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Trongtrakul K, Tajarernmuang P, Limsukon A, Theerakittikul T, Niyatiwatchanchai N, Surasit K, Glunriangsang P, Liwsrisakun C, Bumroongkit C, Pothirat C, Inchai J, Chaiwong W, Chanayat P, Deesomchok A. The National Early Warning Score 2 with Age and Body Mass Index (NEWS2 Plus) to Determine Patients with Severe COVID-19 Pneumonia. J Clin Med 2024; 13:298. [PMID: 38202305 PMCID: PMC10780151 DOI: 10.3390/jcm13010298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 12/08/2023] [Accepted: 12/28/2023] [Indexed: 01/12/2024] Open
Abstract
(1) Background: Early identification of severe coronavirus disease 2019 (COVID-19) pneumonia at the initial phase of hospitalization is very crucial. To address this, we validated and updated the National Early Warning Score 2 (NEWS2) for this purpose. (2) Methods: We conducted a study on adult patients with COVID-19 infection in Chiang Mai, Thailand, between May 2021 and October 2021. (3) Results: From a total of 725 COVID-19 adult patients, 350 (48.3%) patients suffered severe COVID-19 pneumonia. In determining severe COVID-19 pneumonia, NEWS2 and NEWS2 + Age + BMI (NEWS2 Plus) showed the C-statistic values of 0.798 (95% CI, 0.767-0.830) and 0.821 (95% CI, 0.791-0.850), respectively. The C-statistic values of NEWS2 Plus were significantly improved compared to those of NEWS2 alone (p = 0.012). Utilizing a cut-off point of five, NEWS2 Plus exhibited better sensitivity and negative predictive value than the traditional NEWS2, with values of 99.7% vs. 83.7% and 98.9% vs. 80.7%, respectively. (4) Conclusions: The incorporation of age and BMI into the traditional NEWS2 score enhanced the efficacy of determining severe COVID-19 pneumonia. Physicians can rely on NEWS2 Plus (NEWS2 + Age + BMI) as a more effective decision-making tool for triaging COVID-19 patients during early hospitalization.
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Affiliation(s)
- Konlawij Trongtrakul
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Pattraporn Tajarernmuang
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Atikun Limsukon
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Theerakorn Theerakittikul
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Nutchanok Niyatiwatchanchai
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | | | | | - Chalerm Liwsrisakun
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Chaiwat Bumroongkit
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Chaicharn Pothirat
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Juthamas Inchai
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Warawut Chaiwong
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Panida Chanayat
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
| | - Athavudh Deesomchok
- Division of Pulmonary, Critical Care, and Allergy, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (P.T.); (A.L.); (T.T.); (N.N.); (C.L.); (C.B.); (C.P.); (J.I.); (W.C.); (P.C.)
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Ko RE, Kim Z, Jeon B, Ji M, Chung CR, Suh GY, Chung MJ, Cho BH. Deep Learning-Based Early Warning Score for Predicting Clinical Deterioration in General Ward Cancer Patients. Cancers (Basel) 2023; 15:5145. [PMID: 37958319 PMCID: PMC10647448 DOI: 10.3390/cancers15215145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 10/24/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Cancer patients who are admitted to hospitals are at high risk of short-term deterioration due to treatment-related or cancer-specific complications. A rapid response system (RRS) is initiated when patients who are deteriorating or at risk of deteriorating are identified. This study was conducted to develop a deep learning-based early warning score (EWS) for cancer patients (Can-EWS) using delta values in vital signs. METHODS A retrospective cohort study was conducted on all oncology patients who were admitted to the general ward between 2016 and 2020. The data were divided into a training set (January 2016-December 2019) and a held-out test set (January 2020-December 2020). The primary outcome was clinical deterioration, defined as the composite of in-hospital cardiac arrest (IHCA) and unexpected intensive care unit (ICU) transfer. RESULTS During the study period, 19,739 cancer patients were admitted to the general wards and eligible for this study. Clinical deterioration occurred in 894 cases. IHCA and unexpected ICU transfer prevalence was 1.77 per 1000 admissions and 43.45 per 1000 admissions, respectively. We developed two models: Can-EWS V1, which used input vectors of the original five input variables, and Can-EWS V2, which used input vectors of 10 variables (including an additional five delta variables). The cross-validation performance of the clinical deterioration for Can-EWS V2 (AUROC, 0.946; 95% confidence interval [CI], 0.943-0.948) was higher than that for MEWS of 5 (AUROC, 0.589; 95% CI, 0.587-0.560; p < 0.001) and Can-EWS V1 (AUROC, 0.927; 95% CI, 0.924-0.931). As a virtual prognostic study, additional validation was performed on held-out test data. The AUROC and 95% CI were 0.588 (95% CI, 0.588-0.589), 0.890 (95% CI, 0.888-0.891), and 0.898 (95% CI, 0.897-0.899), for MEWS of 5, Can-EWS V1, and the deployed model Can-EWS V2, respectively. Can-EWS V2 outperformed other approaches for specificities, positive predictive values, negative predictive values, and the number of false alarms per day at the same sensitivity level on the held-out test data. CONCLUSIONS We have developed and validated a deep learning-based EWS for cancer patients using the original values and differences between consecutive measurements of basic vital signs. The Can-EWS has acceptable discriminatory power and sensitivity, with extremely decreased false alarms compared with MEWS.
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Affiliation(s)
- Ryoung-Eun Ko
- Department of Critical Care Medicine, Samsung Medical Center, School of Medicine, Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea; (R.-E.K.); (C.R.C.); (G.Y.S.)
| | - Zero Kim
- Medical AI Research Center, Samsung Medical Center, Seoul 06351, Republic of Korea; (Z.K.); (B.J.); (M.J.); (M.J.C.)
- Department of Data Convergence and Future Medicine, School of Medicine, Sungkyunkwan University, Seoul 06351, Republic of Korea
| | - Bomi Jeon
- Medical AI Research Center, Samsung Medical Center, Seoul 06351, Republic of Korea; (Z.K.); (B.J.); (M.J.); (M.J.C.)
| | - Migyeong Ji
- Medical AI Research Center, Samsung Medical Center, Seoul 06351, Republic of Korea; (Z.K.); (B.J.); (M.J.); (M.J.C.)
| | - Chi Ryang Chung
- Department of Critical Care Medicine, Samsung Medical Center, School of Medicine, Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea; (R.-E.K.); (C.R.C.); (G.Y.S.)
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University, Seoul 06351, Republic of Korea
| | - Gee Young Suh
- Department of Critical Care Medicine, Samsung Medical Center, School of Medicine, Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea; (R.-E.K.); (C.R.C.); (G.Y.S.)
- Devision of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University, Seoul 06351, Republic of Korea
| | - Myung Jin Chung
- Medical AI Research Center, Samsung Medical Center, Seoul 06351, Republic of Korea; (Z.K.); (B.J.); (M.J.); (M.J.C.)
- Department of Data Convergence and Future Medicine, School of Medicine, Sungkyunkwan University, Seoul 06351, Republic of Korea
| | - Baek Hwan Cho
- Department of Biomedical Informatics, School of Medicine, CHA University, Seongnam 13497, Republic of Korea
- Institute of Biomedical Informatics, School of Medicine, CHA University, Seongnam 13497, Republic of Korea
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Obradović D, Popović M, Banjac M, Bulajić J, Đurović V, Urošević I, Milovančev A. Outcomes in COVID-19 Patients with Pneumonia Treated with High-Flow Oxygen Therapy and Baricitinib—Retrospective Single-Center Study. Life (Basel) 2023; 13:life13030755. [PMID: 36983910 PMCID: PMC10053916 DOI: 10.3390/life13030755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/07/2023] [Accepted: 03/08/2023] [Indexed: 03/14/2023] Open
Abstract
Background. The aim of the study was to assess the effect of baricitinib on 28-day all-cause mortality and the progression of respiratory failure in patients needing transfer to the intensive care unit (ICU) with COVID-19 pneumonia treated with high-flow oxygen therapy. Methods. This retrospective study included hospitalized patients with COVID-19 pneumonia treated with high-flow oxygen non-invasive ventilation receiving standard of care (SOC) or SOC in addition to baricitinib. Data on patients’ characteristics, pro-inflammatory markers, D dimer, and National Early Warning Score 2 (NEWS2) values were collected and compared between groups. The primary endpoint was 28-day all-cause in-hospital mortality and the secondary outcome was transfer to the ICU. Results. The study included 125 patients. The primary outcome was observed in 44.8% of them: 27% in the baricitinib group vs. 62% in the SOC group, p < 0.001. Transfer to the ICU ward was significantly lower in the baricitinib group: 29% vs. 81%, p < 0.001. A significant improvement was observed when the baricitinib group was compared to SOC in procalcitonin, CRP, D-dimer, neutrophil-to-lymphocyte ratio values, and NEWS2. Conclusion. Treatment with baricitinib in addition to SOC was associated with reduced mortality and a lower prevalence of transfer to the ICU in hospitalized patients with COVID-19 pneumonia treated with high-flow oxygen non-invasive therapy.
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Affiliation(s)
- Dušanka Obradović
- Faculty of Medicine Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia
- Institute for Pulmonary Diseases of Vojvodina, 21204 Sremska Kamenica, Serbia
| | - Milica Popović
- Faculty of Medicine Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia
- Clinic of Nephrology and Clinical Immunology, University Clinical Centre of Vojvodina, 21000 Novi Sad, Serbia
| | - Maja Banjac
- Institute for Pulmonary Diseases of Vojvodina, 21204 Sremska Kamenica, Serbia
| | - Jelena Bulajić
- Urgent Care Center, University Clinical Centre of Vojvodina, 21000 Novi Sad, Serbia
| | - Vladimir Đurović
- Clinic of Nephrology and Clinical Immunology, University Clinical Centre of Vojvodina, 21000 Novi Sad, Serbia
| | - Ivana Urošević
- Faculty of Medicine Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia
- Clinic of Hematology, University Clinical Centre of Vojvodina, 21000 Novi Sad, Serbia
| | - Aleksandra Milovančev
- Faculty of Medicine Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia
- Institute for Cardiovascular Diseases of Vojvodina, 21204 Sremska Kamenica, Serbia
- Correspondence:
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Rønningen PS, Walle-Hansen MM, Ihle-Hansen H, Andersen EL, Tveit A, Myrstad M. Impact of frailty on the performance of the National Early Warning Score 2 to predict poor outcome in patients hospitalised due to COVID-19. BMC Geriatr 2023; 23:134. [PMID: 36890484 PMCID: PMC9994778 DOI: 10.1186/s12877-023-03842-0] [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: 08/11/2022] [Accepted: 02/22/2023] [Indexed: 03/10/2023] Open
Abstract
BACKGROUND The National Early Warning Score 2 (NEWS2) is a scoring tool predictive of poor outcome in hospitalised patients. Older patients with COVID-19 have increased risk of poor outcome, but it is not known if frailty may impact the predictive performance of NEWS2. We aimed to investigate the impact of frailty on the performance of NEWS2 to predict in-hospital mortality in patients hospitalised due to COVID-19. METHODS We included all patients admitted to a non-university Norwegian hospital due to COVID-19 from 9 March 2020 until 31 December 2021. NEWS2 was scored based on the first vital signs recorded upon hospital admission. Frailty was defined as a Clinical Frailty Scale score ≥ 4. The performance of a NEWS2 score ≥ 5 to predict in-hospital mortality was assessed with sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) according to frailty status. RESULTS Out of 412 patients, 70 were aged ≥ 65 years and with frailty. They presented less frequently with respiratory symptoms, and more often with acute functional decline or new-onset confusion. In-hospital mortality was 6% in patients without frailty, and 26% in patients with frailty. NEWS2 predicted in-hospital mortality with a sensitivity of 86%, 95% confidence interval (CI) 64%-97% and AUROC 0.73, 95% CI 0.65-0.81 in patients without frailty. In older patients with frailty, sensitivity was 61%, 95% CI 36%-83% and AUROC 0.61, 95% CI 0.48-0.75. CONCLUSION A single NEWS2 score at hospital admission performed poorly to predict in-hospital mortality in patients with frailty and COVID-19 and should be used with caution in this patient group. Graphical abstract summing up study design, results and conclusion.
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Affiliation(s)
- Peter Selmer Rønningen
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Post Box 800, 3004, Drammen, Norway.
| | - Marte Meyer Walle-Hansen
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Post Box 800, 3004, Drammen, Norway
| | - Håkon Ihle-Hansen
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Post Box 800, 3004, Drammen, Norway.,Department of Internal Medicine, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway
| | - Elizabeth Lyster Andersen
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Post Box 800, 3004, Drammen, Norway
| | - Arnljot Tveit
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Post Box 800, 3004, Drammen, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Marius Myrstad
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Post Box 800, 3004, Drammen, Norway.,Department of Internal Medicine, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway
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Moderate COVID-19: Clinical Trajectories and Predictors of Progression and Outcomes. J Pers Med 2022; 12:jpm12091472. [PMID: 36143257 PMCID: PMC9505620 DOI: 10.3390/jpm12091472] [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: 08/12/2022] [Revised: 09/01/2022] [Accepted: 09/02/2022] [Indexed: 11/17/2022] Open
Abstract
Background: Patients with COVID-19 commonly present at healthcare facilities with moderate disease, i.e., pneumonia without a need for oxygen therapy. Aim: To identify clinical/laboratory characteristics of patients with moderate COVID-19, which could predict disease progression. Methods: 384 adult patients presented with moderate COVID-19 and admitted to two hospitals were retrospectively evaluated. In a multivariate analysis gender, age, BMI, Charlson Comorbidity Index (CCI) and National Early Weaning Score 2 were treated as co-variates. The development of hypoxemic respiratory failure, intubation rate and risk of death were considered as dependent variables. Estimated values are presented as odds-ratio (OR) with 95% confidence interval (CI). Results: Most of the patients were male (63.28%) with a mean (standard deviation) age of 59 (16.04) years. Median (interquartile range) CCI was 2 (1–4). A total of 58.85% of the patients developed respiratory failure; 6.51% were intubated, and 8.85% died. The extent of pneumonia in chest X-ray (involvement of all four quartiles) [OR 3.96 (1.18–13.27), p = 0.026], respiratory rate [OR 1.17 (1.05–1.3), p = 0.004], SatO2 [OR 0.72 (0.58–0.88), p = 0.002], systolic blood pressure [OR 1.02 (1–1.04), p = 0.041] and lymphocyte count [OR 0.9993 (0.9986–0.9999), p = 0.026] at presentation were associated with the development of respiratory failure. The extent of pneumonia [OR 26.49 (1.81–387.18), p = 0.017] was associated with intubation risk. Age [OR 1.14 (1.03–1.26), p = 0.014] and the extent of pneumonia [OR 22.47 (1.59–316.97), p = 0.021] were associated with increased risk of death. Conclusion: Older age, the extent of pneumonia, tachypnea, lower SatO2, higher systolic blood pressure and lymphopenia are associated with dismal outcomes in patients presenting with moderate COVID-19.
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Sozio E, Moore NA, Fabris M, Ripoli A, Rumbolo F, Minieri M, Boverio R, Rodríguez Mulero MD, Lainez-Martinez S, Martínez Martínez M, Calvo D, Gregoriano C, Williams R, Brazzi L, Terrinoni A, Callegari T, Hernández Olivo M, Esteban-Torrella P, Calcerrada I, Bernasconi L, Kidd SP, Sbrana F, Miguens I, Gordon K, Visentini D, Legramante JM, Bassi F, Cortes N, Montrucchio G, Di Lecce VN, Lauritano EC, García de Guadiana-Romualdo L, González del Castillo J, Bernal-Morell E, Andaluz-Ojeda D, Schuetz P, Curcio F, Tascini C, Saeed K. Identification of COVID-19 patients at risk of hospital admission and mortality: a European multicentre retrospective analysis of mid-regional pro-adrenomedullin. Respir Res 2022; 23:221. [PMID: 36031619 PMCID: PMC9420187 DOI: 10.1186/s12931-022-02151-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Background Mid-Regional pro-Adrenomedullin (MR-proADM) is an inflammatory biomarker that improves the prognostic assessment of patients with sepsis, septic shock and organ failure. Previous studies of MR-proADM have primarily focussed on bacterial infections. A limited number of small and monocentric studies have examined MR-proADM as a prognostic factor in patients infected with SARS-CoV-2, however there is need for multicenter validation. An evaluation of its utility in predicting need for hospitalisation in viral infections was also performed. Methods An observational retrospective analysis of 1861 patients, with SARS-CoV-2 confirmed by RT-qPCR, from 10 hospitals across Europe was performed. Biomarkers, taken upon presentation to Emergency Departments (ED), clinical scores, patient demographics and outcomes were collected. Multiclass random forest classifier models were generated as well as calculation of area under the curve analysis. The primary endpoint was hospital admission with and without death. Results Patients suitable for safe discharge from Emergency Departments could be identified through an MR-proADM value of ≤ 1.02 nmol/L in combination with a CRP (C-Reactive Protein) of ≤ 20.2 mg/L and age ≤ 64, or in combination with a SOFA (Sequential Organ Failure Assessment) score < 2 if MR-proADM was ≤ 0.83 nmol/L regardless of age. Those at an increased risk of mortality could be identified upon presentation to secondary care with an MR-proADM value of > 0.85 nmol/L, in combination with a SOFA score ≥ 2 and LDH > 720 U/L, or in combination with a CRP > 29.26 mg/L and age ≤ 64, when MR-proADM was > 1.02 nmol/L. Conclusions This international study suggests that for patients presenting to the ED with confirmed SARS-CoV-2 infection, MR-proADM in combination with age and CRP or with the patient’s SOFA score could identify patients at low risk where outpatient treatment may be safe.
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Asmarawati TP, Suryantoro SD, Rosyid AN, Marfiani E, Windradi C, Mahdi BA, Sutanto H. Predictive Value of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Acute Physiology and Chronic Health Evaluation (APACHE II), and New Early Warning Signs (NEWS-2) Scores Estimate Mortality of COVID-19 Patients Requiring Intensive Care Unit (ICU). Indian J Crit Care Med 2022; 26:464-471. [PMID: 35656039 PMCID: PMC9067497 DOI: 10.5005/jp-journals-10071-24170] [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] [Indexed: 01/08/2023] Open
Abstract
Introduction Various mortality predictive score models for coronavirus disease-2019 (COVID-19) have been deliberated. We studied how sequential organ failure assessment (SOFA), quick sequential organ failure assessment (qSOFA), acute physiology and chronic health evaluation II (APACHE II), and new early warning signs (NEWS-2) scores estimate mortality in COVID-19 patients. Materials and methods We conducted a prospective cohort study of 53 patients with moderate-to-severe COVID-19. We calculated qSOFA, SOFA, APACHE II, and NEWS-2 on initial admission and re-evaluated on day 5. We performed logistic regression analysis to differentiate the predictors of qSOFA, SOFA, APACHE II, and NEWS-2 scores on mortality. Result qSOFA, SOFA, APACHE II, and NEWS-2 scores on day 5 exhibited a difference between survivors and nonsurvivors (p <0.05), also between ICU and non-ICU admission (p <0.05). The initial NEWS-2 revealed a higher AUC value than the qSOFA, APACHE II, and SOFA score in estimating mortality (0.867; 0.83; 0.822; 0.794). In ICU, APACHE II score revealed a higher AUC value than the SOFA, NEWS-2, and qSOFA score (0.853; 0.832; 0.813; 0.809). Concurrently, evaluation on day 5 showed that qSOFA AUC had higher scores than the NEWS-2, APACHE II, and SOFA (0.979; 0.965; 0.939; 0.933) in predicting mortality, while SOFA and APACHE II AUC were higher in ICU admission than NEWS-2 and qSOFA (0.968; 0.964; 0.939; 0.934). According to the cutoff score, APACHE II on day 5 revealed the highest sensitivity and specificity in predicting the mortality (sensitivity 95.7%, specificity 86.7%). Conclusion All scores signify good predictive values on COVID-19 patients mortality following the evaluation on the day 5. Nonetheless, APACHE-II appears to be the best at predicting mortality and ICU admission rate. How to cite this article Asmarawati TP, Suryantoro SD, Rosyid AN, Marfiani E, Windradi C, Mahdi BA, et al. Predictive Value of Sequential Organ Failure Assessment, Quick Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation II, and New Early Warning Signs Scores Estimate Mortality of COVID-19 Patients Requiring Intensive Care Unit. Indian J Crit Care Med 2022;26(4):464–471.
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Affiliation(s)
- Tri Pudy Asmarawati
- Department of Internal Medicine, Universitas Airlangga, Faculty of Medicine, Surabaya, East Java, Indonesia
- Tri Pudy Asmarawati, Department of Internal Medicine, Universitas Airlangga, Faculty of Medicine, Surabaya, East Java, Indonesia, e-mail:
| | - Satriyo Dwi Suryantoro
- Department of Internal Medicine, Universitas Airlangga, Faculty of Medicine, Surabaya, East Java, Indonesia
| | - Alfian Nur Rosyid
- Department of Pulmonary and Respiratory Medicine, Universitas Airlangga, Surabaya, East Java, Indonesia
| | - Erika Marfiani
- Department of Internal Medicine, Universitas Airlangga, Faculty of Medicine, Surabaya, East Java, Indonesia
| | - Choirina Windradi
- Department of Internal Medicine, Universitas Airlangga, Faculty of Medicine, Surabaya, East Java, Indonesia
| | - Bagus Aulia Mahdi
- Department of Internal Medicine, Universitas Airlangga, Faculty of Medicine, Surabaya, East Java, Indonesia
| | - Heri Sutanto
- Department of Internal Medicine, Brawijaya University, Malang, Jawa Timur, Indonesia
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Cárdenas G, Chávez-Canales M, Espinosa AM, Jordán-Ríos A, Malagon DA, Murillo MFM, Araujo LVT, Campos RLB, Wong-Chew RM, González LER, Cresencio KI, Velázquez EG, de la Cerda MR, Leyva Y, Hernández-Ruiz J, Hernández-Medel ML, León-Hernández M, Quero KM, Monciváis AS, Díaz SH, Martínez IRZ, Martínez-Cuazitl A, Salazar INM, Sarmiento EB, Peña AF, Hernández PS, Reynoso RIA, Reyes DM, del Río Ambriz LR, Bonilla RAA, Cruz J, Huerta L, Fierro NA, Hernández M, Pérez-Tapia M, Meneses G, Espíndola-Arriaga E, Rosas G, Chinney A, Mendoza SR, Hernández-Aceves JA, Cervantes-Torres J, Rodríguez AF, Alor RO, Francisco SO, Salazar EA, Besedovsky H, Romano MC, Bobes RJ, Jung H, Soldevila G, López-Alvarenga J, Fragoso G, Laclette JP, Sciutto E. Intranasal dexamethasone: a new clinical trial for the control of inflammation and neuroinflammation in COVID-19 patients. Trials 2022; 23:148. [PMID: 35164840 PMCID: PMC8845269 DOI: 10.1186/s13063-022-06075-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 02/01/2022] [Indexed: 12/15/2022] Open
Abstract
Background By end December of 2021, COVID-19 has infected around 276 million individuals and caused over 5 million deaths worldwide. Infection results in dysregulated systemic inflammation, multi-organ dysfunction, and critical illness. Cells of the central nervous system are also affected, triggering an uncontrolled neuroinflammatory response. Low doses of glucocorticoids, administered orally or intravenously, reduce mortality among moderate and severe COVID-19 patients. However, low doses administered by these routes do not reach therapeutic levels in the CNS. In contrast, intranasally administered dexamethasone can result in therapeutic doses in the CNS even at low doses. Methods This is an approved open-label, multicenter, randomized controlled trial to compare the effectiveness of intranasal versus intravenous dexamethasone administered in low doses to moderate and severe COVID-19 adult patients. The protocol is conducted in five health institutions in Mexico City. A total of 120 patients will be randomized into two groups (intravenous vs. intranasal) at a 1:1 ratio. Both groups will be treated with the corresponding dexamethasone scheme for 10 days. The primary outcome of the study will be clinical improvement, defined as a statistically significant reduction in the NEWS-2 score of patients with intranasal versus intravenous dexamethasone administration. The secondary outcome will be the reduction in mortality during hospitalization. Conclusions This protocol is currently in progress to improve the efficacy of the standard therapeutic dexamethasone regimen for moderate and severe COVID-19 patients. Trial registration ClinicalTrials.govNCT04513184. Registered November 12, 2020. Approved by La Comisión Federal para la Protección contra Riesgos Sanitarios (COFEPRIS) with identification number DI/20/407/04/36. People are currently being recruited. Graphical abstract ![]()
REVIVAL is a multicenter, open-label, randomized, controlled study to compare the standard low doses of intravenous dexamethasone with weight-adjusted low doses of intranasal dexamethasone. Intranasal dexamethasone can reach the respiratory tract more effectively than intravenous administration. Intranasal dexamethasone can reach the central nervous system in therapeutic concentrations, even at low doses. REVIVAL aims to reduce central failures and sequelae by controlling not only systemic inflammation but also neuroinflammation.
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Chikhalkar B, Gosain D, Gaikwad S, Deshmukh R. Assessment of National Early Warning Score 2 as a Tool to Predict the Outcome of COVID-19 Patients on Admission. Cureus 2022; 14:e21164. [PMID: 35165614 PMCID: PMC8831360 DOI: 10.7759/cureus.21164] [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] [Accepted: 01/10/2022] [Indexed: 11/22/2022] Open
Abstract
Introduction: The ongoing pandemic due to coronavirus disease 2019 (COVID-19) has put tremendous strain on the healthcare system around the world. There is a paucity of data describing the role of National Early Warning Score 2 (NEWS2) in the assessment of COVID-19 cases. This study aimed at identifying NEWS2 calculated on admission as a valuable tool for risk stratification and prediction of in-hospital mortality in COVID-19 patients. Materials and method: This prospective, observational study included 814 confirmed COVID-19 cases and was conducted over a period of three months. Vital parameters were assessed and NEWS2 was calculated on admission. Data were entered in excel format and statistical analysis was done in Python 3.8 statistical software (Wilmington, DE: Python Software Foundation). Pearson's chi-squared test was used following which a significant NEWS2 cut-off score to predict in-hospital mortality was determined by means of receiver operating characteristic (ROC) curve. Results: Mortality of 9.09% was noted and correlations were made with age, comorbidity, and NEWS2 score. For in-hospital deaths, comorbidities were present in 66.21% of patients, the mean age was 60.14 years, and average NEWS2 score was 9. For discharged patients only 21.89% had comorbidities, mean age was 42.96 years, and average NEWS2 score was 1.17. NEWS2 score of ≥ 6 had a sensitivity of 93.24% and specificity of 98.91%, and hence was a statistically significant cut-off value for predicting mortality on admission. Conclusion:Age, presence of comorbidities, and NEWS2 have a positive correlation with mortality in COVID-19 patients. NEWS2 score being easy, reliable, and quick to calculate, should be used to triage these patients on admission. Scores ≥ 6 should be considered to have a higher risk of adverse outcomes and hence should be managed prudently along with clinical judgment.
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SARS-CoV-2 and seasonal influenza: similarities and disparities. Arch Virol 2022; 167:2761-2765. [PMID: 36269417 PMCID: PMC9589861 DOI: 10.1007/s00705-022-05615-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/18/2022] [Indexed: 12/14/2022]
Abstract
This report describes the differences in disease severity and clinical presentation between hospitalized patients with coronavirus disease 2019 (COVID-19) and others with seasonal influenza. A total of 136 influenza and 152 COVID-19 patients were included. Patients with influenza more frequently had dyspnea (p = 0.004), hypoxemia (p < 0.001), underlying diseases (p = 0.046), and elevated liver enzymes (p = 0.028). In contrast, patients with COVID-19 were overweight (p < 0.001), lymphopenic (p < 0.001), had elevated CRP (p = 0.011), and radiological abnormalities (p < 0.001). Patients with influenza were more severely ill on admission (NEWS > 5) (p < 0.001). However, length of hospital stay, ventilatory support, and 30-day-mortality were similar. Despite differences in clinical presentation and disease severity between influenza and COVID-19 patients, both groups had similar clinical outcomes.
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