Association of Surge Conditions with Mortality Among Critically Ill Patients with COVID-19

Objective To determine whether surge conditions were associated with increased mortality. Design Multicenter cohort study. Setting U.S. ICUs participating in STOP-COVID. Patients Consecutive adults with COVID-19 admitted to participating ICUs between March 4 and July 1, 2020. Interventions None Measurements and Main Results The main outcome was 28-day in-hospital mortality. To assess the association between admission to an ICU during a surge period and mortality, we used two different strategies: (1) an inverse probability weighted difference-in-differences model limited to appropriately matched surge and non-surge patients and (2) a meta-regression of 50 multivariable difference-in-differences models (each based on sets of randomly matched surge- and non-surge hospitals). In the first analysis, we considered a single surge period for the cohort (March 23 – May 6). In the second, each surge hospital had its own surge period (which was compared to the same time periods in matched non-surge hospitals). Our cohort consisted of 4342 ICU patients (average age 60.8 [sd 14.8], 63.5% men) in 53 U.S. hospitals. Of these, 13 hospitals encountered surge conditions. In analysis 1, the increase in mortality seen during surge was not statistically significant (odds ratio [95% CI]: 1.30 [0.47-3.58], p = .6). In analysis 2, surge was associated with an increased odds of death (odds ratio 1.39 [95% CI, 1.34-1.43], p < .001). Conclusions Admission to an ICU with COVID-19 in a hospital that is experiencing surge conditions may be associated with an increased odds of death. Given the high incidence of COVID-19, such increases would translate into substantial excess mortality.

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COMBINATION OF TOCILIZUMAB AND STEROIDS TO IMPROVE MORTALITY IN PATIENTS WITH SEVERE COVID-19 INFECTION: A SPANISH, MULTICENTER, COHORT STUDY

10.1101/2020.09.07.20189357 ◽

2020 ◽

Cited By ~ 1

Author(s):

Belen Ruiz-Antoran ◽

Aranzazu Sancho-Lopez ◽

Ferran Torres ◽

Victor Moreno-Torres ◽

Itziar de Pablo Lopez de Abechuco ◽

...

Keyword(s):

Cohort Study ◽

Retrospective Cohort ◽

Oxygen Therapy ◽

Inclusion Criteria ◽

Multicenter Cohort Study ◽

Inverse Probability ◽

Multicenter Cohort ◽

Tertiary Hospitals ◽

Randomised Controlled ◽

The Impact

Background: We aimed to determine the impact of tocilizumab use in severe COVID-19 pneumonia mortality. Methods: We performed a multicentre retrospective cohort study in 18 tertiary hospitals in Spain, from March to April 2020. Consecutive patients admitted with severe COVID-19 treated with tocilizumab were compared to patients not treated with tocilizumab, adjusting by Inverse Probability of the Treatment Weights (IPTW). Tocilizumab effect in patients receiving steroids during the 48h following inclusion was analyzed. Results: During the study period, 506 patients with severe COVID-19 fulfilled inclusion criteria. Among them, 268 were treated with tocilizumab and 238 patients were not. Median time to tocilizumab treatment from onset of symptoms was 11 days (IQR 8-14). Global mortality was 23.7%. Mortality was lower in patients treated with tocilizumab than in controls (16.8% versus 31.5%, HR 0.514 [95CI 0.355-0.744], p<0.001; weighted HR 0.741 [95CI 0.619-0.887], p=0.001). Tocilizumab treatment reduced mortality by 14.7% relative to no tocilizumab treatment (RRR 46.7%). We calculated a number necessary to treat of 7. Among patients treated with steroids, mortality was lower in patients treated with tocilizumab than in those treated with steroids alone (10.9% versus 40.2%, HR 0.511 [95CI 0.352-0.741], p=0.036; weighted HR 0.6 [95CI 0.449-0.804], p<0.001) (Interaction p=0.094). Conclusions: These results show that survival of patients with severe COVID-19 is higher in patients treated with tocilizumab than in those not treated, and that tocilizumab effect adds to that of steroids administered to non-intubated cases with COVID-19 during the first 48 hours of presenting with respiratory failure despite of oxygen therapy. Randomised controlled studies are needed to confirm these results.

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Clinical features and predictors for patients with severe SARS-CoV-2 pneumonia at the start of the pandemic: a retrospective multicenter cohort study

BMC Infectious Diseases ◽

10.1186/s12879-021-06335-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Chao Cao ◽

Li He ◽

Jingping Ma ◽

Meiping Chen ◽

Yiting Li ◽

...

Keyword(s):

Cohort Study ◽

Clinical Features ◽

Lymphocyte Count ◽

Odds Ratio ◽

Small Sample Size ◽

Demographic Data ◽

Small Sample ◽

Clinical Trial Registry ◽

Multicenter Cohort Study ◽

Multicenter Cohort

Abstract Background This study was performed to investigate clinical features of patients with severe SARS-CoV-2 pneumonia and identify risk factors for converting to severe cases in those who had mild to moderate diseases at the start of the pandemic in China. Methods In this retrospective, multicenter cohort study, patients with mild to moderate SARS-CoV-2 pneumonia were included. Demographic data, symptoms, laboratory values, and clinical outcomes were collected. Data were compared between non-severe and severe patients. Results 58 patients were included in the final analysis. Compared with non-severe cases, severe patients with SARS-CoV-2 pneumonia had a longer: time to clinical recovery (12·9 ± 4·4 vs 8·3 ± 4·7; P = 0·0011), duration of viral shedding (15·7 ± 6·7 vs 11·8 ± 5·0; P = 0·0183), and hospital stay (20·7 ± 1·2 vs 14·4 ± 4·3; P = 0·0211). Multivariate logistic regression indicated that lymphocyte count was significantly associated with the rate of converting to severe cases (odds ratio 1·28, 95%CI 1·06–1·54, per 0·1 × 109/L reduced; P = 0·007), while using of low-to-moderate doses of systematic corticosteroids was associated with reduced likelihood of converting to a severe case (odds ratio 0·14, 95%CI 0·02–0·80; P = 0·0275). Conclusions The low peripheral blood lymphocyte count was an independent risk factor for SARS-CoV-2 pneumonia patients converting to severe cases. However, this study was carried out right after the start of the pandemic with small sample size. Further prospective studies are warranted to confirm these findings. Trial registration Chinese Clinical Trial Registry, ChiCTR2000029839. Registered 15 February 2020 - Retrospectively registered.

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Inverse probability weighted estimation of the marginal odds ratio

Statistics in Medicine ◽

10.1002/sim.3385 ◽

2008 ◽

Vol 27 (26) ◽

pp. 5560-5563

Author(s):

Peter C. Austin

Keyword(s):

Odds Ratio ◽

Inverse Probability ◽

Inverse Probability Weighted ◽

Inverse Probability Weighted Estimation ◽

Weighted Estimation

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Inverse probability weighted estimation of the marginal odds ratio: Correspondence regarding ‘The performance of different propensity score methods for estimating marginal odds ratios’ by P. Austin,Statictics in Medicine, 2007;26:3078-3094

Statistics in Medicine ◽

10.1002/sim.3362 ◽

2008 ◽

Vol 27 (26) ◽

pp. 5556-5559 ◽

Cited By ~ 11

Author(s):

Andrew Forbes ◽

Susan Shortreed

Keyword(s):

Propensity Score ◽

Odds Ratio ◽

Odds Ratios ◽

Inverse Probability ◽

Propensity Score Methods ◽

Inverse Probability Weighted ◽

Inverse Probability Weighted Estimation ◽

Weighted Estimation

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Clinical Features and Predictors for Patients with Severe SARS-CoV-2 Pneumonia: a retrospective multicenter cohort study

10.1101/2020.06.01.20119032 ◽

2020 ◽

Author(s):

Chao Cao ◽

Meiping Chen ◽

Yiting Li ◽

Lili Yu ◽

Weina Huang ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Cohort Study ◽

Clinical Outcomes ◽

Clinical Features ◽

Lymphocyte Count ◽

Odds Ratio ◽

Multicenter Cohort Study ◽

Multicenter Cohort ◽

Novel Coronavirus

SummaryBackgroundStarting from early December 2019, cases of human infection with a novel coronavirus were identified in Wuhan, Hubei Province, China. It spreads rapidly to other cities and numerous countries. This study was performed to investigate clinical features of patients with severe SARS-CoV-2 pneumonia and identify risk factors for converting to severe cases in those who had mild to moderate diseases.MethodsIn this retrospective, multicenter cohort study, patients with mild to moderate SARS-CoV-2 pneumonia were included from Ningbo First Hospital and Jingzhou Central Hospital. Demographic data, symptoms, laboratory values, comorbidities, and clinical outcomes were collected. Data were compared between non-severe and severe patients. Logistic regression analysis was performed to assess risk factors in predicting the patients with SARS-CoV-2 pneumonia who would convert to severe cases.Findings120 patients (36 from Ningbo First Hospital and 84 from Jingzhou Central Hospital) were included in this study, among which 62 were excluded and 58 were included in the final analysis. Compared with non-severe cases, severe patients with SARS-CoV-2 pneumonia had a longer: time to clinical recovery (12.9±4.4 vs 8.3±4.7; p=0.0011), duration of viral shedding (15.7±6.7 vs 11.8±5.0; p=0.0183), and hospital stay (20.7±1.2 vs 14.4±4.3; p=0.0211). Multivariate logistic regression indicated that lymphocyte count was significantly associated with the rate of converting to severe cases (odds ratio 1.28, 95%CI 1.06–1.54, per 0.1×109/L reduced; p=0.007), while using of low-to-moderate doses of systematic corticosteroids was associated with reduced likelihood of converting to a severe case (odds ratio 0.14, 95%CI 0.02–0.80; p=0.0275).InterpretationThe low peripheral blood lymphocyte count was an independent risk factor for SARS-CoV-2 pneumonia patients converting to severe cases. This finding may help clinicians more accurately predict prognosis, and triage priorities to improve clinical outcomes.Research in contextEvidence before this studySevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) is a novel coronavirus that have emerged in early December 2019, and has caused a novel coronavirus disease (COVID-19). It has been deemed as a public health emergency of global concern by The World Health Organization (WHO). We searched PubMed for articles published up to March 11, 2020, using the search terms (“novel coronavirus” OR “SARS-CoV-2” OR “COVID-19”) with no language or time restrictions. Previous work has described clinical characteristics of critically ill and non-critically ill patients with COVID-19. However, no published works have focused on clinical features of patients with severe SARS-CoV-2 pneumonia and identify risk factors for converting to severe cases in those who had mild to moderate diseases.Added value of this studyIn this retrospective and multicenter cohort study, we reported demographics characteristics, baseline symptoms, laboratory findings, corticosteroid usage and hospital course of patients with non-severe COVID-19 and severe COVID-19. Comparing with non-severe patients, severe patients with COVID-19 was found to have a longer: time to clinical recovery (12.9±4.4 vs 8.3±4.7; p=0.0011), duration of viral shedding (15.7±6.7 vs 11.8±5.0; p=0.0183), and hospital stay (20.7±1.2 vs 14.4±4.3; p=0.0211). By multivariate logistic regression, we found increasing odds of converting to severe cases associated with lower lymphocyte count (odds ratio 1.28, 95%CI 1.06–1.54, per 0.1×109/L reduced; p=0.007). Using of low-to-moderate doses of systematic corticosteroids was associated with reduced likelihood of converting to a severe case (odds ratio 0.14, 95%CI 0.02–0.80; p=0.0275).Implications of all the available evidenceLow lymphocyte count in peripheral blood was an independent risk factor for patients who converted to severe cases. In addition, using of systematic corticosteroids in mild to moderate patients with SARS-CoV-2 pneumonia was associated with a reduced risk of converting to severe cases. These findings may help clinicians predict prognosis more accurately, and triage priorities to improve clinical outcomes. Further prospective studies are warranted to confirm these findings.

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