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1.
Diagnostics (Basel) ; 13(6)2023 Mar 15.
Article in English | MEDLINE | ID: covidwho-2281040

ABSTRACT

Background: This study evaluated the temporal characteristics of lung chest X-ray (CXR) scores in COVID-19 patients during hospitalization and how they relate to other clinical variables and outcomes (alive or dead). Methods: This is a retrospective study of COVID-19 patients. CXR scores of disease severity were analyzed for: (i) survivors (N = 224) versus non-survivors (N = 28) in the general floor group, and (ii) survivors (N = 92) versus non-survivors (N = 56) in the invasive mechanical ventilation (IMV) group. Unpaired t-tests were used to compare survivors and non-survivors and between time points. Comparison across multiple time points used repeated measures ANOVA and corrected for multiple comparisons. Results: For general-floor patients, non-survivor CXR scores were significantly worse at admission compared to those of survivors (p < 0.05), and non-survivor CXR scores deteriorated at outcome (p < 0.05) whereas survivor CXR scores did not (p > 0.05). For IMV patients, survivor and non-survivor CXR scores were similar at intubation (p > 0.05), and both improved at outcome (p < 0.05), with survivor scores showing greater improvement (p < 0.05). Hospitalization and IMV duration were not different between groups (p > 0.05). CXR scores were significantly correlated with lactate dehydrogenase, respiratory rate, D-dimer, C-reactive protein, procalcitonin, ferritin, SpO2, and lymphocyte count (p < 0.05). Conclusions: Longitudinal CXR scores have the potential to provide prognosis, guide treatment, and monitor disease progression.

2.
Am J Emerg Med ; 51: 1-5, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1439821

ABSTRACT

BACKGROUND: Many patients with Coronavirus disease-2019 (Covid-19) present with radiological evidence of pneumonia. Because it is difficult to determine co-existence of bacterial pneumonia, many of these patients are initially treated with antibiotics. We compared the rates of bacterial infections and mortality in Covid-19 patients with pulmonary infiltrates versus patients diagnosed with 'pneumonia' the year previously. METHODS: We conducted a medical record review of patients admitted with Covid-19 and a pulmonary infiltrate and compared them with patients diagnosed with pneumonia admitted in the prior year before the pandemic. Data abstracted included baseline demographics, comorbidities, signs and symptoms, laboratory and microbiological results, and imaging findings. Outcomes were bacterial infections and mortality. Patients presenting with and without Covid-19 were compared using univariable and multivariable analyses. RESULTS: There were 1398 and 1001 patients admitted through the emergency department (ED) with and without Covid-19 respectively. Compared with non-Covid-19 patients, those with Covid-19 were younger (61±18 vs. 65±25 years, P < 0.001) and had a lower Charlson Comorbidity Index (0.7 vs. 1.2, P < 0.001). Bacterial infections were present in fewer Covid-19 than non-Covid-19 patients (8% vs. 13%, P < 0.001), and most infections in Covid-19 were nosocomial as opposed to community acquired in non-Covid-19 patients. CXR was more often read as abnormal and with bilateral infiltrates in patients with Covid-19 (82% vs. 70%, P < 0.001 and 81% vs. 48%, P < 0.001, respectively). Mortality was higher in patients with Covid-19 vs. those without (15% vs. 9%, P < 0.001). Multivariable predictors (OR [95%CI]) of mortality were age (1.04 [1.03-1.05]/year), tachypnea (1.55 [1.12-2.14]), hypoxemia (2.98 [2.04-4.34]), and bacterial infection (2.80 [1.95-4.02]). Compared with non-Covid-19 patients with pneumonia, patients with Covid-19 were more likely to die (2.68 [1.97-3.63]). CONCLUSIONS: The rate of bacterial infections is lower in Covid-19 patients with pulmonary infiltrates compared with patients diagnosed with pneumonia prior to the pandemic and most are nosocomial. Mortality was higher in Covid-19 than non-Covid-19 patients even after adjusting for age, tachypnea, hypoxemia, and bacterial infection.


Subject(s)
Bacterial Infections/epidemiology , COVID-19/mortality , Coinfection/epidemiology , Pneumonia/mortality , Adult , Age Factors , Aged , Aged, 80 and over , Comorbidity , Cross Infection/epidemiology , Female , Hospitalization , Humans , Hypoxia/epidemiology , Male , Middle Aged , Missouri/epidemiology , Retrospective Studies , Risk Factors , Tachypnea/epidemiology
3.
J Intensive Care Med ; 36(10): 1209-1216, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1358981

ABSTRACT

Background: Respiratory failure due to coronavirus disease of 2019 (COVID-19) often presents with worsening gas exchange over a period of days. Once patients require mechanical ventilation (MV), the temporal change in gas exchange and its relation to clinical outcome is poorly described. We investigated whether gas exchange over the first 5 days of MV is associated with mortality and ventilator-free days at 28 days in COVID-19. Methods: In a cohort of 294 COVID-19 patients, we used data during the first 5 days of MV to calculate 4 daily respiratory scores: PaO2/FiO2 (P/F), oxygenation index (OI), ventilatory ratio (VR), and Murray lung injury score. The association between these scores at early (days 1-3) and late (days 4-5) time points with mortality was evaluated using logistic regression, adjusted for demographics. Correlation with ventilator-free days was assessed (Spearman rank-order coefficients). Results: Overall mortality was 47.6%. Nonsurvivors were older (P < .0001), more male (P = .029), with more preexisting cardiopulmonary disease compared to survivors. Mean PaO2 and PaCO2 were similar during this timeframe. However, by days 4 to 5 values for all airway pressures and FiO2 had diverged, trending lower in survivors and higher in nonsurvivors. The most substantial between-group difference was the temporal change in OI, improving 15% in survivors and worsening 11% in nonsurvivors (P < .05). The adjusted mortality OR was significant for age (1.819, P = .001), OI at days 4 to 5 (2.26, P = .002), and OI percent change (1.90, P = .02). The number of ventilator-free days correlated significantly with late VR (-0.166, P < .05), early and late OI (-0.216, P < .01; -0.278, P < .01, respectively) and early and late P/F (0.158, P < .05; 0.283, P < .01, respectively). Conclusion: Nonsurvivors of COVID-19 needed increasing intensity of MV to sustain gas exchange over the first 5 days, unlike survivors. Temporal change OI, reflecting both PaO2 and the intensity of MV, is a potential marker of outcome in respiratory failure due to COVID-19.


Subject(s)
COVID-19 , Respiratory Distress Syndrome , Respiratory Insufficiency , Humans , Male , Respiration, Artificial , Respiratory Insufficiency/etiology , Respiratory Insufficiency/therapy , SARS-CoV-2
4.
Acad Emerg Med ; 27(12): 1260-1269, 2020 12.
Article in English | MEDLINE | ID: covidwho-991139

ABSTRACT

BACKGROUND: Despite reported higher rates and worse outcomes due to COVID-19 in certain racial and ethnic groups, much remains unknown. We explored the association between Hispanic ethnicity and outcomes in COVID-19 patients in Long Island, New York. METHODS: We conducted a retrospective cohort study of 2,039 Hispanic and non-Hispanic Caucasian patients testing positive for SARS-CoV-2 between March 7 and May 23, 2020, at a large suburban academic tertiary care hospital near New York City. We explored the association of ethnicity with need for intensive care unit (ICU), invasive mechanical ventilation (IMV), and mortality. RESULTS: Of all patients, 1,079 (53%) were non-Hispanic Caucasians and 960 (47%) were Hispanic. Hispanic patients presented in higher numbers than expected for our catchment area. Compared with Caucasians, Hispanics were younger (45 years vs. 59 years), had fewer comorbidities (66% with no comorbidities vs. 40%), were less likely to have commercial insurance (35% vs. 59%), or were less likely to come from a nursing home (2% vs. 10%). In univariate comparisons, Hispanics were less likely to be admitted (37% vs. 59%) or to die (3% vs. 10%). Age, shortness of breath, congestive heart failure (CHF), coronary artery disease (CAD), hypoxemia, and presentation from nursing homes were associated with admission. Male sex and hypoxemia were associated with ICU admission. Male sex, chronic obstructive pulmonary disease, and hypoxemia were associated with IMV. Male sex, CHF, CAD, and hypoxemia were associated with mortality. After other factors were adjusted for, Hispanics were less likely to be admitted (odds ratio = 0.62, 95% confidence interval = 0.52 to 0.92) but Hispanic ethnicity was not associated with ICU admission, IMV, or mortality. CONCLUSIONS: Hispanics presented at higher rates than average for our population but outcomes among Hispanic patients with COVID-19 were similar to those of Caucasian patients.


Subject(s)
COVID-19/epidemiology , Hispanic or Latino/statistics & numerical data , Patient Admission/statistics & numerical data , White People/statistics & numerical data , Aged , COVID-19/diagnosis , Critical Illness/epidemiology , Ethnicity , Female , Humans , Intensive Care Units , Male , Middle Aged , New York City/epidemiology , Odds Ratio , Respiration, Artificial , Retrospective Studies , SARS-CoV-2
5.
PLoS One ; 15(7): e0236618, 2020.
Article in English | MEDLINE | ID: covidwho-691336

ABSTRACT

This study aimed to develop risk scores based on clinical characteristics at presentation to predict intensive care unit (ICU) admission and mortality in COVID-19 patients. 641 hospitalized patients with laboratory-confirmed COVID-19 were selected from 4997 persons under investigation. We performed a retrospective review of medical records of demographics, comorbidities and laboratory tests at the initial presentation. Primary outcomes were ICU admission and death. Logistic regression was used to identify independent clinical variables predicting the two outcomes. The model was validated by splitting the data into 70% for training and 30% for testing. Performance accuracy was evaluated using area under the curve (AUC) of the receiver operating characteristic analysis (ROC). Five significant variables predicting ICU admission were lactate dehydrogenase, procalcitonin, pulse oxygen saturation, smoking history, and lymphocyte count. Seven significant variables predicting mortality were heart failure, procalcitonin, lactate dehydrogenase, chronic obstructive pulmonary disease, pulse oxygen saturation, heart rate, and age. The mortality group uniquely contained cardiopulmonary variables. The risk score model yielded good accuracy with an AUC of 0.74 ([95% CI, 0.63-0.85], p = 0.001) for predicting ICU admission and 0.83 ([95% CI, 0.73-0.92], p<0.001) for predicting mortality for the testing dataset. This study identified key independent clinical variables that predicted ICU admission and mortality associated with COVID-19. This risk score system may prove useful for frontline physicians in clinical decision-making under time-sensitive and resource-constrained environment.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Intensive Care Units , Models, Theoretical , Patient Admission/trends , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , Aged , Aged, 80 and over , Area Under Curve , COVID-19 , Clinical Decision-Making , Coronavirus Infections/virology , Female , Hospitals, University , Humans , Logistic Models , Male , Middle Aged , New York/epidemiology , Pandemics , Pneumonia, Viral/virology , Prognosis , ROC Curve , Retrospective Studies , Risk Factors , SARS-CoV-2
6.
Ann Emerg Med ; 76(4): 394-404, 2020 10.
Article in English | MEDLINE | ID: covidwho-610543

ABSTRACT

Study objective: Most coronavirus disease 2019 (COVID-19) reports have focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients. However, at initial presentation, most patients' viral status is unknown. Determination of factors that predict initial and subsequent need for ICU and invasive mechanical ventilation is critical for resource planning and allocation. We describe our experience with 4,404 persons under investigation and explore predictors of ICU care and invasive mechanical ventilation at a New York COVID-19 epicenter. Methods: We conducted a retrospective cohort study of all persons under investigation and presenting to a large academic medical center emergency department (ED) in New York State with symptoms suggestive of COVID-19. The association between patient predictor variables and SARS-CoV-2 status, ICU admission, invasive mechanical ventilation, and mortality was explored with univariate and multivariate analyses. Results: Between March 12 and April 14, 2020, we treated 4,404 persons under investigation for COVID-19 infection, of whom 68% were discharged home, 29% were admitted to a regular floor, and 3% to an ICU. One thousand six hundred fifty-one of 3,369 patients tested have had SARS-CoV-2-positive results to date. Of patients with regular floor admissions, 13% were subsequently upgraded to the ICU after a median of 62 hours (interquartile range 28 to 106 hours). Fifty patients required invasive mechanical ventilation in the ED, 4 required out-of-hospital invasive mechanical ventilation, and another 167 subsequently required invasive mechanical ventilation in a median of 60 hours (interquartile range 26 to 99) hours after admission. Testing positive for SARS-CoV-2 and lower oxygen saturations were associated with need for ICU and invasive mechanical ventilation, and with death. High respiratory rates were associated with the need for ICU care. Conclusion: Persons under investigation for COVID-19 infection contribute significantly to the health care burden beyond those ruling in for SARS-CoV-2. For every 100 admitted persons under investigation, 9 will require ICU stay, invasive mechanical ventilation, or both on arrival and another 12 within 2 to 3 days of hospital admission, especially persons under investigation with lower oxygen saturations and positive SARS-CoV-2 swab results. This information should help hospitals manage the pandemic efficiently.


Subject(s)
Coronavirus Infections/therapy , Critical Care/statistics & numerical data , Emergency Service, Hospital/statistics & numerical data , Pneumonia, Viral/therapy , Respiration, Artificial/statistics & numerical data , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Comorbidity , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Female , Humans , Male , Middle Aged , New York/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , Retrospective Studies , Risk Factors , SARS-CoV-2 , Young Adult
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