A case-control study of risk factors for death from 2009 pandemic influenza A(H1N1): is American Indian racial status an independent risk factor?

Hennessy, Thomas W.; Bruden, Dana; Castrodale, Louisa; Komatsu, Kenneth; Erhart, Laura M.; Thompson, Deborah; Bradley, Kristy; O’Leary, Daniel R.; McLaughlin, Joseph

doi:10.1017/s0950268815001211

Cited by 27 publications

(55 citation statements)

References 27 publications

(35 reference statements)

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“…Smoking history was another pedictor of FluA-p mortality in our study, which is a finding commensurate with some previous reports [34][35][36]. Wong and colleagues, for example, found that influenza-related mortality for all-causes and for cardiovascular and respiratory diseases was greater in current and exsmokers than in never smokers [34].…”

Section: Discussionsupporting

confidence: 93%

“…Early administration of NAI therapy is associated with better outcomes in severe influenza [40,41]. Old age, obesity, pregnancy and chronic medical conditions, such as COPD, diabetes mellitus, and chronic kidney disease, have been associated with poorer outcomes in patients with influenza [35,42,43]. However, in our study only cardiovascular disease was identified as a risk factor for mortality in FluA-p patients.…”

Section: Discussionmentioning

confidence: 50%

“…Wong and colleagues, for example, found that influenza-related mortality for all-causes and for cardiovascular and respiratory diseases was greater in current and exsmokers than in never smokers [34]. A case-control study by Hennessy et al found that smoking (OR 3.03, 95% CI 1.01-9.23) was a significant risk factor for death in patients with A(H1N1) pdm09 [35]. Although the precise nature of the association between smoking and influenza-related mortality has yet to be determined, some potential mechanisms suggest the possibility of biological associations.…”

Section: Discussionmentioning

confidence: 99%

“…Overview of FluA-p patientsOverall,39.2% (272/693) of patients were above 65 years old and 66.5% (461/693) of patients were male 35…”

mentioning

confidence: 99%

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FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

Liang

Han

et al. 2020

Respir Res

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Background: The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. Methods: A total of 693 laboratory-confirmed FluA-p patients diagnosed between Jan 2013 and Dec 2018 and recruited from five teaching hospitals in China were included in the study. The sample included 494 patients in the derivation cohort and 199 patients in the validation cohort. The prediction rule was established based on independent risk factors for 30-day mortality in FluA-p patients from the derivation cohort. Results: The 30-day mortality of FluA-p patients was 19.6% (136/693). The FluA-p score was based on a multivariate logistic regression model designed to predict mortality. Results indicated the following significant predictors (regression statistics and point contributions toward total score in parentheses): blood urea nitrogen > 7 mmol/L (OR 1.604, 95% CI 1.150-4.492, p = 0.040; 1 points), pO 2 /F i O 2 ≤ 250 mmHg (OR 2.649, 95% CI 1.103-5.142, p = 0.022; 2 points), cardiovascular disease (OR 3.967, 95% CI 1.269-7.322, p < 0.001; 3 points), arterial PH < 7.35 (OR 3.959, 95% CI 1.393-7.332, p < 0.001; 3 points), smoking history (OR 5.176, 95% CI 2.604-11.838, p = 0.001; 4 points), lymphocytes < 0.8 × 10 9 /L (OR 8.391, 95% CI 3.271-16.212, p < 0.001; 5 points), and early neurominidase inhibitor therapy (OR 0.567, 95% CI 0.202-0.833, p = 0.005; − 2 points). Seven points was used as the cut-off value for mortality risk stratification. The model showed a sensitivity of 0.941, a specificity of 0.762, and overall better predictive performance than the PSI risk class (AUROC = 0.908 vs 0.560, p < 0.001) and the CURB-65 score (AUROC = 0.908 vs 0.777, p < 0.001). Conclusions: Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 50%

Section: Discussionmentioning

confidence: 99%

“…Overview of FluA-p patientsOverall,39.2% (272/693) of patients were above 65 years old and 66.5% (461/693) of patients were male 35…”

mentioning

confidence: 99%

See 2 more Smart Citations

FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

Liang

Han

et al. 2020

Respir Res

View full text Add to dashboard Cite

show abstract

“…Smoking history was another pedictor of FluA-p mortality in our study, which is a finding commensurate with some previous reports [35][36][37]. Wong and colleagues, for example, found that influenza-related mortality for all-causes and for cardiovascular and respiratory diseases was greater in current and ex-smokers than in never smokers [35].…”

Section: Psi and Curb-65 Scores Are Recommended By The Infectious Dissupporting

confidence: 93%

FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

Chen

Han

et al. 2020

Preprint

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Background The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. Methods A total of 693 laboratory-confirmed FluA-p patients diagnosed between Jan 2013 and Dec 2018 and recruited from five teaching hospitals in China were included in the study. The sample included 494 patients in the derivation cohort and 199 patients in the validation cohort. The prediction rule was established based on independent risk factors for 30-day mortality in FluA-p patients from the derivation cohort. Results The 30-day mortality of FluA-p patients was 19.6% (136/693). The FluA-p score was based on a multivariate logistic regression model designed to predict mortality. Results indicated the following significant predictors (regression statistics and point contributions toward total score in parentheses): blood urea nitrogen > 7 mmol/L ( OR 1.604, 95% CI 1.150-4.492, p = 0.040; 1 points), pO 2 /F i O 2 ≤ 250 mmHg ( OR 2.649, 95% CI 1.103-5.142, p = 0.022; 2 points), cardiovascular disease ( OR 3.967, 95% CI 1.269-7.322, p <0.001; 3 points), arterial PH < 7.35 ( OR 3.959, 95% CI 1.393-7.332, p < 0.001; 3 points), smoking history ( OR 5.176, 95% CI 2.604-11.838, p = 0.001; 4 points), lymphocytes < 0.8×10 9 /L ( OR 8.391, 95% CI 3.271-16.212, p <0.001; 5 points), and early neurominidase inhibitor therapy ( OR 0.567, 95% CI 0.202-0.833, p = 0.005; -2 points). Seven points was used as the cut-off value for mortality risk stratification. The model showed a sensitivity of 0.941, a specificity of 0.762, and overall better predictive performance than the PSI risk class (AUROC = 0.908 vs 0.560, p < 0.001) and the CURB-65 score (AUROC = 0.908 vs 0.777, p < 0.001). Conclusions Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions.

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Clinical and Demographic Factors Associated With COVID-19, Severe COVID-19, and SARS-CoV-2 Infection in Adults

et al. 2023

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ImportanceCurrent data identifying COVID-19 risk factors lack standardized outcomes and insufficiently control for confounders.ObjectiveTo identify risk factors associated with COVID-19, severe COVID-19, and SARS-CoV-2 infection.Design, Setting, and ParticipantsThis secondary cross-protocol analysis included 4 multicenter, international, randomized, blinded, placebo-controlled, COVID-19 vaccine efficacy trials with harmonized protocols established by the COVID-19 Prevention Network. Individual-level data from participants randomized to receive placebo within each trial were combined and analyzed. Enrollment began July 2020 and the last data cutoff was in July 2021. Participants included adults in stable health, at risk for SARS-CoV-2, and assigned to the placebo group within each vaccine trial. Data were analyzed from April 2022 to February 2023.ExposuresComorbid conditions, demographic factors, and SARS-CoV-2 exposure risk at the time of enrollment.Main Outcomes and MeasuresCoprimary outcomes were COVID-19 and severe COVID-19. Multivariate Cox proportional regression models estimated adjusted hazard ratios (aHRs) and 95% CIs for baseline covariates, accounting for trial, region, and calendar time. Secondary outcomes included severe COVID-19 among people with COVID-19, subclinical SARS-CoV-2 infection, and SARS-CoV-2 infection.ResultsA total of 57 692 participants (median [range] age, 51 [18-95] years; 11 720 participants [20.3%] aged ≥65 years; 31 058 participants [53.8%] assigned male at birth) were included. The analysis population included 3270 American Indian or Alaska Native participants (5.7%), 7849 Black or African American participants (13.6%), 17 678 Hispanic or Latino participants (30.6%), and 40 745 White participants (70.6%). Annualized incidence was 13.9% (95% CI, 13.3%-14.4%) for COVID-19 and 2.0% (95% CI, 1.8%-2.2%) for severe COVID-19. Factors associated with increased rates of COVID-19 included workplace exposure (high vs low: aHR, 1.35 [95% CI, 1.16-1.58]; medium vs low: aHR, 1.41 [95% CI, 1.21-1.65]; P &lt; .001) and living condition risk (very high vs low risk: aHR, 1.41 [95% CI, 1.21-1.66]; medium vs low risk: aHR, 1.19 [95% CI, 1.08-1.32]; P &lt; .001). Factors associated with decreased rates of COVID-19 included previous SARS-CoV-2 infection (aHR, 0.13 [95% CI, 0.09-0.19]; P &lt; .001), age 65 years or older (aHR vs age &lt;65 years, 0.57 [95% CI, 0.50-0.64]; P &lt; .001) and Black or African American race (aHR vs White race, 0.78 [95% CI, 0.67-0.91]; P = .002). Factors associated with increased rates of severe COVID-19 included race (American Indian or Alaska Native vs White: aHR, 2.61 [95% CI, 1.85-3.69]; multiracial vs White: aHR, 2.19 [95% CI, 1.50-3.20]; P &lt; .001), diabetes (aHR, 1.54 [95% CI, 1.14-2.08]; P = .005) and at least 2 comorbidities (aHR vs none, 1.39 [95% CI, 1.09-1.76]; P = .008). In analyses restricted to participants who contracted COVID-19, increased severe COVID-19 rates were associated with age 65 years or older (aHR vs &lt;65 years, 1.75 [95% CI, 1.32-2.31]; P &lt; .001), race (American Indian or Alaska Native vs White: aHR, 1.98 [95% CI, 1.38-2.83]; Black or African American vs White: aHR, 1.49 [95% CI, 1.03-2.14]; multiracial: aHR, 1.81 [95% CI, 1.21-2.69]; overall P = .001), body mass index (aHR per 1-unit increase, 1.03 [95% CI, 1.01-1.04]; P = .001), and diabetes (aHR, 1.85 [95% CI, 1.37-2.49]; P &lt; .001). Previous SARS-CoV-2 infection was associated with decreased severe COVID-19 rates (aHR, 0.04 [95% CI, 0.01-0.14]; P &lt; .001).Conclusions and RelevanceIn this secondary cross-protocol analysis of 4 randomized clinical trials, exposure and demographic factors had the strongest associations with outcomes; results could inform mitigation strategies for SARS-CoV-2 and viruses with comparable epidemiological characteristics.

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A case-control study of risk factors for death from 2009 pandemic influenza A(H1N1): is American Indian racial status an independent risk factor?

Cited by 27 publications

References 27 publications

FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients

Clinical and Demographic Factors Associated With COVID-19, Severe COVID-19, and SARS-CoV-2 Infection in Adults

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