scholarly journals Lack of effect on in-hospital mortality of drugs used during COVID-19 pandemic: Findings of the retrospective multicenter COVOCA study

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256903
Author(s):  
Pia Clara Pafundi ◽  
Raffaele Galiero ◽  
Vittorio Simeon ◽  
Luca Rinaldi ◽  
Alessandro Perrella ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Drug Class ◽  
Orotracheal Intubation ◽  
Current Increase ◽  
Campania Region ◽  
Non Invasive ◽  
Non Invasive Ventilation ◽  
Mortality Incidence ◽  
Observational Cohort ◽  
Retrospective Observational Cohort Study

Introduction During COVID-19 pandemic, the use of several drugs has represented the worldwide clinical practice. However, though the current increase of knowledge about the disease, there is still no effective treatment for the usage of drugs. Thus, we retrospectively assessed use and effects of therapeutic regimens in hospitalized patients on in-hospital mortality. Methods COVOCA is a retrospective observational cohort study on 18 COVID centres throughout Campania Region Hospitals. We included adult patients with confirmed SARS-CoV-2 infection, discharged/dead between March/June 2020. Results 618 patients were included, with an overall in-hospital cumulative mortality incidence of 23.1%. Most prescribed early treatments were antivirals (72%), antibiotics (65%) and hydroxychloroquine/anticoagulants (≈50%). Tocilizumab, indeed, was largely prescribed late during hospitalization. Multivariable models, with a cut-off at day 2 for early COVID-19 therapy administration, did not disclose any significant association of a single drug administration on the clinical outcome. Discussion COVOCA represents the first multicenter database in Campania region. None drug class used during the pandemic significantly modified the outcome, regardless of therapy beginning, both overall and net of those already in non-invasive ventilation (NIV)/ orotracheal intubation (OTI) at hospitalization. Our cumulative incidence of mortality seems lower than other described during the same period, particularly in Northern Italy.

scholarly journals Early prediction of in-hospital mortality in acute pancreatitis: a retrospective observational cohort study based on a large multicentre critical care database

BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e041893
Author(s):  
Caifeng Li ◽  
Qian Ren ◽  
Zhiqiang Wang ◽  
Guolin Wang
Keyword(s):  
Risk Factors ◽  
Acute Pancreatitis ◽  
Multivariate Analysis ◽  
Hospital Mortality ◽  
Observational Cohort Study ◽  
Calibration Plot ◽  
Observational Cohort ◽  
Care Database ◽  
Retrospective Observational Cohort Study ◽  
Apache Iv

ObjectiveTo develop and validate a prediction model for predicting in-hospital mortality in patients with acute pancreatitis (AP).DesignA retrospective observational cohort study based on a large multicentre critical care database.SettingAll subject data were collected from the eICU Collaborative Research Database (eICU-CRD), which covers 200 859 intensive care unit admissions of 139 367 patients in 208 US hospitals between 2014 and 2015.ParticipantsA total of 746 patients with AP were drawn from eICU-CRD. Due to loss to follow-up (four patients) or incomplete data (364 patients), 378 patients were enrolled in the primary cohort to establish a nomogram model and to conduct internal validation.Primary and secondary outcome measuresThe outcome of the prediction model was in-hospital mortality. All risk factors found significant in the univariate analysis were considered for multivariate analysis to adjust for confounding factors. Then a nomogram model was established. The performance of the nomogram model was evaluated by the concordance index (C-index) and the calibration plot. The nomogram model was internally validated using the bootstrap resampling method. The predictive accuracy of the nomogram model was compared with that of Acute Physiology, Age, and Chronic Health Evaluation (APACHE) IV. Decision curve analysis (DCA) was performed to evaluate and compare the potential net benefit using of different predictive models.ResultsThe overall in-hospital mortality rate is 4.447%. Age, BUN (blood urea nitrogen) and lactate (ABL) were the independent risk factors determined by multivariate analysis. The C-index of nomogram model ABL (0.896 (95% CI 0.825 to 0.967)) was similar to that of APACHE IV (p=0.086), showing a comparable discriminating power. Calibration plot demonstrated good agreement between the predicted and the actual in-hospital mortality. DCA showed that the nomogram model ABL was clinically useful.ConclusionsNomogram model ABL, which used readily available data, exhibited high predictive value for predicting in-hospital mortality in AP.

scholarly journals Diabetes increases severe COVID-19 outcomes primarily in younger adults Age and diabetes in COVID-19 severity

2021 ◽  
Author(s):  
Marc Diedisheim ◽  
Etienne Dancoisne ◽  
Jean-François Gautier ◽  
Etienne Larger ◽  
Emmanuel Cosson ◽  
...  
Keyword(s):  
Risk Factor ◽  
Outcome Measure ◽  
Orotracheal Intubation ◽  
Composite Outcome ◽  
Younger Adults ◽  
Confounding Variables ◽  
Patients With Diabetes ◽  
Observational Cohort ◽  
Retrospective Observational Cohort Study

Abstract Context Diabetes is reported as a risk factor for severe COVID-19, but whether this risk is similar in all categories of age remains unclear. Objective To investigate the risk of severe COVID-19 outcomes in hospitalized patients with and without diabetes according to age categories. Design Setting and Participants We conducted a retrospective observational cohort study of 6,314 consecutive patients hospitalized for COVID-19 between February and June 30 2020, and follow-up recorded until 30 September 2020, in the Paris metropolitan area, France. Main Outcome Measure(s) The main outcome was a composite outcome of mortality and orotracheal intubation in subjects with diabetes compared with subjects without diabetes, after adjustment for confounding variables and according to age categories. Results Diabetes was recorded in 39% of subjects. Main outcome was higher in patients with diabetes, independently of confounding variables (HR 1.13 [1.03-1.24]) and increased with age in individuals without diabetes, from 23% for those <50 to 35% for those >80 years but reached a plateau after 70 in those with diabetes. In direct comparison between patients with and without diabetes, diabetes-associated risk was inversely proportional to age, highest in <50 and similar after 70 years. Similarly, mortality was higher in patients with diabetes (26%) than in those without diabetes (22%, p<0.001), but adjusted HR for diabetes was significant only in patients under 50 (HR 1.81 [1.14-2.87]). Conclusions Diabetes should be considered as an independent risk factor for the severity of COVID-19 in young adults more so than in older adults, especially for individuals younger than 70 years.

scholarly journals Diabetes and Overweight/Obesity Are Independent, Nonadditive Risk Factors for In-Hospital Severity of COVID-19: An International, Multicenter Retrospective Meta-analysis

2021 ◽  
Author(s):  
Danielle K. Longmore ◽  
Jessica E. Miller ◽  
Siroon Bekkering ◽  
Christoph Saner ◽  
Edin Mifsud ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Hospital Mortality ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Invasive Mechanical Ventilation ◽  
Invasive Ventilation ◽  
Site Specific ◽  
Non Invasive ◽  
Obesity And Diabetes ◽  
Non Invasive Ventilation

<a><b>OBJECTIVE</b><b> </b></a> <p>Obesity is an established risk factor for severe coronavirus disease 2019 (COVID-19) but the contribution of overweight and/or diabetes remain unclear. In a multi-center international study, we investigated if overweight, obesity and diabetes were independently associated with COVID-19 severity, and whether the body mass index (BMI)-associated risk was increased among those with diabetes. </p> <p> </p> <p><b>RESEARCH DESIGN & METHODS </b><b></b></p> <p>We retrospectively extracted data from health care records and regional databases of hospitalized adult patients with COVID-19 from 18 sites in 11 countries. We used standardized definitions and analyses to generate site-specific estimates, modelling the odds of each outcome (supplemental oxygen/non-invasive ventilation, invasive mechanical ventilation, and in-hospital mortality) by BMI category (reference, overweight, obese) adjusting for age, sex, and pre-specified co-morbidities. Subgroup analysis was performed on patients with pre-existing diabetes. Site-specific estimates were combined in a meta-analysis. </p> <p><u> </u></p> <p><b>RESULTS</b><b></b></p> <p>Among 7244 patients (65.6% overweight/obese), those with overweight were more likely to require oxygen/non-invasive ventilation (random effects adjusted odds ratio [aOR] 1.44 [95% CI 1.15-1.80]) and invasive mechanical ventilation (aOR 1.22 [CI 1.03-1.46]). There was no association between overweight and in-hospital mortality (aOR 0.88 [CI 0.74-1.04]). Similar effects were observed in patients with obesity or diabetes. In the subgroup analysis, the aOR for any outcome was not additionally increased in those with diabetes and overweight or obesity. </p> <p> </p> <p><b>CONCLUSIONS</b><b></b></p> <p>In adults hospitalized with COVID-19, overweight as well as obesity and diabetes were associated with increased odds of respiratory support but not mortality. In patients with diabetes, the odds of severe COVID-19 were not increased above the BMI-associated risk. </p>

scholarly journals Comparative Survival Analysis of Immunomodulatory Therapy for COVID-19 ‘Cytokine Storm’: A Retrospective Observational Cohort Study

2020 ◽  
Author(s):  
Sonali Narain ◽  
Dimitre G. Stefanov ◽  
Alice S. Chau ◽  
Andrew G. Weber ◽  
Galina Marder ◽  
...  
Keyword(s):  
Lactate Dehydrogenase ◽  
Hospital Mortality ◽  
Standard Of Care ◽  
P Value ◽  
Cytokine Storm ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Treatment Standard ◽  
Observational Cohort ◽  
Retrospective Observational Cohort Study

AbstractBackgroundCytokine storm is a marker of COVID-19 illness severity and increased mortality. Immunomodulatory treatments have been repurposed to improve mortality outcomes.MethodsWe conducted a retrospective analysis of electronic health records across the Northwell Health system. COVID-19 patients hospitalized between March 1, 2020 and April 15, 2020, were included. Cytokine storm was defined by inflammatory markers: ferritin >700ng/mL, C-reactive protein >30mg/dL, or lactate dehydrogenase >300U/L. Patients were subdivided into six groups -no immunomodulatory treatment (standard of care) and five groups that received either corticosteroids, anti-interleukin 6 (IL-6) antibody (tocilizumab) or anti-IL-1 therapy (anakinra) alone or in combination with corticosteroids. The primary outcome was hospital mortality.ResultsThere were 3,098 patients who met inclusion criteria. The most common comorbidities were hypertension (40-56%), diabetes (32-43%) and cardiovascular disease (2-15%). Patients most frequently met criteria with high lactate dehydrogenase (74.8%) alone, or in combination, followed by ferritin (71.4%) and C-reactive protein (9.4%). More than 80% of patients had an elevated D-dimer. Patients treated with a combination of tocilizumab and corticosteroids (Hazard Ratio [HR]: 0.459, 95% Confidence Interval [CI]: 0.295-0.714; p<0.0001) or corticosteroids alone (HR: 0.696, 95% CI: 0.512-0.946; p=0.01) had improved hospital survival compared to standard of care. Corticosteroids and tocilizumab was associated with increased survival when compared to corticosteroids and anakinra (HR: 0.612, 95% CI: 0.391-0.958; p-value=0.02).ConclusionsWhen compared to standard of care, corticosteroid and tocilizumab used in combination, or corticosteroids alone, was associated with reduced hospital mortality for patients with COVID-19 cytokine storm.

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