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Ntalouka MP, Brotis A, Mermiri M, Pagonis A, Chatzis A, Bareka M, Kotsi P, Pantazopoulos I, Gourgoulianis K, Arnaoutoglou EM. Predicting the Outcome of Patients with Severe COVID-19 with Simple Inflammatory Biomarkers: The Utility of Novel Combined Scores-Results from a European Tertiary/Referral Centre. J Clin Med 2024; 13:967. [PMID: 38398280 PMCID: PMC10889418 DOI: 10.3390/jcm13040967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 12/29/2023] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
Background: The clinical significance of combinations of inflammatory biomarkers in severe COVID-19 infection is yet to be proved. Although several studies have evaluated the prognostic value of biomarkers in patients with COVID-19, there are limited data regarding the value of the combination scores that could take full advantage of the prognostic value of several biomarkers and that could account for the heterogeneity of patients with severe COVID-19. We investigated the prognostic value of combination scores of admission values of inflammatory biomarkers in adults with severe COVID-19. Methods: Adults admitted to the Department of Respiratory Medicine of the UHL with severe COVID-19 (April-September 2021, NCT05145751) were included. Demographics, medical history, laboratory tests and outcome (high-flow nasal cannula (HFNC), admission to Intensive Care Unit (ICU) or death) were recorded. The optimal cut-off points of on admission values of C-reactive protein (CRP), CRP to lymphocyte ratio (CLR), lymphocyte to neutrophil ratio (LNR) and derived variation of neutrophil to lymphocyte ratio (dv-NLR (neutrophil/white blood count-lymphocyte)) for the predetermined outcome were defined. Based on the cut-off of CRP, LNR, dv-NLR and CLR, which were found to be predictors for HFNC, 3 scores were defined: CRP and LNR (C-CRP #1), CRP and dv-NLR (C-CRP #2), CRP and CLR (C-CRP #3). Likewise, based on the cut-off of CRP and CLR, which were found to be predictors for death, the score of CRP and CLR (C-CRP #3*) was defined. The combination scores were then classified as: 2 points (both biomarkers elevated); 1 point (one biomarker elevated) and 0 points (normal values). None of the biomarkers was predictive for the ICU admission, so no further analysis was performed. Binomial logistic regression analysis was used to establish the predictive role for each biomarker. Results: One hundred and fifteen patients (60% males, mean age 57.7 years) were included. Thirty-seven (32.2%) patients required HFNC, nine (7.8%) died and eight (7%) were admitted to ICU, respectively. As far as HFNC is concerned, the cut-off point was 3.2 for CRP, 0.231 for LNR, 0.90 for dv-NLR and 0.004 for CLR. Two points of C-CRP #1 and 2 points of C-CRP #3 predicted HFNC with a probability as high as 0.625 (p = 0.005) and 0.561 (p < 0.001), respectively. Moreover, 1 point of C-CRP #2 and 2 points of C-CRP #2 predicted HFNC with a probability of 0.333 and 0.562, respectively. For death, the optimal cut-off point for CRP was 1.11 and for CLR 3.2*1033. Two points of C-CRP #3* with an accuracy of 0.922 predicted mortality (p = 0.0038) in severe COVID-19. Conclusions: The combination scores of CRP and inflammatory biomarkers, based on admission values, are promising predictors for respiratory support using HFNC and for mortality in patients suffering from severe COVID-19 infection.
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Affiliation(s)
- Maria P. Ntalouka
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa University Hospital, 41110 Larissa, Greece; (M.P.N.); (M.M.); (A.C.); (M.B.)
| | - Alexandros Brotis
- Department of Neurosurgery, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa University Hospital, 41110 Larissa, Greece;
| | - Maria Mermiri
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa University Hospital, 41110 Larissa, Greece; (M.P.N.); (M.M.); (A.C.); (M.B.)
| | - Athanasios Pagonis
- Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, 41110 Larissa, Greece; (A.P.); (I.P.); (K.G.)
| | - Athanasios Chatzis
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa University Hospital, 41110 Larissa, Greece; (M.P.N.); (M.M.); (A.C.); (M.B.)
| | - Metaxia Bareka
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa University Hospital, 41110 Larissa, Greece; (M.P.N.); (M.M.); (A.C.); (M.B.)
| | - Paraskevi Kotsi
- Department of Transfusion Medicine, University of Thessaly, 41110 Larissa, Greece;
| | - Ioannis Pantazopoulos
- Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, 41110 Larissa, Greece; (A.P.); (I.P.); (K.G.)
- Department of Emergency Medicine, Faculty of Medicine, University of Thessaly, 41110 Larissa, Greece
| | - Konstantinos Gourgoulianis
- Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, 41110 Larissa, Greece; (A.P.); (I.P.); (K.G.)
| | - Eleni M. Arnaoutoglou
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa University Hospital, 41110 Larissa, Greece; (M.P.N.); (M.M.); (A.C.); (M.B.)
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Tahavvori A, Mosaddeghi-Heris R, Ghanbari Sevari F, Alavi SMA, Panahi P, Abbasi N, Rahmani Youshanlouei H, Hejazian SS. Combined systemic inflammatory indexes as reflectors of outcome in patients with COVID‑19 infection admitted to ICU. Inflammopharmacology 2023; 31:2337-2348. [PMID: 37550520 DOI: 10.1007/s10787-023-01308-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023]
Abstract
INTRODUCTION The principal etiology of mortality in COVID-19 patients is the systemic pro-inflammatory processes which may lead to acute respiratory distress syndrome. Hematologic indices are reachable representatives of inflammation in patients with COVID-19 infection. The purpose of the current study was to evaluate the potential predictive value of these inflammatory indices in the in-hospital mortality of ICU-admitted COVID-19 patients. The studied indexes included AISI, dNLR, NLPR, NLR, SII, and SIRI. METHOD 315 COVID-19 patients admitted to ICU managed in Imam Khomeini Hospital of Urmia, Iran, during the last 6 months of 2020 were retrospectively enrolled in the study and divided into two subgroups based on their final outcome, discharge or death. RESULTS Total leucocyte count (TLC), absolute neutrophil count (NLC), urea, Cr, RDW, AISI, dNLR, NLPR, NLR, SII, and SIRI were drastically elevated in the dead patients (P < 0.05). The optimal cut-off points for AISI (378.81), dNLR (5.66), NLPR (0.03), NLR (5.97), SII (1589.25), and SIRI (2.31) were obtained using ROC curves. NLR and SII had the highest sensitivity (71.4%) and specificity (73.6%), respectively. Patients with above-cut-off levels of ISI, dNLR, NLPR, NLR, and SII had lower average survival time. Age (OR = 1.057, CI95%: 1.030-1.085, p < 0.001) and dNLR (OR = 1.131, CI95%: 1.061-1.206, p < 0.001) were the independent predictors for mortality in the studied COVID-19 patients based on multivariate logistic regression. CONCLUSION Age and dNLR are valuable predictive factors for in-hospital death of ICU-admitted COVID-19 patients. Besides, other indices, AISI, NLPR, NLR, SII, and SIRI, may have an additional role that requires further investigation.
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Affiliation(s)
- Amir Tahavvori
- Department of Internal Medicine, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran
| | - Reza Mosaddeghi-Heris
- Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran
| | - Faezeh Ghanbari Sevari
- Hematology and Oncology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | - Peghah Panahi
- Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Niloufar Abbasi
- Department of Internal Medicine, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran
| | | | - Seyyed Sina Hejazian
- Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.
- Immunology Research Center, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
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Radkhah H, Mansouri ES, Rahimipour Anaraki S, Gholizadeh Mesgarha M, Sheikhy A, Khadembashiri MM, Khadembashiri MA, Eslami M, Mahmoodi T, Inanloo B, Pour Mohammad A. Predictive value of hematological indices on incidence and severity of pulmonary embolism in COVID-19 patients. Immun Inflamm Dis 2023; 11:e1012. [PMID: 37773719 PMCID: PMC10540144 DOI: 10.1002/iid3.1012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/28/2023] [Accepted: 08/31/2023] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND Pulmonary thromboembolism (PTE) is a common complication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which raises the COVID-19 disease's fatality rate from 3% to 45%. Nevertheless, due to fairly indistinguishable clinical symptoms and a lack of validated clinical prediction models, PTE diagnosis in COVID-19 patients is challenging. This study aims to investigate the applicability of hematological indices to predict PTE incidence and its severity in SARS-CoV-2 patients. METHODS A retrospective cohort study was conducted on hospitalized patients with a confirmed diagnosis of SARS-CoV-2 infection who underwent CT angiography to assess probable PTE in them. The correlation between complete blood count parameters 1 day before CT angiography and CT angiography outcomes, and simplified pulmonary embolism severity index (s-PESI) was investigated. RESULTS We discovered that among individuals with a probable PTE, males and those with higher platelet-to-lymphocyte (PLR) and neutrophil-to-lymphocyte (NLR) ratios had a greater likelihood of PTE incidence (p < .001, .027, and .037, respectively). PLR was a significant and independent predictor of PTE with a p value of .045. Moreover, a higher neutrophil count was associated with a higher s-PESI score in COVID-19 patients developing PTE (p: .038). CONCLUSIONS Among hematological indices, NLR and more precisely PLR are cost-effective and simply calculable markers that can assist physicians in determining whether or not COVID-19 patients with clinically probable PTE require CT angiography and the higher neutrophil count can be employed as an indicator of PTE severity in COVID-19 patients. Further large multicenter and prospective studies are warranted to corroborate these observations.
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Affiliation(s)
- Hanieh Radkhah
- Department of Internal Medicine, School of Medicine, Sina HospitalTehran University of Medical Sciences (TUMS)TehranIran
| | - Ensieh Sadat Mansouri
- Department of Internal Medicine, School of Medicine, Sina HospitalTehran University of Medical Sciences (TUMS)TehranIran
| | | | | | - Ali Sheikhy
- Students' Scientific Research CenterTehran University of Medical Sciences (TUMS)TehranIran
| | | | | | - Mohamad Eslami
- Students' Scientific Research CenterTehran University of Medical Sciences (TUMS)TehranIran
| | - Tara Mahmoodi
- Students' Scientific Research CenterTehran University of Medical Sciences (TUMS)TehranIran
| | - Behnaz Inanloo
- Sina HospitalTehran University of Medical Sciences (TUMS)TehranIran
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Asperges E, Albi G, Zuccaro V, Sambo M, Pieri TC, Calia M, Colaneri M, Maiocchi L, Melazzini F, Lasagna A, Peri A, Mojoli F, Sacchi P, Bruno R. Dynamic NLR and PLR in Predicting COVID-19 Severity: A Retrospective Cohort Study. Infect Dis Ther 2023:10.1007/s40121-023-00813-1. [PMID: 37198387 DOI: 10.1007/s40121-023-00813-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 04/18/2023] [Indexed: 05/19/2023] Open
Abstract
INTRODUCTION The hyperinflammation phase of severe SARS-CoV-2 is characterised by complete blood count alterations. In this context, the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) can be used as prognostic factors. We studied NLR and PLR trends at different timepoints and computed optimal cutoffs to predict four outcomes: use of continuous positive airways pressure (CPAP), intensive care unit (ICU) admission, invasive ventilation and death. METHODS We retrospectively included all adult patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia admitted from 23 January 2020 to 18 May 2021. Analyses included non-parametric tests to study the ability of NLR and PLR to distinguish the patients' outcomes at each timepoint. Receiver operating characteristic (ROC) curves were built for NLR and PLR at each timepoint (minus discharge) to identify cutoffs to distinguish severe and non-severe disease. Their statistical significance was assessed with the chi-square test. Collection of data under the SMACORE database was approved with protocol number 20200046877. RESULTS We included 2169 patients. NLR and PLR were higher in severe coronavirus disease 2019 (COVID-19). Both ratios were able to distinguish the outcomes at each timepoint. For NLR, the areas under the receiver operating characteristic curve (AUROC) ranged between 0.59 and 0.81, and for PLR between 0.53 and 0.67. From each ROC curve we computed an optimal cutoff value. CONCLUSION NLR and PLR cutoffs are able to distinguish severity grades and mortality at different timepoints during the course of disease, and, as such, they allow a tailored approach. Future prospects include validating our cutoffs in a prospective cohort and comparing their performance against other COVID-19 scores.
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Affiliation(s)
- Erika Asperges
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Giuseppe Albi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100, Pavia, Italy
| | - Valentina Zuccaro
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Margherita Sambo
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
- Dipartimento di Scienze Clinico-Chirurgiche, Diagnostiche e Pediatriche-Università di Pavia, Pavia, Italy
| | - Teresa C Pieri
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
- Dipartimento di Scienze Clinico-Chirurgiche, Diagnostiche e Pediatriche-Università di Pavia, Pavia, Italy
| | - Matteo Calia
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
- Dipartimento di Scienze Clinico-Chirurgiche, Diagnostiche e Pediatriche-Università di Pavia, Pavia, Italy
| | - Marta Colaneri
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Laura Maiocchi
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Federica Melazzini
- U.O.C. Medicina Interna Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Angioletta Lasagna
- U.O.C. Oncologia Medica Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Andrea Peri
- Dipartimento di Chirurgia Fondazione, IRCCS Policlinico San Matteo, Pavia, Italy
| | - Francesco Mojoli
- U.O.C. Anestesia e Rianimazione Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Paolo Sacchi
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Raffaele Bruno
- U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
- Dipartimento di Scienze Clinico-Chirurgiche, Diagnostiche e Pediatriche-Università di Pavia, Pavia, Italy.
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Fernandes NF, Costa IF, Pereira KN, de Carvalho JAM, Paniz C. Hematological ratios in coronavirus disease 2019 patients with and without invasive mechanical ventilation. J Investig Med 2023; 71:321-328. [PMID: 36680362 DOI: 10.1177/10815589221149189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Patients with the most severe form of coronavirus disease 2019 (COVID-19) often require invasive ventilation. Determining the best moment to intubate a COVID-19 patient is complex decision and can result in important consequences for the patient. Therefore, markers that could aid in clinical decision-making such as hematological indices are highly useful. These markers are easy to calculate, do not generate extra costs for the laboratory, and are readily implemented in routine practice. Thus, this study aimed to investigate differences in the ratios calculated from the hemogram between patients with and without the need for invasive mechanical ventilation (IMV) and a control group. This was an observational retrospective analysis of 212 patients with COVID-19 that were hospitalized between April 1, 2020 and March 31, 2021 who were stratified as IMV (n = 129) or did not require invasive mechanical ventilation (NIMV) (n = 83). A control group of 198 healthy individuals was also included. From the first hemogram of each patient performed after admission, the neutrophil-to-lymphocyte ratio (NLR), the derived NLR (d-NLR), the lymphocyte-to-monocyte ratio, the platelet-to-lymphocyte ratio, the neutrophil-to-platelet ratio (NPR), and the systemic immune-inflammation index (SII) were calculated. All hematological ratios exhibited significant differences between the control group and COVID-19 patients. NLR, d-NLR, SII, and NPR were higher in the IMV group than they were in the NIMV group. The hematological indices addressed in this study demonstrated high potential for use as auxiliaries in clinical decision-making regarding the need for IMV.
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Affiliation(s)
- Natieli Flores Fernandes
- Departamento de Análises Clínicas e Toxicológicas, Universidade Federal de Santa Maria, Santa Maria, Brazil
| | - Isabella Ferreira Costa
- Departamento de Análises Clínicas e Toxicológicas, Universidade Federal de Santa Maria, Santa Maria, Brazil
| | - Karla Nunes Pereira
- Departamento de Análises Clínicas e Toxicológicas, Universidade Federal de Santa Maria, Santa Maria, Brazil
- Laboratório de Análises Clínicas, Hospital Universitário, Universidade Federal de Santa Maria, Santa Maria, Brazil
| | - José Antonio Mainardi de Carvalho
- Departamento de Análises Clínicas e Toxicológicas, Universidade Federal de Santa Maria, Santa Maria, Brazil
- Laboratório de Análises Clínicas, Hospital Universitário, Universidade Federal de Santa Maria, Santa Maria, Brazil
| | - Clóvis Paniz
- Departamento de Análises Clínicas e Toxicológicas, Universidade Federal de Santa Maria, Santa Maria, Brazil
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Buttia C, Llanaj E, Raeisi-Dehkordi H, Kastrati L, Amiri M, Meçani R, Taneri PE, Ochoa SAG, Raguindin PF, Wehrli F, Khatami F, Espínola OP, Rojas LZ, de Mortanges AP, Macharia-Nimietz EF, Alijla F, Minder B, Leichtle AB, Lüthi N, Ehrhard S, Que YA, Fernandes LK, Hautz W, Muka T. Prognostic models in COVID-19 infection that predict severity: a systematic review. Eur J Epidemiol 2023; 38:355-372. [PMID: 36840867 PMCID: PMC9958330 DOI: 10.1007/s10654-023-00973-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 01/28/2023] [Indexed: 02/26/2023]
Abstract
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.
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Affiliation(s)
- Chepkoech Buttia
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Emergency Department, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 16C, 3010 Bern, Switzerland
- Epistudia, Bern, Switzerland
| | - Erand Llanaj
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
- ELKH-DE Public Health Research Group of the Hungarian Academy of Sciences, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
- Epistudia, Bern, Switzerland
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Hamidreza Raeisi-Dehkordi
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Lum Kastrati
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Mojgan Amiri
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Renald Meçani
- Department of Pediatrics, “Mother Teresa” University Hospital Center, Tirana, University of Medicine, Tirana, Albania
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Petek Eylul Taneri
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- HRB-Trials Methodology Research Network College of Medicine, Nursing and Health Sciences University of Galway, Galway, Ireland
| | | | - Peter Francis Raguindin
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Swiss Paraplegic Research, Nottwil, Switzerland
- Faculty of Health Sciences, University of Lucerne, Lucerne, Switzerland
| | - Faina Wehrli
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Farnaz Khatami
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
- Department of Community Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Octavio Pano Espínola
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Department of Preventive Medicine and Public Health, University of Navarre, Pamplona, Spain
- Navarra Institute for Health Research, IdiSNA, Pamplona, Spain
| | - Lyda Z. Rojas
- Research Group and Development of Nursing Knowledge (GIDCEN-FCV), Research Center, Cardiovascular Foundation of Colombia, Floridablanca, Santander, Colombia
| | | | | | - Fadi Alijla
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Beatrice Minder
- Public Health and Primary Care Library, University Library of Bern, University of Bern, Bern, Switzerland
| | - Alexander B. Leichtle
- University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, and Center for Artificial Intelligence in Medicine (CAIM), University of Bern, Bern, Switzerland
| | - Nora Lüthi
- Emergency Department, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 16C, 3010 Bern, Switzerland
| | - Simone Ehrhard
- Emergency Department, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 16C, 3010 Bern, Switzerland
| | - Yok-Ai Que
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Laurenz Kopp Fernandes
- Deutsches Herzzentrum Berlin (DHZB), Berlin, Germany
- Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Wolf Hautz
- Emergency Department, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 16C, 3010 Bern, Switzerland
| | - Taulant Muka
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Epistudia, Bern, Switzerland
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Thungthienthong M, Vattanavanit V. Platelet-to-White Blood Cell Ratio as a Predictor of Mortality in Patients with Severe COVID-19 Pneumonia: A Retrospective Cohort Study. Infect Drug Resist 2023; 16:445-455. [PMID: 36718462 PMCID: PMC9884061 DOI: 10.2147/idr.s398731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 01/18/2023] [Indexed: 01/25/2023] Open
Abstract
Purpose Complete blood count (CBC) parameters are widely used as predictors of Coronavirus disease 2019 (COVID-19) severity. However, the clinical significance of these markers in severe COVID-19 pneumonia remains unclear. This study aimed to investigate the role of CBC parameters in predicting mortality in patients with severe COVID-19 pneumonia. Patients and Methods We conducted a retrospective study at a tertiary care center in southern Thailand. Between January 2020 and December 2021, adult patients who had been diagnosed with severe COVID-19 pneumonia were enrolled. Demographic and clinical data, including CBC data on admission, were analyzed and compared between survivors and non-survivors. Results A total of 215 patients with severe COVID-19 pneumonia were enrolled. The in-hospital mortality was 29.3%. Non-survivors had a significantly lower platelet-to-white blood cell ratio (PWR) than survivors (15.8 vs 29.0, p < 0.001). PWR had the best accuracy in predicting in-hospital mortality, with an area under the curve (AUC) of the receiver operating characteristic curve of 0.801, followed by the CURB-65 of 0.789. Conclusion PWR appears to be a simple independent predictor of mortality in patients with severe COVID-19 pneumonia.
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Affiliation(s)
- Metus Thungthienthong
- Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand
| | - Veerapong Vattanavanit
- Critical Care Medicine Unit, Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand,Correspondence: Veerapong Vattanavanit, Critical Care Medicine Unit, Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, 15 Kanjanavanich Road, Hat Yai, Songkhla, 90110, Thailand, Tel +66848456228, Fax +6674429385, Email
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Coşkun S, Güngörer V, Öner N, Sezer M, Karagöl C, Tekin ZE, Tekgöz PN, Kaplan MM, Polat MC, Çelikel E, Acar BÇ. The role of indices in predicting disease severity and outcomes of multisystem inflammatory syndrome in children. Pediatr Int 2023; 65:e15609. [PMID: 37674297 DOI: 10.1111/ped.15609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 05/23/2023] [Accepted: 06/23/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND The aim of this study was to evaluate the role of the systemic immune inflammation index (SII), C-reactive protein/albumin ratio (CAR), the monocyte/lymphocyte ratio (MLR), and the neutrophil/lymphocyte ratio (NLR) in predicting disease severity, treatment, and prognosis in multisystem inflammatory syndrome in children (MIS-C). METHODS This medical record review retrospectively evaluated the clinical and laboratory findings of 191 MIS-C patients followed in the Department of Pediatric Rheumatology at Ankara City Hospital, Turkey. The patients were grouped by disease severity: mild, moderate, and severe. SII, CAR, MLR, and NLR were calculated for each group. RESULTS All patients had fever at the time of admission; 153 (80.1%) had gastrointestinal tract involvement, 74 (38.7%) had rash, 63 (33%) had conjunctivitis, 107 (56%) had cardiac involvement, 32 (15.6%) had renal involvement, and 143 (74.9%) had hematological involvement. According to logistic regression analysis, SII, NLR, MLR, and CAR were found to be predictive indexes for disease severity, need for intensive care, need for inotropes, and anakinra treatment in MIS-C. The cut-off values of ≥1605.3 for SII, ≥9.1 for NLR, and ≥3.9 for CAR increased the risk of severe disease by 3.4, 7.1, and 5.7 times, respectively. CONCLUSION NLR, SII, MLR, and CAR are effective and useful for predicting the severity of MIS-C, the need for intensive care, and the need for anakinra treatment.
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Affiliation(s)
- Serkan Coşkun
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Vildan Güngörer
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Nimet Öner
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Müge Sezer
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Cüneyt Karagöl
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Zahide Ekici Tekin
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Pakize Nilüfer Tekgöz
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Melike Mehveş Kaplan
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Merve Cansu Polat
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Elif Çelikel
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
| | - Banu Çelikel Acar
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Health Sciences, Ankara City Hospital, Ankara, Turkey
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9
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Anbarli Metin D, Metin H, Atiş S. The modified systemic inflammation score is a predictor of ICU admission of COVID-19 patients. JOURNAL OF ACUTE DISEASE 2023. [DOI: 10.4103/2221-6189.369074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023] Open
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10
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Qin R, He L, Yang Z, Jia N, Chen R, Xie J, Fu W, Chen H, Lin X, Huang R, Luo T, Liu Y, Yao S, Jiang M, Li J. Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis. Clin Rev Allergy Immunol 2023; 64:33-65. [PMID: 35040086 PMCID: PMC8763427 DOI: 10.1007/s12016-021-08908-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/29/2021] [Indexed: 01/26/2023]
Abstract
Abnormal immunological indicators associated with disease severity and mortality in patients with COVID-19 have been reported in several observational studies. However, there are marked heterogeneities in patient characteristics and research methodologies in these studies. We aimed to provide an updated synthesis of the association between immune-related indicators and COVID-19 prognosis. We conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune-related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes. A total of 145 studies were included in the current meta-analysis, with 26 immunological, 11 hematological, 5 inflammatory, 4 coagulation, and 10 biochemical variables reported. Of them, levels of cytokines, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, IgG, and CD4+ T/CD8+ T cell ratio, WBC, neutrophil, platelet, ESR, CRP, ferritin, SAA, D-dimer, FIB, and LDH were significantly increased in severely ill patients or non-survivors. Moreover, non-severely ill patients or survivors presented significantly higher counts of lymphocytes, monocytes, lymphocyte/monocyte ratio, eosinophils, CD3+ T,CD4+T and CD8+T cells, B cells, and NK cells. The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19 containing IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells, and their subtype CD4+ and CD8+ T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with poor prognosis. Therefore, parameters of immune response dysfunction combined with inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict severe patients and those non-survivors.
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Affiliation(s)
- Rundong Qin
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Li He
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Zhaowei Yang
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Nan Jia
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Ruchong Chen
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Jiaxing Xie
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Wanyi Fu
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Hao Chen
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Xinliu Lin
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Renbin Huang
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Tian Luo
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Yukai Liu
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Siyang Yao
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Mei Jiang
- grid.470124.4National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
| | - Jing Li
- grid.470124.4Department of Allergy and Clinical Immunology, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong China
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Gutiérrez-Pérez IA, Buendía-Roldán I, Pérez-Rubio G, Chávez-Galán L, Hernández-Zenteno RDJ, Aguilar-Duran H, Fricke-Galindo I, Zaragoza-García O, Falfán-Valencia R, Guzmán-Guzmán IP. Outcome predictors in COVID-19: An analysis of emergent systemic inflammation indices in Mexican population. Front Med (Lausanne) 2022; 9:1000147. [PMID: 36341268 PMCID: PMC9633849 DOI: 10.3389/fmed.2022.1000147] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/30/2022] [Indexed: 01/08/2023] Open
Abstract
Introduction The systemic viral disease caused by the SARS-CoV-2 called coronavirus disease 2019 (COVID-19) continues to be a public health problem worldwide. Objective This study is aimed to evaluate the association and predictive value of indices of systemic inflammation with severity and non-survival of COVID-19 in Mexican patients. Materials and Methods A retrospective study was carried out on 807 subjects with a confirmed diagnosis of COVID-19. Clinical characteristics, acute respiratory distress syndrome (ARDS), severity according to PaO2/FiO2 ratio, invasive mechanical ventilation (IMV), and non-survival outcome were considered to assess the predictive value and the association of 11 systemic inflammatory indices derived from hematological parameters analyzed at the hospital admission of patients. The receiver operating characteristics curve was applied to determine the thresholds for 11 biomarkers, and their prognostic values were assessed via the Kaplan-Meier method. Results 26% of the studied subjects showed COVID-19 severe (PaO2/FiO2 ratio ≤ 100), 82.4% required IMV, and 39.2% were non-survival. The indices NHL, NLR, RDW, dNLR, and SIRI displayed predictive values for severe COVID-19 and non-survival. NHL, SIRI, and NLR showed predictive value for IMV. The cut-off values for RDW (OR = 1.85, p < 0.001), NHL (OR = 1.67, p = 0.004) and NLR (OR = 1.56, p = 0.012) were mainly associated with severe COVID-19. NHL (OR = 3.07, p < 0.001), AISI (OR = 2.64, p < 0.001) and SIRI (OR = 2.51, p < 0.001) were associated with IMV support, while for non-survival the main indices associated were NHL (OR = 2.65, p < 0.001), NLR (OR = 2.26, p < 0.001), dNLR (OR = 1.92, p < 0.001), SIRI (OR = 1.67, p = 0.002) and SII (OR = 1.50, p = 0.010). The patients with an RDW, PLR, NLR, dNLR, MLR, SII, and NHL above the cut-off had a survival probability of COVID-19 50% lower, with an estimated mean survival time of 40 days. Conclusion The emergent systemic inflammation indices NHL, NLR, RDW, SII, and SIRI have a predictive power of severe COVID-19, IMV support, and low survival probability during hospitalization by COVID-19 in Mexican patients.
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Affiliation(s)
- Ilse Adriana Gutiérrez-Pérez
- HLA Laboratory, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
- Faculty of Chemical-Biological Sciences, Universidad Autónoma de Guerrero, Chilpancingo, Mexico
| | - Ivette Buendía-Roldán
- Translational Research Laboratory on Aging and Pulmonary Fibrosis, Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, Mexico City, Mexico
| | - Gloria Pérez-Rubio
- HLA Laboratory, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Leslie Chávez-Galán
- Laboratory of Integrative Immunology, Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, Mexico City, Mexico
| | | | - Hiram Aguilar-Duran
- Translational Research Laboratory on Aging and Pulmonary Fibrosis, Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, Mexico City, Mexico
| | - Ingrid Fricke-Galindo
- HLA Laboratory, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Oscar Zaragoza-García
- Faculty of Chemical-Biological Sciences, Universidad Autónoma de Guerrero, Chilpancingo, Mexico
| | - Ramcés Falfán-Valencia
- HLA Laboratory, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
- *Correspondence: Ramcés Falfán-Valencia,
| | - Iris Paola Guzmán-Guzmán
- Faculty of Chemical-Biological Sciences, Universidad Autónoma de Guerrero, Chilpancingo, Mexico
- Iris Paola Guzmán-Guzmán,
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Ayalew G, Mulugeta B, Haimanot Y, Adane T, Bayleyegn B, Abere A. Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio Can Predict the Severity in COVID-19 Patients from Ethiopia: A Retrospective Study. Int J Gen Med 2022; 15:7701-7708. [PMID: 36238542 PMCID: PMC9553031 DOI: 10.2147/ijgm.s383558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 09/30/2022] [Indexed: 11/23/2022] Open
Abstract
Background Coronaviruses are a broad family of pathogens that can cause mild to severe respiratory illnesses. Due to a strong inflammatory response and a weak immunological response, viral pneumonia inflammation, like Coronavirus Disease 2019 (COVID-19), displays an unbalanced immune response. Therefore, circulating biomarkers of inflammation and the immune system can serve as reliable predictors of a patient's prognosis for COVID-19. Hematological ratios are reliable markers of inflammation that are frequently utilized in pneumonia, primarily in viral infections with low cost in developing countries. Purpose To examine the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in predicting the severity of COVID-19 patients. Methods An institutional-based retrospective study was done on 105 hospitalized COVID-19 patients at the University of Gondar comprehensive specialized referral hospital, Northwest Ethiopia. The laboratory evaluations that were gathered, evaluated, and reported on included the total leucocyte count (TLC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute monocyte count (AMC), NLR, LMR, and PLR. The Kruskal-Wallis test and Wilcoxon matched-pairs signed test were used to see whether there were any differences between the continuous variables. Receiver operating curve (ROC) analysis was used to determine the appropriate cut-off values for NLR, PLR, and LMR. P-value <0.05 was considered a statistically significant association. Results ANC, NLR, and PLR were highest in the critical group (p = 0.001), while this group had the least ALC and LMR (p = 0.001). We calculated the optimal cut-off values of the hematological ratios; NLR (8.4), LMR (1.4), and PLR (18.0). NLR had the highest specificity and sensitivity, at 83.8% and 80.4%, respectively. Conclusion Our research showed that NLR and PLR were good indicators of severity in COVID-19. However, our findings indicate that MLR is not a reliable predictor.
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Affiliation(s)
- Getnet Ayalew
- Department of Medical Microbiology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia,Correspondence: Getnet Ayalew, Department of Medical Microbiology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, P.O.Box: 196, Gondar, Ethiopia, Tel +251-918-73-00-13, Email
| | - Birhan Mulugeta
- Department of Immunology and Molecular Biology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | | | - Tiruneh Adane
- Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Biruk Bayleyegn
- Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Aberham Abere
- Department of Medical Parasitology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
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The Associations of Iron Related Biomarkers with Risk, Clinical Severity and Mortality in SARS-CoV-2 Patients: A Meta-Analysis. Nutrients 2022; 14:nu14163406. [PMID: 36014912 PMCID: PMC9416650 DOI: 10.3390/nu14163406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/04/2022] [Accepted: 08/07/2022] [Indexed: 11/22/2022] Open
Abstract
The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading rapidly around the world and has led to millions of infections and deaths. Growing evidence indicates that iron metabolism is associated with COVID-19 progression, and iron-related biomarkers have great potential for detecting these diseases. However, the results of previous studies are conflicting, and there is not consistent numerical magnitude relationship between those biomarkers and COVID-19. Thereby, we aimed to integrate the results of current studies and to further explore their relationships through a meta-analysis. We searched peer-reviewed literature in PubMed, Scopus and Web of Science up to 31 May 2022. A random effects model was used for pooling standard mean difference (SMD) and the calculation of the corresponding 95% confidence interval (CI). I2 was used to evaluate heterogeneity among studies. A total of 72 eligible articles were included in the meta-analysis. It was found that the ferritin levels of patients increased with the severity of the disease, whereas their serum iron levels and hemoglobin levels showed opposite trends. In addition, non-survivors had higher ferritin levels (SMD (95%CI): 1.121 (0.854, 1.388); Z = 8.22 p for Z < 0.001; I2 = 95.7%, p for I2 < 0.001), lower serum iron levels (SMD (95%CI): −0.483 (−0.597, −0.368), Z = 8.27, p for Z < 0.001; I2 = 0.9%, p for I2 =0.423) and significantly lower TIBC levels (SMD (95%CI): −0.612 (−0.900, −0.324), Z = 4.16, p for Z < 0.001; I2 = 71%, p for I2 = 0.016) than survivors. This meta-analysis demonstrates that ferritin, serum iron, hemoglobin and total iron banding capacity (TIBC) levels are strongly associated with the risk, severity and mortality of COVID-19, providing strong evidence for their potential in predicting disease occurrence and progression.
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Real-Life Use of Tocilizumab in the Treatment of Severe COVID-19 Pneumonia. Adv Virol 2022; 2022:7060466. [PMID: 35721667 PMCID: PMC9203205 DOI: 10.1155/2022/7060466] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 04/09/2022] [Indexed: 12/14/2022] Open
Abstract
Introduction Coronavirus disease 2019 (COVID-19) can progress to severe respiratory compromise and lead to mortality due to induction of cytokine storm. Tocilizumab (TCZ) is approved by the FDA for the treatment of cytokine release syndrome (CRS). This study aims to analyze the outcomes among patients who received TCZ in the United Arab Emirates. Methods A retrospective cohort study was conducted among COVID-19 patients who received TCZ in a tertiary care hospital from May 2020 to August 2021. For analysis, patients were divided into two groups based on survival and clinical improvement. Results Overall, 80% of patients receiving TCZ were discharged by day 28. There was a gradual improvement in oxygen requirements in our patients with a majority of them on room air by day 28. Age more than 50 years (P=0.034) and comorbidities such as cardiovascular disease (CVD) (P=0.002) and renal insufficiency (P=0.013) were significantly associated with mortality. Discussion. In our analysis, patients who were mechanically ventilated at the time of administration of TCZ had a significantly higher risk of death by day 28. In both survived and improved groups, younger patients had better outcomes than older patients. Patients who received TCZ earlier during therapy from the onset of symptoms had better survival outcomes. There was only one death among 14 patients who received vaccination. There was no significant difference in mortality among patients with comorbidities such as diabetes, hypertension, dyslipidemia, obesity, and pulmonary diseases, hypothesizing that administration of TCZ improves the outcomes in COVID-19 patients with these comorbidities.
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Asaduzzaman MD, Romel Bhuia M, Nazmul Alam ZHM, Zabed Jillul Bari M, Ferdousi T. Significance of hemogram‐derived ratios for predicting in‐hospital mortality in COVID‐19: A multicenter study. Health Sci Rep 2022; 5:e663. [PMID: 35686199 PMCID: PMC9172589 DOI: 10.1002/hsr2.663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 03/27/2022] [Accepted: 05/15/2022] [Indexed: 11/10/2022] Open
Abstract
Background To address the problem of resource limitation, biomarkers having a potential for mortality prediction are urgently required. This study was designed to evaluate whether hemogram‐derived ratios could predict in‐hospital deaths in COVID‐19 patients. Materials and Methods This multicenter retrospective study included hospitalized COVID‐19 patients from four COVID‐19 dedicated hospitals in Sylhet, Bangladesh. Data on clinical characteristics, laboratory parameters, and survival outcomes were analyzed. Logistic regression models were fitted to identify the predictors of in‐hospital death. Results Out of 442 patients, 55 (12.44%) suffered in‐hospital death. The proportion of male was higher in nonsurvivor group (61.8%). The mean age was higher in nonsurvivors (69 ± 13 vs. 59 ± 14 years, p < 0.001). Compared to survivors, nonsurvivors exhibited higher frequency of comorbidities, such as chronic kidney disease (34.5% vs. 15.2%, p ≤ 0.001), chronic obstructive pulmonary disease (23.6% vs. 10.6%, p = 0.011), ischemic heart disease (41.8% vs. 19.4%, p < 0.001), and diabetes mellitus (76.4% vs. 61.8%, p = 0.05). Leukocytosis and lymphocytopenia were more prevalent in nonsurvivors (p < 0.05). Neutrophil‐to‐lymphocyte ratio (NLR), derived NLR (d‐NLR), and neutrophil‐to‐platelet ratio (NPR) were significantly higher in nonsurvivors (p < 0.05). After adjusting for potential covariates, NLR (odds ratio [OR] 1.05; 95% confidence interval [CI] 1.009‐1.08), d‐NLR (OR 1.08; 95% CI 1.006‐1.14), and NPR (OR 1.20; 95% CI 1.09‐1.32) have been found to be significant predictors of mortality in hospitalized COVID‐19 patients. The optimal cut‐off points for NLR, d‐NLR, and NPR for prediction of in‐hospital mortality for COVID‐19 patients were 7.57, 5.52 and 3.87, respectively. Conclusion Initial assessment of NLR, d‐NLR, and NPR values at hospital admission is of good prognostic value for predicting mortality of patients with COVID‐19.
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Affiliation(s)
- MD Asaduzzaman
- Department of Medicine Sylhet MAG Osmani Medical College Hospital Sylhet Bangladesh
| | - Mohammad Romel Bhuia
- Department of Statistics Shahjalal University of Science and Technology Sylhet Bangladesh
| | - ZHM Nazmul Alam
- Department of Medicine Sylhet MAG Osmani Medical College Hospital Sylhet Bangladesh
| | | | - Tasnim Ferdousi
- Department of Ophthalmology Bangabandhu Sheikh Mujib Medical University Dhaka Bangladesh
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Ntalouka MP, Pantazopoulos I, Brotis AG, Pagonis A, Vatsiou I, Chatzis A, Rarras CN, Kotsi P, Gourgoulianis KI, Arnaoutoglou EM. Prognostic role of simple inflammatory biomarkers in patients with severe COVID-19: an observational study. Hippokratia 2022; 26:70-77. [PMID: 37188050 PMCID: PMC10177850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
BACKGROUND/AIM Simple inflammatory biomarkers, such as neutrophil to lymphocyte ratio (NLR), could serve as prognosis indicators in patients with Coronavirus disease 2019 (COVID-19). The utility of on-admission inflammatory biomarkers in predicting outcomes was investigated in patients suffering from severe COVID-19 infection. METHODS We performed a retrospective study to assess the role of white blood count (WBC), neutrophils (N), lymphocyte (L), platelets (PLTs), C-reactive protein (CRP), reverse transcription polymerase chain reaction (RT-PCR), NLR (N/L), PLR (P/L), dv (derived variation of)-NLR (N/WBC-L), LNR (L/N), dv (derived variation of)-LNR (L/WBC-N), and CLR (CRP/L), in predicting the need for high-flow nasal cannula (HFNC) use, admission to Intensive Care Unit (ICU), and death in adult patients with severe COVID-19 admitted to the Department of Respiratory Medicine from April to September 2021. RESULTS One hundred and fifteen patients (60 % males) with a mean age of 57.7 ± 16.3 years were included. Thirty-seven patients (32.2 %) required escalation with HFNC, eight patients (7 %) were admitted to the ICU, and nine patients (7.8%) died. Based on univariate analysis, CRP [odds ratio (OR): 1.25, 95 % confidence interval (CI): 1.1-1.42), LNR (OR: 0.015, 95 % CI: 0.00-0.35), dv-NLR (OR: 5*106, 95 % CI: 26.7-9*109), CLR (OR: 7*1058, 95 % CI: 3*1025-2*1092), length of hospitalization (LOH; OR: 1.44, 95 % CI: 1.22-1.63), dyspnea at presentation (OR: 2.83, 95 % CI: 1.23-6.52), and ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2) on admission (OR: 0.967, 95 % CI: 0.952-0.983) were independent predictors for oxygen requirements. However, the multivariate analysis showed that LNR (OR: 1.686e0-4, 95 % CI: 6.441e00-8-0.441), PaO2/FiO2 on admission (OR: 0.965, 95 % CI: 0.941-0.989), and LOH (OR: 1.717, 95 % CI: 1.274-2.314) were the most important predictor for HFNC use. Nasal congestion at presentation (OR: 11.5, 95 % CI: 1.61-82.8) was a unique and independent predictor for ICU admission. As far as death is concerned, the univariate analysis identified elevated CRP (OR: 1.11, 95 % CI: 1.0-1.24), low RT-PCR (OR: 0.829, 95 % CI: 0.688-0.999), high CLR (OR: 3.2*1033, 95 % CI: 5.8-1.8*1066), age (OR: 1.08, 95 % CI: 1.02-1.14), body mass index (BMI) over 30 (OR: 5.25, 95 % CI: 1.26-21.96), the chronic use of angiotensin-converting enzyme inhibitors (OR: 5.72, 95 % CI: 1.35-24.09), nitrates (OR: 14.85, 95 % CI: 1.81-121.8), diuretics (OR: 8.21, 95 % CI: 1.97-34.32), PaO2/FiO2 on admission (OR: 0.983, 95 % CI: 0.970-0.998), and nasal congestion at presentation (OR: 9.81, 95 % CI: 1.40-68.68) as independent predictors. However, the multivariate analysis pinpointed that obesity (BMI >30) (OR: 10.498, 95 % CI: 1.107-99.572) remained the most important predictor for death. CONCLUSION LNR and PaO2/FiO2 on admission could be used to timely identify patients requiring HFNC during hospitalization, while obesity (BMI >30) could be an independent predictor of death. Nasal congestion emerges as a unique predictor for ICU admission. HIPPOKRATIA 2022, 26 (2):70-77.
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Affiliation(s)
- M P Ntalouka
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - I Pantazopoulos
- Department of Emergency Medicine, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
- Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - A G Brotis
- Department of Neurosurgery, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - A Pagonis
- Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - I Vatsiou
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - A Chatzis
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - C N Rarras
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - P Kotsi
- Department of Transfusion Medicine, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - K I Gourgoulianis
- Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - E M Arnaoutoglou
- Department of Anesthesiology, Faculty of Medicine, School of Health Sciences, University Hospital of Larissa, University of Thessaly, Larissa, Greece
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Aggarwal AN, Prasad KT, Muthu V. Obstructive lung diseases burden and COVID-19 in developing countries: a perspective. Curr Opin Pulm Med 2022; 28:84-92. [PMID: 34652297 PMCID: PMC8815642 DOI: 10.1097/mcp.0000000000000836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW Asthma and chronic obstructive pulmonary disease (COPD) are widely prevalent disorders, and important contributors to morbidity and mortality, in both developing and developed countries. It is conjectured that these obstructive lung diseases may have had more deleterious effects in developing nations during the 2019 coronavirus disease (COVID-19) pandemic. We provide an evidence-based perspective on the relationship between asthma/COPD prevalence and COVID-19 burden, and the impact of comorbid asthma/COPD on selected COVID-19 outcomes and healthcare utilization, with special reference to developing countries. RECENT FINDINGS Developing countries with higher COPD (but not asthma) prevalence appear to have higher COVID-19 related mortality. Patients with asthma (but not COPD) in developing countries may be less likely to acquire COVID-19. Published literature suggests that the overall impact of comorbid asthma or COPD on adverse COVID-19 outcomes may be broadly similar between developed and developing nations. SUMMARY There is paucity of information on interaction between asthma/COPD and COVID-19 in developing countries. Limited data suggest minor differences between developed and developing nations. In view of inadequacies in healthcare preparedness and delivery in several developing countries, there is a need to generate quality evidence to assess impact of obstructive lung diseases and COVID-19 on each other.
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Affiliation(s)
- Ashutosh N Aggarwal
- Department of Pulmonary Medicine, Postgraduate Institute of Medical Education and Research, Chandigarh, India
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Combined Blood Indexes of Systemic Inflammation as a Mirror to Admission to Intensive Care Unit in COVID-19 Patients: A Multicentric Study. J Epidemiol Glob Health 2021; 12:64-73. [PMID: 34904189 PMCID: PMC8668150 DOI: 10.1007/s44197-021-00021-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 11/29/2021] [Indexed: 01/09/2023] Open
Abstract
Background The Coronavirus 2019 is a pandemic that has spread worldwide, threatening human health. The main cause of death in patients with COVID-19 is a systemic pro-inflammatory mechanism that quickly progresses to acute respiratory distress syndrome. Hematological ratios as affordable indicators of inflammatory response were studied in COVID-19 patients. The study aimed to study the importance of the blood cell indexes of the systemic inflammatory response, as the Aggregate Index of Systemic Inflammation (AISI), neutrophils lymphocyte to platelet ratio (NLPR), systemic immune-inflammation index (SII) and, systemic inflammation response index (SIRI) in predicting intensive care unit (ICU) admission of COVID-19 patients. Methods 495 COVID-19 patients managed in four tertiary centers; divided into non-ICU and ICU groups. Results Total leucocyte count (TLC), AISI, NLPR, SII, and SIRI were more elevated in the ICU group (P < 0.001 for all except AMC P = 0.006), while this group had less absolute lymphocyte count (ALC) (P = 0.047). We estimated the optimal cut-off values of the hematological ratio; AISI (729), NLPR (0.0195), SII (1346), and SIRI (2.5). SII had the highest specificity (95.6%), while NLPR had the highest sensitivity (61.3%). Age, AISI, CRP, D-dimer, and oxygen aid were the independent predictors for ICU admission in COVID-19 in multivariate logistic regression. Conclusion AISI is a predictor for severity and ICU admission in COVID-19 patients, SII is a predictor of survival, while NLPR and SIRI have an additive role that needs further evaluation. Supplementary Information The online version contains supplementary material available at 10.1007/s44197-021-00021-5.
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Kantroo V, Kanwar MS, Goyal P, Rosha D, Modi N, Bansal A, Ansari AP, Wangnoo SK, Sobti S, Kansal S, Chawla R, Jasuja S, Gupta I. Mortality and Clinical Outcomes among Patients with COVID-19 and Diabetes. Med Sci (Basel) 2021; 9:medsci9040065. [PMID: 34842758 PMCID: PMC8628982 DOI: 10.3390/medsci9040065] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/19/2021] [Accepted: 10/22/2021] [Indexed: 12/11/2022] Open
Abstract
Background Diabetes mellitus (DM) is a decisive risk factor for severe illness in coronavirus disease 2019 (COVID-19). India is home to a large number of people with DM, and many of them were infected with COVID-19. It is critical to understand the impact of DM on mortality and other clinical outcomes of COVID-19 infection from this region. Aims The primary objective of our study was to analyze the mortality rate in people with DM infected with COVID-19. The secondary objectives were to assess the effect of various comorbidities on mortality and study the impact of DM on other clinical outcomes. Methods This is a retrospective study of COVID-19 infected patients admitted to a tertiary care hospital in north India in the early phase of the pandemic. Results Of the 1211 cases admitted, 19 were excluded because of incomplete data, and 1192 cases were finally considered for analysis. DM constituted 26.8% of total patients. The overall mortality rate was 6.1%, and the rate was 10.7% in the presence of diabetes (p < 0.01, OR 2.55). In univariate analysis, increased age, chronic kidney disease (CKD), coronary artery disease (CAD), stroke, and cancer were associated with mortality. On multiple logistic regression, the independent predictors of mortality were CAD, CKD, and cancer. Breathlessness and low SpO2 at presentation, extensive involvement in CXR, and elevated ANC/ALC ratio were also significantly associated with mortality. Conclusions The presence of comorbidities such as DM, hypertension, CAD, CKD, and cancer strongly predict the risk of mortality in COVID-19 infection. Early triaging and aggressive therapy of patients with these comorbidities can optimize clinical outcomes.
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Affiliation(s)
- Viny Kantroo
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
- Correspondence:
| | - Manjit S. Kanwar
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Piyush Goyal
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Deepak Rosha
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Nikhil Modi
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Avdhesh Bansal
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Athar Parvez Ansari
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Subhash Kumar Wangnoo
- Department of Apollo Centre of Diabetes and Endocrinology, Indraprastha Apollo Hospitals, New Delhi 110076, India;
| | - Sanjay Sobti
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Sudha Kansal
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Rajesh Chawla
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
| | - Sanjiv Jasuja
- Department of Nephrology and Kidney Transplant, Indraprastha Apollo Hospitals, New Delhi 110076, India;
| | - Ishan Gupta
- Department of Respiratory, Critical Care and Sleep Medicine, Indraprastha Apollo Hospitals, New Delhi 110076, India; (M.S.K.); (P.G.); (D.R.); (N.M.); (A.B.); (A.P.A.); (S.S.); (S.K.); (R.C.); (I.G.)
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