Improvement of antibiotic therapy and ICU survival in severe non-pneumococcal community-acquired pneumonia: a matched case-control study

INTRODUCTION: We aimed to compare intensive care unit mortality due to non-pneumococcal severe community-acquired pneumonia between the periods 2000-2002 and 2008-2014, and the impact of the improvement in antibiotic strategies on outcomes. METHODS: This was a matched case-control study enrolling 144 patients with non-pneumococcal severe pneumonia: 72 patients from the 2000-2002 database (CAPUCI I group) were paired with 72 from the 2008-2014 period (CAPUCI II group), matched by the following variables: microorganism, shock at admission, invasive mechanical ventilation, immunocompromise, chronic obstructive pulmonary disease, and age over 65 years. RESULTS: The most frequent microorganism was methicillin-susceptible Staphylococcus aureus (22.1%) followed by Legionella pneumophila and Haemophilus influenzae (each 20.7%); prevalence of shock was 59.7%, while 73.6% of patients needed invasive mechanical ventilation. Intensive care unit mortality was significantly lower in the CAPUCI II group (34.7% versus 16.7%; odds ratio (OR) 0.78, 95% confidence interval (CI) 0.64-0.95; p = 0.02). Appropriate therapy according to microorganism was 91.5% in CAPUCI I and 92.7% in CAPUCI II, while combined therapy and early antibiotic treatment were significantly higher in CAPUCI II (76.4 versus 90.3% and 37.5 versus 63.9%; p < 0.05). In the multivariate analysis, combined antibiotic therapy (OR 0.23, 95% CI 0.07-0.74) and early antibiotic treatment (OR 0.07, 95% CI 0.02-0.22) were independently associated with decreased intensive care unit mortality. CONCLUSIONS: In non-pneumococcal severe community-acquired pneumonia , early antibiotic administration and use of combined antibiotic therapy were both associated with increased intensive care unit survival during the study period

Pandemic and post-pandemic Influenza A (H1N1) infection in critically ill patients

Background: There is a vast amount of information published regarding the impact of 2009 pandemic Influenza A (pH1N1) virus infection. However, a comparison of risk factors and outcome during the 2010-2011 post-pandemic period has not been described. Methods: A prospective, observational, multi-center study was carried out to evaluate the clinical characteristics and demographics of patients with positive RT-PCR for H1N1 admitted to 148 Spanish intensive care units (ICUs). Data were obtained from the 2009 pandemic and compared to the 2010-2011 post-pandemic period. Results: Nine hundred and ninety-seven patients with confirmed An/H1N1 infection were included. Six hundred and forty-eight patients affected by 2009 (pH1N1) virus infection and 349 patients affected by the post-pandemic Influenza (H1N1)v infection period were analyzed. Patients during the post-pandemic period were older, had more chronic comorbid conditions and presented with higher severity scores (Acute Physiology And Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA)) on ICU admission. Patients from the post-pandemic Influenza (H1N1)v infection period received empiric antiviral treatment less frequently and with delayed administration. Mortality was significantly higher in the post-pandemic period. Multivariate analysis confirmed that haematological disease, invasive mechanical ventilation and continuous renal replacement therapy were factors independently associated with worse outcome in the two periods. HIV was the only new variable independently associated with higher ICU mortality during the post-pandemic Influenza (H1N1)v infection period. Conclusion: Patients from the post-pandemic Influenza (H1N1)v infection period had an unexpectedly higher mortality rate and showed a trend towards affecting a more vulnerable population, in keeping with more typical seasonal viral infection

Pandemic and post-pandemic Influenza A (H1N1) infection in critically ill patients

Background: There is a vast amount of information published regarding the impact of 2009 pandemic Influenza A (pH1N1) virus infection. However, a comparison of risk factors and outcome during the 2010-2011 post-pandemic period has not been described. Methods: A prospective, observational, multi-center study was carried out to evaluate the clinical characteristics and demographics of patients with positive RT-PCR for H1N1 admitted to 148 Spanish intensive care units (ICUs). Data were obtained from the 2009 pandemic and compared to the 2010-2011 post-pandemic period. Results: Nine hundred and ninety-seven patients with confirmed An/H1N1 infection were included. Six hundred and forty-eight patients affected by 2009 (pH1N1) virus infection and 349 patients affected by the post-pandemic Influenza (H1N1)v infection period were analyzed. Patients during the post-pandemic period were older, had more chronic comorbid conditions and presented with higher severity scores (Acute Physiology And Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA)) on ICU admission. Patients from the post-pandemic Influenza (H1N1)v infection period received empiric antiviral treatment less frequently and with delayed administration. Mortality was significantly higher in the post-pandemic period. Multivariate analysis confirmed that haematological disease, invasive mechanical ventilation and continuous renal replacement therapy were factors independently associated with worse outcome in the two periods. HIV was the only new variable independently associated with higher ICU mortality during the post-pandemic Influenza (H1N1)v infection period. Conclusion: Patients from the post-pandemic Influenza (H1N1)v infection period had an unexpectedly higher mortality rate and showed a trend towards affecting a more vulnerable population, in keeping with more typical seasonal viral infection

Procalcitonin (PCT) levels for ruling-out bacterial coinfection in ICU patients with influenza: A CHAID decision-tree analysis

Objectives: To define which variables upon ICU admission could be related to the presence of coinfection using CHAID (Chi-squared Automatic Interaction Detection) analysis. Methods: A secondary analysis from a prospective, multicentre, observational study (2009-2014) in ICU patients with confirmed A(H1N1)pdm09 infection. We assessed the potential of biomarkers and clinical variables upon admission to the ICU for coinfection diagnosis using CHAID analysis. Performance of cut-off points obtained was determined on the basis of the binominal distributions of the true (+) and true (−) results. Results: Of the 972 patients included, 196 (20.3%) had coinfection. Procalcitonin (PCT; ng/mL 2.4 vs. 0.5, p < 0.001), but not C-reactive protein (CRP; mg/dL 25 vs. 38.5; p = 0.62) was higher in patients with coinfection. In CHAID analyses, PCT was the most important variable for coinfection. PCT <0.29 ng/mL showed high sensitivity (Se = 88.2%), low Sp (33.2%) and high negative predictive value (NPV = 91.9%). The absence of shock improved classification capacity. Thus, for PCT <0.29 ng/mL, the Se was 84%, the Sp 43% and an NPV of 94% with a post-test probability of coinfection of only 6%. Conclusion: PCT has a high negative predictive value (94%) and lower PCT levels seems to be a good tool for excluding coinfection, particularly for patients without shock

Intensive care adult patients with severe respiratory failure caused by Influenza A (H1N1)v in Spain

Introduction: Patients with influenza A (H1N1)v infection have developed rapidly progressive lower respiratory tract disease resulting in respiratory failure. We describe the clinical and epidemiologic characteristics of the first 32 persons reported to be admitted to the intensive care unit (ICU) due to influenza A (H1N1)v infection in Spain. Methods: We used medical chart reviews to collect data on ICU adult patients reported in a standardized form. Influenza A (H1N1)v infection was confirmed in specimens using real-time reverse transcriptase-polymerase-chain-reaction (RT PCR) assay. Results: Illness onset of the 32 patients occurred between 23 June and 31 July, 2009. The median age was 36 years (IQR = 31 - 52). Ten (31.2%) were obese, 2 (6.3%) pregnant and 16 (50%) had pre-existing medical complications. Twenty-nine (90.6%) had primary viral pneumonitis, 2 (6.3%) exacerbation of structural respiratory disease and 1 (3.1%) secondary bacterial pneumonia. Twenty-four patients (75.0%) developed multiorgan dysfunction, 7 (21.9%) received renal replacement techniques and 24 (75.0%) required mechanical ventilation. Six patients died within 28 days, with two additional late deaths. Oseltamivir administration delay ranged from 2 to 8 days after illness onset, 31.2% received high-dose (300 mg/day), and treatment duration ranged from 5 to 10 days (mean 8.0 +/- 3.3). Conclusions: Over a 5-week period, influenza A (H1N1)v infection led to ICU admission in 32 adult patients, with frequently observed severe hypoxemia and a relatively high case-fatality rate. Clinicians should be aware of pulmonary complications of influenza A (H1N1)v infection, particularly in pregnant and young obese but previously healthy persons

Autoantibodies neutralizing type I IFNs are present in ~4% of uninfected individuals over 70 years old and account for ~20% of COVID-19 deaths

Publisher Copyright: © 2021 The Authors, some rights reserved.Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/ml; in plasma diluted 1:10) of IFN-alpha and/or IFN-omega are found in about 10% of patients with critical COVID-19 (coronavirus disease 2019) pneumonia but not in individuals with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-alpha and/or IFN-omega (100 pg/ml; in 1:10 dilutions of plasma) in 13.6% of 3595 patients with critical COVID-19, including 21% of 374 patients >80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1124 deceased patients (aged 20 days to 99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-beta. We also show, in a sample of 34,159 uninfected individuals from the general population, that auto-Abs neutralizing high concentrations of IFN-alpha and/or IFN-omega are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of individuals carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals 80 years. By contrast, auto-Abs neutralizing IFN-beta do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over 80s and total fatal COVID-19 cases.Peer reviewe

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies

SignificanceThere is growing evidence that preexisting autoantibodies neutralizing type I interferons (IFNs) are strong determinants of life-threatening COVID-19 pneumonia. It is important to estimate their quantitative impact on COVID-19 mortality upon SARS-CoV-2 infection, by age and sex, as both the prevalence of these autoantibodies and the risk of COVID-19 death increase with age and are higher in men. Using an unvaccinated sample of 1,261 deceased patients and 34,159 individuals from the general population, we found that autoantibodies against type I IFNs strongly increased the SARS-CoV-2 infection fatality rate at all ages, in both men and women. Autoantibodies against type I IFNs are strong and common predictors of life-threatening COVID-19. Testing for these autoantibodies should be considered in the general population

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection fatality rate (IFR) doubles with every 5 y of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-β are found in ∼20% of deceased patients across age groups, and in ∼1% of individuals aged 4% of those >70 y old in the general population. With a sample of 1,261 unvaccinated deceased patients and 34,159 individuals of the general population sampled before the pandemic, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to noncarriers. The RRD associated with any combination of autoantibodies was higher in subjects under 70 y old. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRDs were 17.0 (95% CI: 11.7 to 24.7) and 5.8 (4.5 to 7.4) for individuals <70 y and ≥70 y old, respectively, whereas, for autoantibodies neutralizing both molecules, the RRDs were 188.3 (44.8 to 774.4) and 7.2 (5.0 to 10.3), respectively. In contrast, IFRs increased with age, ranging from 0.17% (0.12 to 0.31) for individuals <40 y old to 26.7% (20.3 to 35.2) for those ≥80 y old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84% (0.31 to 8.28) to 40.5% (27.82 to 61.20) for autoantibodies neutralizing both. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, especially when neutralizing both IFN-α2 and IFN-ω. Remarkably, IFRs increase with age, whereas RRDs decrease with age. Autoimmunity to type I IFNs is a strong and common predictor of COVID-19 death.The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute; The Rockefeller University; the St. Giles Foundation; the NIH (Grants R01AI088364 and R01AI163029); the National Center for Advancing Translational Sciences; NIH Clinical and Translational Science Awards program (Grant UL1 TR001866); a Fast Grant from Emergent Ventures; Mercatus Center at George Mason University; the Yale Center for Mendelian Genomics and the Genome Sequencing Program Coordinating Center funded by the National Human Genome Research Institute (Grants UM1HG006504 and U24HG008956); the Yale High Performance Computing Center (Grant S10OD018521); the Fisher Center for Alzheimer’s Research Foundation; the Meyer Foundation; the JPB Foundation; the French National Research Agency (ANR) under the “Investments for the Future” program (Grant ANR-10-IAHU-01); the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (Grant ANR-10-LABX-62-IBEID); the French Foundation for Medical Research (FRM) (Grant EQU201903007798); the French Agency for Research on AIDS and Viral hepatitis (ANRS) Nord-Sud (Grant ANRS-COV05); the ANR GENVIR (Grant ANR-20-CE93-003), AABIFNCOV (Grant ANR-20-CO11-0001), CNSVIRGEN (Grant ANR-19-CE15-0009-01), and GenMIS-C (Grant ANR-21-COVR-0039) projects; the Square Foundation; Grandir–Fonds de solidarité pour l’Enfance; the Fondation du Souffle; the SCOR Corporate Foundation for Science; The French Ministry of Higher Education, Research, and Innovation (Grant MESRI-COVID-19); Institut National de la Santé et de la Recherche Médicale (INSERM), REACTing-INSERM; and the University Paris Cité. P. Bastard was supported by the FRM (Award EA20170638020). P. Bastard., J.R., and T.L.V. were supported by the MD-PhD program of the Imagine Institute (with the support of Fondation Bettencourt Schueller). Work at the Neurometabolic Disease lab received funding from Centre for Biomedical Research on Rare Diseases (CIBERER) (Grant ACCI20-767) and the European Union's Horizon 2020 research and innovation program under grant agreement 824110 (EASI Genomics). Work in the Laboratory of Virology and Infectious Disease was supported by the NIH (Grants P01AI138398-S1, 2U19AI111825, and R01AI091707-10S1), a George Mason University Fast Grant, and the G. Harold and Leila Y. Mathers Charitable Foundation. The Infanta Leonor University Hospital supported the research of the Department of Internal Medicine and Allergology. The French COVID Cohort study group was sponsored by INSERM and supported by the REACTing consortium and by a grant from the French Ministry of Health (Grant PHRC 20-0424). The Cov-Contact Cohort was supported by the REACTing consortium, the French Ministry of Health, and the European Commission (Grant RECOVER WP 6). This work was also partly supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases and the National Institute of Dental and Craniofacial Research, NIH (Grants ZIA AI001270 to L.D.N. and 1ZIAAI001265 to H.C.S.). This program is supported by the Agence Nationale de la Recherche (Grant ANR-10-LABX-69-01). K.K.’s group was supported by the Estonian Research Council, through Grants PRG117 and PRG377. R.H. was supported by an Al Jalila Foundation Seed Grant (Grant AJF202019), Dubai, United Arab Emirates, and a COVID-19 research grant (Grant CoV19-0307) from the University of Sharjah, United Arab Emirates. S.G.T. is supported by Investigator and Program Grants awarded by the National Health and Medical Research Council of Australia and a University of New South Wales COVID Rapid Response Initiative Grant. L.I. reports funding from Regione Lombardia, Italy (project “Risposta immune in pazienti con COVID-19 e co-morbidità”). This research was partially supported by the Instituto de Salud Carlos III (Grant COV20/0968). J.R.H. reports funding from Biomedical Advanced Research and Development Authority (Grant HHSO10201600031C). S.O. reports funding from Research Program on Emerging and Re-emerging Infectious Diseases from Japan Agency for Medical Research and Development (Grant JP20fk0108531). G.G. was supported by the ANR Flash COVID-19 program and SARS-CoV-2 Program of the Faculty of Medicine from Sorbonne University iCOVID programs. The 3C Study was conducted under a partnership agreement between INSERM, Victor Segalen Bordeaux 2 University, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also supported by the Caisse Nationale d’Assurance Maladie des Travailleurs Salariés, Direction générale de la Santé, Mutuelle Générale de l’Education Nationale, Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Program “Cohortes et collections de données biologiques.” S. Debette was supported by the University of Bordeaux Initiative of Excellence. P.K.G. reports funding from the National Cancer Institute, NIH, under Contract 75N91019D00024, Task Order 75N91021F00001. J.W. is supported by a Research Foundation - Flanders (FWO) Fundamental Clinical Mandate (Grant 1833317N). Sample processing at IrsiCaixa was possible thanks to the crowdfunding initiative YoMeCorono. Work at Vall d’Hebron was also partly supported by research funding from Instituto de Salud Carlos III Grant PI17/00660 cofinanced by the European Regional Development Fund (ERDF/FEDER). C.R.-G. and colleagues from the Canarian Health System Sequencing Hub were supported by the Instituto de Salud Carlos III (Grants COV20_01333 and COV20_01334), the Spanish Ministry for Science and Innovation (RTC-2017-6471-1; AEI/FEDER, European Union), Fundación DISA (Grants OA18/017 and OA20/024), and Cabildo Insular de Tenerife (Grants CGIEU0000219140 and “Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19”). T.H.M. was supported by grants from the Novo Nordisk Foundation (Grants NNF20OC0064890 and NNF21OC0067157). C.M.B. is supported by a Michael Smith Foundation for Health Research Health Professional-Investigator Award. P.Q.H. and L. Hammarström were funded by the European Union’s Horizon 2020 research and innovation program (Antibody Therapy Against Coronavirus consortium, Grant 101003650). Work at Y.-L.L.’s laboratory in the University of Hong Kong (HKU) was supported by the Society for the Relief of Disabled Children. MBBS/PhD study of D.L. in HKU was supported by the Croucher Foundation. J.L.F. was supported in part by the Evaluation-Orientation de la Coopération Scientifique (ECOS) Nord - Coopération Scientifique France-Colombie (ECOS-Nord/Columbian Administrative department of Science, Technology and Innovation [COLCIENCIAS]/Colombian Ministry of National Education [MEN]/Colombian Institute of Educational Credit and Technical Studies Abroad [ICETEX, Grant 806-2018] and Colciencias Contract 713-2016 [Code 111574455633]). A. Klocperk was, in part, supported by Grants NU20-05-00282 and NV18-05-00162 issued by the Czech Health Research Council and Ministry of Health, Czech Republic. L.P. was funded by Program Project COVID-19 OSR-UniSR and Ministero della Salute (Grant COVID-2020-12371617). I.M. is a Senior Clinical Investigator at the Research Foundation–Flanders and is supported by the CSL Behring Chair of Primary Immunodeficiencies (PID); by the Katholieke Universiteit Leuven C1 Grant C16/18/007; by a Flanders Institute for Biotechnology-Grand Challenges - PID grant; by the FWO Grants G0C8517N, G0B5120N, and G0E8420N; and by the Jeffrey Modell Foundation. I.M. has received funding under the European Union’s Horizon 2020 research and innovation program (Grant Agreement 948959). E.A. received funding from the Hellenic Foundation for Research and Innovation (Grant INTERFLU 1574). M. Vidigal received funding from the São Paulo Research Foundation (Grant 2020/09702-1) and JBS SA (Grant 69004). The NH-COVAIR study group consortium was supported by a grant from the Meath Foundation.Peer reviewe

Lung microbiome on admission in critically ill patients with acute bacterial and viral pneumonia

Abstract Composition of pulmonary microbiome of patients with severe pneumonia is poorly known. The aim of this work was to analyse the lung microbiome of patients admitted to the intensive care unit  (ICU) with severe community acquired pneumonia (CAP) between 2019 and 2021 in comparison with a control group of 6 patients undergoing digestive surgery. As a second objective, the diagnostic capabilities of metagenomics was also studied in a small group of selected patients. The lung microbiome of patients with viral (5 with Influenza A and 8 with SARS-CoV-2) pneumonia at admission showed a similar diversity as the control group (p = 0.140 and p = 0.213 respectively). Contrarily, the group of 12 patients with pneumococcal pneumonia showed a significant lower Simpson´s index (p = 0.002). In the control group (n = 6) Proteobacteria (36.6%), Firmicutes (24.2%) and Actinobacteria (23.0%) were the predominant phyla. In SARS-CoV-2 patients (n = 8), there was a predominance of Proteobacteria (mean 41.6%) (Moraxella and Pelomonas at the genus level), Actinobacteria (24.6%) (Microbacterium) and Firmicutes (22.8%) mainly Streptococcus, Staphylococcus and Veillonella. In patients with Influenza A pneumonia (n = 5) there was a predominance of Firmicutes (35.1%) mainly Streptococcus followed by Proteobacteria (29.2%) (Moraxella, Acinetobacter and Pelomonas). In the group of pneumococcal pneumonia (n = 12) two phyla predominated: Firmicutes (53.1%) (Streptococcus) and Proteobacteria (36.5%) (Haemophilus). In the 7 patients with non-pneumococcal bacterial pneumonia Haemophilus influenzae (n = 2), Legionella pneumophila (n = 2), Klebsiella pneumoniae, Streptococcus pyogenes and Leptospira were detected by metagenomics, confirming the diagnosis done using conventional microbiological techniques. The diversity of the respiratory microbiome in patients with severe viral pneumonia at ICU admission was similar to that of the control group. Contrarily, patients with pneumococcal pneumonia showed a lower grade of diversity. At initial stages of SARS-CoV-2 infection, no important alterations in the pulmonary microbiome were observed. The analysis of bacterial microbiome showed promising results as a diagnostic tool

Human metapneumovirus as cause of severe community-acquired pneumonia in adults: insights from a ten-year molecular and epidemiological analysis

Human metapneumovirus; Severe community-acquired pneumonia; BiomarkersMetapneumovirus humano; Neumonía severa adquirida en la comunidad; BiomarcadoresMetapneumovirus humà; Pneumònia greu adquirida a la comunitat; BiomarcadorsBackground Information on the clinical, epidemiological and molecular characterization of human metapneumovirus in critically ill adult patients with severe community-acquired pneumonia (CAP) and the role of biomarkers identifying bacterial coinfection is scarce. Methods This is a retrospective epidemiological study of adult patients with hMPV severe CAP admitted to ICU during a ten-year period with admission PSI score ≥ 3. Results The 92.8% of the 28 patients with severe CAP due to human metapneumovirus were detected during the first half of the year. Median age was 62 years and 60.7% were male. The genotyping of isolated human metapneumovirus showed group B predominance (60.7%). All patients had acute respiratory failure. Median APACHE II and SOFA score were 13 and 6.55, respectively. The 25% were coinfected with Streptococcus pneumoniae. 60.7% of the patients had shock at admission and 50% underwent mechanical ventilation. Seven patients developed ARDS, three of them younger than 60 years and without comorbidities. Mortality in ICU was 14.3%. Among survivors, ICU and hospital stay were 6.5 and 14 days, respectively. Plasma levels of procalcitonin were higher in patients with bacterial coinfection (18.2 vs 0.54; p < 0.05). The levels of C-reactive protein, however, were similar. Conclusion Human metapneumovirus was associated with severe CAP requiring ICU admission among elderly patients or patients with comorbidities, but also in healthy young subjects. These patients often underwent mechanical ventilation with elevated health resource consumption. While one out of four patients showed pneumococcal coinfection, plasma procalcitonin helped to implement antimicrobial stewardship