stopgap treatment while new antivirals and vaccines are being developed1,2. This retrospective, propensity score-matched case-control study assessed the effectiveness of convalescent plasma therapy in 39 patients with severe or life-threatening COVID-19 at The Mount Sinai Hospital in New York City. Oxygen requirements on day 14 after transfusion worsened in 17.9% of plasma recipients versus 28.2% of propensity score-matched controls who were hospitalized with COVID-19 (adjusted odds ratio (OR), 0.86; 95% confidence interval (CI), 0.75-0.98; chi-square test P value = 0.025). Survival also improved in plasma recipients (adjusted hazard ratio (HR), 0.34; 95% CI, 0.13-0.89; chi-square test P = 0.027). Convalescent plasma is potentially effective against COVID-19, but adequately powered, randomized controlled trials are needed.


Subject(s)
COVID-19/pathology , COVID-19/therapy , Adult , Aged , Antibodies, Viral/blood , COVID-19/epidemiology , Case-Control Studies , Female , Humans , Immunization, Passive , Male , Middle Aged , Pandemics , Propensity Score , Retrospective Studies , SARS-CoV-2/immunology , Severity of Illness Index , Treatment Outcome
15.
Anesthesiology ; 133(4): 892-904, 2020 10 01.
Article in English | MEDLINE | ID: covidwho-772637

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, ventilator sharing was suggested to increase availability of mechanical ventilation. The safety and feasibility of ventilator sharing is unknown. METHODS: A single ventilator in pressure control mode was used with flow control valves to simultaneously ventilate two patients with different lung compliances. The system was first evaluated using high-fidelity human patient simulator mannequins and then tested for 1 h in two pairs of COVID-19 patients with acute respiratory failure. Patients were matched on positive end-expiratory pressure, fractional inspired oxygen tension, and respiratory rate. Tidal volume and peak airway pressure (PMAX) were recorded from each patient using separate independent spirometers and arterial blood gas samples drawn at 0, 30, and 60 min. The authors assessed acid-base status, oxygenation, tidal volume, and PMAX for each patient. Stability was assessed by calculating the coefficient of variation. RESULTS: The valves performed as expected in simulation, providing a stable tidal volume of 400 ml each to two mannequins with compliance ratios varying from 20:20 to 20:90 ml/cm H2O. The system was then tested in two pairs of patients. Pair 1 was a 49-yr-old woman, ideal body weight 46 kg, and a 55-yr-old man, ideal body weight 64 kg, with lung compliance 27 ml/cm H2O versus 35 ml/cm H2O. The coefficient of variation for tidal volume was 0.2 to 1.7%, and for PMAX 0 to 1.1%. Pair 2 was a 32-yr-old man, ideal body weight 62 kg, and a 56-yr-old woman, ideal body weight 46 kg, with lung compliance 12 ml/cm H2O versus 21 ml/cm H2O. The coefficient of variation for tidal volume was 0.4 to 5.6%, and for PMAX 0 to 2.1%. CONCLUSIONS: Differential ventilation using a single ventilator is feasible. Flow control valves enable delivery of stable tidal volume and PMAX similar to those provided by individual ventilators.


Subject(s)
Coronavirus Infections/therapy , Pneumonia, Viral/therapy , Respiration, Artificial/methods , Ventilators, Mechanical , Acid-Base Equilibrium , Adult , COVID-19 , Continuous Positive Airway Pressure , Coronavirus Infections/complications , Feasibility Studies , Female , Humans , Lung Compliance , Male , Manikins , Middle Aged , Oxygen/blood , Pandemics , Pneumonia, Viral/complications , Positive-Pressure Respiration , Respiration, Artificial/instrumentation , Respiratory Insufficiency/etiology , Respiratory Insufficiency/therapy , Spirometry , Tidal Volume , Ventilators, Mechanical/supply & distribution
16.
J Gen Intern Med ; 35(10): 2838-2844, 2020 10.
Article in English | MEDLINE | ID: covidwho-723327

ABSTRACT

BACKGROUND: Data on patients with coronavirus disease 2019 (COVID-19) who return to hospital after discharge are scarce. Characterization of these patients may inform post-hospitalization care. OBJECTIVE: To describe clinical characteristics of patients with COVID-19 who returned to the emergency department (ED) or required readmission within 14 days of discharge. DESIGN: Retrospective cohort study of SARS-COV-2-positive patients with index hospitalization between February 27 and April 12, 2020, with ≥ 14-day follow-up. Significance was defined as P < 0.05 after multiplying P by 125 study-wide comparisons. PARTICIPANTS: Hospitalized patients with confirmed SARS-CoV-2 discharged alive from five New York City hospitals. MAIN MEASURES: Readmission or return to ED following discharge. RESULTS: Of 2864 discharged patients, 103 (3.6%) returned for emergency care after a median of 4.5 days, with 56 requiring inpatient readmission. The most common reason for return was respiratory distress (50%). Compared with patients who did not return, there were higher proportions of COPD (6.8% vs 2.9%) and hypertension (36% vs 22.1%) among those who returned. Patients who returned also had a shorter median length of stay (LOS) during index hospitalization (4.5 [2.9,9.1] vs 6.7 [3.5, 11.5] days; Padjusted = 0.006), and were less likely to have required intensive care on index hospitalization (5.8% vs 19%; Padjusted = 0.001). A trend towards association between absence of in-hospital treatment-dose anticoagulation on index admission and return to hospital was also observed (20.9% vs 30.9%, Padjusted = 0.06). On readmission, rates of intensive care and death were 5.8% and 3.6%, respectively. CONCLUSIONS: Return to hospital after admission for COVID-19 was infrequent within 14 days of discharge. The most common cause for return was respiratory distress. Patients who returned more likely had COPD and hypertension, shorter LOS on index-hospitalization, and lower rates of in-hospital treatment-dose anticoagulation. Future studies should focus on whether these comorbid conditions, longer LOS, and anticoagulation are associated with reduced readmissions.


Subject(s)
Coronavirus Infections/epidemiology , Emergency Service, Hospital/statistics & numerical data , Patient Readmission/statistics & numerical data , Pneumonia, Viral/epidemiology , Aged , Anticoagulants/administration & dosage , Betacoronavirus , COVID-19 , Case-Control Studies , Comorbidity , Coronavirus Infections/therapy , Female , Humans , Hypertension/epidemiology , Length of Stay/statistics & numerical data , Male , Middle Aged , New York City/epidemiology , Pandemics , Pneumonia, Viral/therapy , Pulmonary Disease, Chronic Obstructive/epidemiology , Respiratory Distress Syndrome/epidemiology , Retrospective Studies , SARS-CoV-2
17.
SN Compr Clin Med ; 2(9): 1319-1322, 2020.
Article in English | MEDLINE | ID: covidwho-710357

ABSTRACT

Previous studies demonstrated a higher COVID-19 fatality rate in men. The aim of this study was to compare age and comorbidities between women and men who died from COVID-19. We retrospectively analyzed data of COVID-19 patients hospitalized to a large academic hospital system in New York City between March 1 and May 9, 2020. We used a multivariable logistic regression model to identify independently significant variables associated with gender in patients who died from COVID-19. The model was adjusted for age and comorbidities known to be associated with COVID-19 mortality. We identified 6760 patients diagnosed with COVID-19. Of these patients, 3018/6760 (44.6%) were women. The mortality rate was higher for men (women 18.2% vs. men 20.6%, p = 0.039). Of the patients who died, women were on average 5 years older than men (woman 77.4 ± 12.7 vs. men 72.4 ± 13.0, p < 0.001). In the multivariable model, cardiovascular comorbidities were not significantly different between women and men. Chronic kidney disease (aOR for women 0.7, 95% CI 0.5-0.9) and smoking (aOR for women 0.7, 95% CI 0.5-0.9) were more common in men. Age decile (aOR for women 1.4, 95% CI 1.3-1.6) and obesity (aOR for women 2.3, 95% CI 1.8-3.0) were higher in women. This study demonstrates that women who died of COVID-19 showed a similar cardiovascular disease profile as men. Yet, they are 5 years older than men. Investigating the gender impacts of COVID-19 is an important part of understanding the disease behavior.

18.
Obesity (Silver Spring) ; 28(9): 1595-1599, 2020 09.
Article in English | MEDLINE | ID: covidwho-700198

ABSTRACT

OBJECTIVE: Coronavirus disease 2019 (COVID-19) continues to spread, and younger patients are also being critically affected. This study analyzed obesity as an independent risk factor for mortality in hospitalized patients younger than 50. METHODS: This study retrospectively analyzed data of patients with COVID-19 who were hospitalized to a large academic hospital system in New York City between March 1, 2020, and May 17, 2020. Data included demographics, comorbidities, BMI, and smoking status. Obesity groups included the following: BMI of 30 to < 40 kg/m2 and BMI ≥ 40 kg/m2 . Multivariable logistic regression models identified variables independently associated with mortality in patients younger and older than 50. RESULTS: Overall, 3,406 patients were included; 572 (17.0%) patients were younger than 50. In the younger age group, 60 (10.5%) patients died. In the older age group, 1,076 (38.0%) patients died. For the younger population, BMI ≥ 40 was independently associated with mortality (adjusted odds ratio 5.1; 95% CI: 2.3-11.1). For the older population, BMI ≥ 40 was also independently associated with mortality to a lesser extent (adjusted odds ratio 1.6; 95% CI: 1.2-2.3). CONCLUSIONS: This study demonstrates that hospitalized patients younger than 50 with severe obesity are more likely to die of COVID-19. This is particularly relevant in the Western world, where obesity rates are high.


Subject(s)
Betacoronavirus , Coronavirus Infections/mortality , Obesity, Morbid/complications , Pneumonia, Viral/mortality , Adult , Aged , COVID-19 , Comorbidity , Coronavirus Infections/complications , Female , Hospitalization , Humans , Logistic Models , Male , Middle Aged , Obesity, Morbid/mortality , Odds Ratio , Pandemics , Pneumonia, Viral/complications , Retrospective Studies , Risk Factors , SARS-CoV-2
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