1
|
Molitch-Hou E, Zhang H, Gala P, Tate A. Impact of the COVID-19 Public Health Crisis and a Structured COVID Unit on Physician Behaviors in Code Status Ordering. Am J Hosp Palliat Care 2024; 41:1076-1084. [PMID: 37786255 PMCID: PMC10985045 DOI: 10.1177/10499091231204943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023] Open
Abstract
Purpose: Code status orders are standard practice impacting end-of-life care for individuals. This study reviews the impact of a COVID unit on physician behaviors towards goal-concordant end-of-life care at an urban academic tertiary-care hospital. Methods: We conducted a retrospective cohort study of code status ordering on adult inpatients comparing the pre-pandemic period to patients who tested positive, negative and were not tested during the pandemic from January 1, 2019, to December 31, 2020. Results: We analyzed 59,471 unique patient encounters (n = 35,317 pre-pandemic and n = 24,154 during). 1,631 cases of COVID-19 were seen. The rate of code status orders among all inpatients increased from 22% pre-pandemic to 29% during the pandemic (P < .001). Code status orders increased for both patients who were COVID-negative (32% P < .001) and COVID-positive (65% P < .001). Being in a cohorted COVID unit increased code status ordering by an odds of 4.79 (P < .001). Compared to the pre-pandemic cohort, the COVID-positive cohort is less female (50% to 56% P < .001), more Black (66% to 61% P < .001), more Hispanic (6.5% to 5%) and less white (26% to 30% P < .001). Compared to Black patients, white patients had lower odds (.86) of code status ordering (P < .001). Other race/ethnicity categories were not significant. Conclusions: Code status ordering remains low. Compared to pre-pandemic rates, the frequency of orders placed significantly increased for all patients during the pandemic. The largest increase occurred in patients with COVID-19. This increase likely occurred due to protocols in the COVID unit and disease uncertainty.
Collapse
Affiliation(s)
- Ethan Molitch-Hou
- Department of Medicine, Section of Hospital Medicine, University of Chicago, Chicago, IL, USA
| | - Hui Zhang
- Center for Health and The Social Sciences, The University of Chicago, Chicago, IL, USA
| | - Pooja Gala
- NYU Grossman School of Medicine, New York University, New York, NY, USA
| | - Alexandra Tate
- Department of Medicine, Section of Hospital Medicine, University of Chicago, Chicago, IL, USA
| |
Collapse
|
2
|
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.
Collapse
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.)
| |
Collapse
|
3
|
Bian Y, Han Q, Zheng Y, Yao Y, Fan X, Lv R, Pang J, Xu F, Chen Y. SUPER Score Contributes to Warning and Management in Early-Stage COVID-19. INFECTIOUS MEDICINE 2023; 2:308-314. [PMID: 38205173 PMCID: PMC10774654 DOI: 10.1016/j.imj.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 08/11/2023] [Accepted: 09/03/2023] [Indexed: 01/12/2024]
Abstract
Background Some COVID-19 patients deteriorate to severe cases with relatively higher case-fatality rates, which increases the medical burden. This necessitates identification of patients at risk of severe disease. Early assessment plays a crucial role in identifying patients at risk of severe disease. This study is to assess the effectiveness of SUPER score as a predictor of severe COVID-19 cases. Methods We consecutively enrolled COVID-19 patients admitted to a comprehensive medical center in Wuhan, China, and recorded clinical characteristics and laboratory indexes. The SUPER score was calculated using parameters including oxygen saturation, urine volume, pulse, emotional state, and respiratory rate. In addition, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity of the SUPER score for the diagnosis of severe COVID-19 were calculated and compared with the National Early Warning Score 2 (NEWS2). Results The SUPER score at admission, with a threshold of 4, exhibited good predictive performance for early identification of severe COVID-19 cases, yielding an AUC of 0.985 (95% confidence interval [CI] 0.897-1.000), sensitivity of 1.00 (95% CI 0.715-1.000), and specificity of 0.92 (95% CI 0.775-0.982), similar to NEWS2 (AUC 0.984; 95% CI 0.895-1.000, sensitivity 0.91; 95% CI 0.587-0.998, specificity 0.97; 95% CI 0.858-0.999). Compared with patients with a SUPER score<4, patients in the high-risk group exhibited lower lymphocyte counts, interleukin-2, interleukin-4 and higher fibrinogen, C-reactive protein, aspartate aminotransferase, and lactate dehydrogenase levels. Conclusions In conclusion, the SUPER score demonstrated equivalent accuracy to the NEWS2 score in predicting severe COVID-19. Its application in prognostic assessment therefore offers an effective early warning system for critical management and facilitating efficient allocation of health resources.
Collapse
Affiliation(s)
- Yuan Bian
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Qi Han
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Yue Zheng
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Yu Yao
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Xinhui Fan
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Ruijuan Lv
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Jiaojiao Pang
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Feng Xu
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Yuguo Chen
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- Chest Pain Center, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital of Shandong University, Jinan 250012, China
- Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Shandong Provincial Engineering Laboratory for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
| |
Collapse
|
4
|
Ruangsomboon O, Phanprasert N, Jirathanavichai S, Puchongmart C, Boonmee P, Thirawattanasoot N, Dorongthom T, Praphruetkit N, Monsomboon A. The utility of the Rapid Emergency Medicine Score (REMS) compared with three other early warning scores in predicting in-hospital mortality among COVID-19 patients in the emergency department: a multicenter validation study. BMC Emerg Med 2023; 23:45. [PMID: 37101141 PMCID: PMC10132401 DOI: 10.1186/s12873-023-00814-w] [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: 10/30/2022] [Accepted: 04/12/2023] [Indexed: 04/28/2023] Open
Abstract
BACKGROUND Many early warning scores (EWSs) have been validated to prognosticate adverse outcomes of COVID-19 in the Emergency Department (ED), including the quick Sequential Organ Failure Assessment (qSOFA), the Modified Early Warning Score (MEWS), and the National Early Warning Score (NEWS). However, the Rapid Emergency Medicine Score (REMS) has not been widely validated for this purpose. We aimed to assess and compare the prognostic utility of REMS with that of qSOFA, MEWS, and NEWS for predicting mortality in emergency COVID-19 patients. METHODS We conducted a multi-center retrospective study at five EDs of various levels of care in Thailand. Adult patients visiting the ED who tested positive for COVID-19 prior to ED arrival or within the index hospital visit between January and December 2021 were included. Their EWSs at ED arrival were calculated and analysed. The primary outcome was all-cause in-hospital mortality. The secondary outcome was mechanical ventilation. RESULTS A total of 978 patients were included in the study; 254 (26%) died at hospital discharge, and 155 (15.8%) were intubated. REMS yielded the highest discrimination capacity for in-hospital mortality (the area under the receiver operator characteristics curves (AUROC) 0.771 (95% confidence interval (CI) 0.738, 0.804)), which was significantly higher than qSOFA (AUROC 0.620 (95%CI 0.589, 0.651); p < 0.001), MEWS (AUROC 0.657 (95%CI 0.619, 0.694); p < 0.001), and NEWS (AUROC 0.732 (95%CI 0.697, 0.767); p = 0.037). REMS was also the best EWS in terms of calibration, overall model performance, and balanced diagnostic accuracy indices at its optimal cutoff. REMS also performed better than other EWSs for mechanical ventilation. CONCLUSION REMS was the early warning score with the highest prognostic utility as it outperformed qSOFA, MEWS, and NEWS in predicting in-hospital mortality in COVID-19 patients in the ED.
Collapse
Affiliation(s)
- Onlak Ruangsomboon
- Department of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand
| | - Nutthida Phanprasert
- Department of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand
| | - Supawich Jirathanavichai
- Department of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand
| | | | - Phetsinee Boonmee
- Department of Emergency Medicine, Ratchaburi Hospital, Ratchaburi, Thailand
| | | | - Thawonrat Dorongthom
- Department of Emergency Medicine and Forensic Medicine, Prachuap Khiri Khan hospital, Prachuap Khiri Khan, Thailand
| | - Nattakarn Praphruetkit
- Department of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand
| | - Apichaya Monsomboon
- Department of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand.
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Wei S, Xiong D, Wang J, Liang X, Wang J, Chen Y. The accuracy of the National Early Warning Score 2 in predicting early death in prehospital and emergency department settings: a systematic review and meta-analysis. ANNALS OF TRANSLATIONAL MEDICINE 2023; 11:95. [PMID: 36819553 PMCID: PMC9929743 DOI: 10.21037/atm-22-6587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 01/11/2023] [Indexed: 01/31/2023]
Abstract
Background Many studies have explored the accuracy of the National Early Warning Score 2 (NEWS2) in predicting mortality in prehospital and emergency settings, but their findings are inconsistent. Whether NEWS2 is reliable for the pre-examination and triage of patients in prehospital settings and emergency departments remains debatable. Hence, this study aimed to evaluate the accuracy of NEWS2 in predicting mortality in prehospital settings and emergency departments. Methods We searched PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wan Fang Data, Vip Database and SinoMed from the inception of each database to January 2023. The inclusion criteria: (I) patients in the prehospital settings or emergency departments; (II) the NEWS2 for predicting 2-day mortality, 30-day mortality, and in-hospital mortality; (III) sufficient data, such as sensitivity, specificity, overall survival, and deaths, were provided for the study; (IV) the type of study was accuracy prediction study. Two authors independently extracted data, including authors, year of publication, country of origin, study design, sample size, threshold cutoff values of NEWS2, and mortality. The PROBAST was used to assess the risk of bias in the included studies. Results Thirty studies with 185,835 participants were included. Among the 30 included studies, 13 have a high risk of bias, and 17 have a low risk of bias. The pooled sensitivity, specificity and AUC of 2-day mortality (early mortality), 30-day mortality and in-hospital mortality were 0.81 vs. 0.76 vs. 0.72 (95% CI: 0.61, 0.80), 0.81 vs. 0.69 vs. 0.78 (95% CI: 0.49, 0.93) and 0.88 vs. 0.80 vs. 0.78 (95% CI: 0.74, 0.82), respectively. Conclusions NEWS2 has excellent sensitivity and specificity in predicting early mortality in patients in the prehospitals setting and emergency departments. Nonetheless, it has poor performance in predicting in-hospital mortality and 30-day mortality. Our findings underpin the use of NEWS2 as a pre-examination and triage tool to predict early death in the prehospital settings and emergency departments. To improve the predictive accuracy, it should be used to monitor patients continuously rather than at a single point-in-time.
Collapse
Affiliation(s)
- Shengfeng Wei
- Department of Emergency Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Dan Xiong
- Department of Emergency Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jia Wang
- Department of Emergency Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xinmeng Liang
- Department of Emergency Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jingxian Wang
- Department of Emergency Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yuee Chen
- Department of Emergency Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| |
Collapse
|
7
|
Multicenter validation of Early Warning Scores for detection of clinical deterioration in COVID-19 hospitalized patients. Med Intensiva 2023; 47:9-15. [PMID: 36272911 PMCID: PMC9579896 DOI: 10.1016/j.medine.2021.11.023] [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: 09/02/2021] [Accepted: 11/08/2021] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Investigate the predictive value of NEWS2, NEWS-C, and COVID-19 Severity Index for predicting intensive care unit (ICU) transfer in the next 24h. DESIGN Retrospective multicenter study. SETTING Two third-level hospitals in Argentina. PATIENTS All adult patients with confirmed COVID-19, admitted on general wards, excluding patients with non-intubated orders. INTERVENTIONS Patients were divided between those who were admitted to ICU and non-admitted. We calculated the three scores for each day of hospitalization. VARIABLES We evaluate the calibration and discrimination of the three scores for the outcome ICU admission within 24, 48h, and at hospital admission. RESULTS We evaluate 13,768 days of hospitalizations on general medical wards of 1318 patients. Among these, 126 (9.5%) were transferred to ICU. The AUROC of NEWS2 was 0.73 (95%CI 0.68-0.78) 24h before ICU admission, and 0.52 (95%CI 0.47-0.57) at hospital admission. The AUROC of NEWS-C was 0.73 (95%CI 0.68-0.78) and 0.52 (95%CI 0.47-0.57) respectively, and the AUROC of COVID-19 Severity Index was 0.80 (95%CI 0.77-0.84) and 0.61 (95%CI 0.58-0.66) respectively. COVID-19 Severity Index presented better calibration than NEWS2 and NEWS-C. CONCLUSION COVID-19 Severity index has better calibration and discrimination than NEWS2 and NEWS-C to predict ICU transfer during hospitalization.
Collapse
|
8
|
Huespe I, Bisso I, Roman E, Prado E, Gemelli N, Sinner J, Heras M, Risk M. Multicenter validation of Early Warning Scores for detection of clinical deterioration in COVID-19 hospitalized patients. Med Intensiva 2023; 47:9-15. [PMID: 34866728 PMCID: PMC8629741 DOI: 10.1016/j.medin.2021.11.002] [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: 09/02/2021] [Accepted: 11/08/2021] [Indexed: 01/04/2023]
Abstract
Objective Investigate the predictive value of NEWS2, NEWS-C, and COVID-19 Severity Index for predicting intensive care unit (ICU) transfer in the next 24 h. Design Retrospective multicenter study. Setting Two third-level hospitals in Argentina. Patients All adult patients with confirmed COVID-19, admitted on general wards, excluding patients with non-intubated orders. Interventions Patients were divided between those who were admitted to ICU and non-admitted. We calculated the three scores for each day of hospitalization. Variables We evaluate the calibration and discrimination of the three scores for the outcome ICU admission within 24, 48 h, and at hospital admission. Results We evaluate 13,768 days of hospitalizations on general medical wards of 1318 patients. Among these, 126 (9.5%) were transferred to ICU. The AUROC of NEWS2 was 0.73 (95%CI 0.68-0.78) 24 h before ICU admission, and 0.52 (95%CI 0.47-0.57) at hospital admission. The AUROC of NEWS-C was 0.73 (95%CI 0.68-0.78) and 0.52 (95%CI 0.47-0.57) respectively, and the AUROC of COVID-19 Severity Index was 0.80 (95%CI 0.77-0.84) and 0.61 (95%CI 0.58-0.66) respectively. COVID-19 Severity Index presented better calibration than NEWS2 and NEWS-C. Conclusion COVID-19 Severity index has better calibration and discrimination than NEWS2 and NEWS-C to predict ICU transfer during hospitalization.
Collapse
Affiliation(s)
- I.A. Huespe
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Argentina,Instituto de Medicina Traslacional e Ingeniería Biomédica, HIBA, IUHI, CONICET, Buenos Aires, Argentina,Internal Medicine Research Unit, Hospital Italiano de Buenos Aires, CABA, Argentina,Corresponding author
| | - I.C. Bisso
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Argentina
| | - E.S. Roman
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Argentina
| | - E. Prado
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Argentina,Instituto de ciencias aplicadas Sergio Provenzano (ICAP), Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - N. Gemelli
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Argentina
| | - J. Sinner
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Argentina
| | - M.L. Heras
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Argentina
| | - M.R. Risk
- Instituto de Medicina Traslacional e Ingeniería Biomédica, HIBA, IUHI, CONICET, Buenos Aires, Argentina
| |
Collapse
|
9
|
Evaluation of the effectiveness of quick COVID-19 Severity Index and COVID-GRAM Critical Illness Risk Score in determining mortality and severity in COVID-19. JOURNAL OF SURGERY AND MEDICINE 2022. [DOI: 10.28982/josam.1093344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background/Aim: With the COVID-19 pandemic, the increase in the number of patients admitted to the emergency department has led to an increase in the need for intensive care and mechanical ventilation. Methods that can predict the development of serious disease will allow for a more accurate use of resources. This study was conducted to test the ability of the Quick COVID-19 Severity Index and the COVID-GRAM Critical Illness Risk Score to predict serious disease development and mortality.
Methods: This is a prospective cohort study. Among the patients admitted to the emergency department, those hospitalized due to COVID-19 were included in the study. The Quick COVID-19 Severity Index and COVID-GRAM Critical Illness Risk Scores of the patients were calculated, and the ability of these scores to predict serious illness and mortality was investigated.
Results: A total of 556 patients were included in this study. Development of critical illness, described as the need for non-invasive / invasive ventilation or the need for intensive care unit admission, was found significant when the Quick COVID-19 Severity Index was above 5 and the COVID-GRAM Critical Illness Risk Score showed high risk (AUC: 0.927; P < 0.001, AUC: 0.986; P < 0.001, respectively). A Quick COVID-19 Severity Index over 6 and COVID-GRAM Critical Illness Risk Score indicating high risk were found to be associated with mortality (AUC: 0.918, P < 0.001, AUC: 0.982, P < 0.001, respectively).
Conclusion: Both the Quick COVID-19 Severity Index and the COVID-GRAM Critical Illness Risk Score can be used to assess severity in COVID-19 patients in the emergency room. However, the COVID-GRAM Critical Illness Risk Score was more successful in differentiating low- and high-risk patients.
Collapse
|
10
|
Martín-Rodríguez F, Sanz-García A, Ortega GJ, Delgado-Benito JF, García Villena E, Mazas Pérez-Oleaga C, López-Izquierdo R, Castro Villamor MA. One-on-one comparison between qCSI and NEWS scores for mortality risk assessment in patients with COVID-19. Ann Med 2022; 54:646-654. [PMID: 35193439 PMCID: PMC8881067 DOI: 10.1080/07853890.2022.2042590] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE To compare the predictive value of the quick COVID-19 Severity Index (qCSI) and the National Early Warning Score (NEWS) for 90-day mortality amongst COVID-19 patients. METHODS Multicenter retrospective cohort study conducted in adult patients transferred by ambulance to an emergency department (ED) with suspected COVID-19 infection subsequently confirmed by a SARS-CoV-2 test (polymerase chain reaction). We collected epidemiological data, clinical covariates (respiratory rate, oxygen saturation, systolic blood pressure, heart rate, temperature, level of consciousness and use of supplemental oxygen) and hospital variables. The primary outcome was cumulative all-cause mortality during a 90-day follow-up, with mortality assessment monitoring time points at 1, 2, 7, 14, 30 and 90 days from ED attendance. Comparison of performances for 90-day mortality between both scores was carried out by univariate analysis. RESULTS From March to November 2020, we included 2,961 SARS-CoV-2 positive patients (median age 79 years, IQR 66-88), with 49.2% females. The qCSI score provided an AUC ranging from 0.769 (1-day mortality) to 0.749 (90-day mortality), whereas AUCs for NEWS ranging from 0.825 for 1-day mortality to 0.777 for 90-day mortality. At all-time points studied, differences between both scores were statistically significant (p < .001). CONCLUSION Patients with SARS-CoV-2 can rapidly develop bilateral pneumonias with multiorgan disease; in these cases, in which an evacuation by the EMS is required, reliable scores for an early identification of patients with risk of clinical deterioration are critical. The NEWS score provides not only better prognostic results than those offered by qCSI at all the analyzed time points, but it is also better suited for COVID-19 patients.KEY MESSAGESThis work aims to determine whether NEWS is the best score for mortality risk assessment in patients with COVID-19.AUCs for NEWS ranged from 0.825 for 1-day mortality to 0.777 for 90-day mortality and were significantly higher than those for qCSI in these same outcomes.NEWS provides a better prognostic capacity than the qCSI score and allows for long-term (90 days) mortality risk assessment of COVID-19 patients.
Collapse
Affiliation(s)
- Francisco Martín-Rodríguez
- Unidad Móvil de Emergencias Valladolid I, Gerencia de Emergencias Sanitarias, Gerencia Regional de Salud de Castilla y León (SACYL), Valladolid, Spain.,Centro de Simulación Clínica Avanzada, Facultad de Medicina, Universidad de Valladolid, Valladolid, Spain
| | - Ancor Sanz-García
- Data Analysis Unit, Instituto de Investigación Sanitaria del Hospital de la Princesa (IIS-IP), Madrid, Spain
| | - Guillermo J Ortega
- Data Analysis Unit, Instituto de Investigación Sanitaria del Hospital de la Princesa (IIS-IP), Madrid, Spain.,Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Buenos Aires, Argentina
| | - Juan F Delgado-Benito
- Unidad Móvil de Emergencias de Salamanca, Gerencia de Emergencias Sanitarias, Gerencia Regional de Salud de Castilla y León (SACYL), Valladolid, Spain
| | - Eduardo García Villena
- Escuela Politécnica Superior, Universidad Europea del Atlántico, Santander, Spain.,Departamento de Medio Ambiente y Sostenibilidad, Universidad Internacional Iberoamericana, Arecibo, Puerto Rico (EE.UU)
| | | | - Raúl López-Izquierdo
- Servicio de Urgencias, Hospital Universitario Rio Hortega de Valladolid, Gerencia Regional de Salud de Castilla y León (SACYL), Valladolid, Spain
| | - Miguel A Castro Villamor
- Centro de Simulación Clínica Avanzada, Facultad de Medicina, Universidad de Valladolid, Valladolid, Spain
| |
Collapse
|
11
|
İlhan B, Bozdereli Berikol G, Doğan H. The predictive value of modified risk scores in patients with acute exacerbation of COPD: a retrospective cohort study. Intern Emerg Med 2022; 17:2119-2127. [PMID: 35854207 PMCID: PMC9296366 DOI: 10.1007/s11739-022-03048-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 06/30/2022] [Indexed: 11/26/2022]
Abstract
This study aims to evaluate the performance of CREWS (Chronic Respiratory Early Warning Score), S-NEWS (Salford-National Early Warning Score), qNEWS (Quick National Early Warning Score), NEWS (National Early Warning Score), and qSOFA (Quick Sequential Organ Failure Assessment) scores in predicting mortality, intensive care unit (ICU) admission and the need for mechanical ventilation (MV) of patients presented with acute exacerbations of chronic obstructive pulmonary disease (AECOPD). This retrospective cohort study was conducted in the emergency department of a tertiary hospital between January 1 and December 31, 2019. The patients with AECOPD and aged ≥ 18 were included. Patients who were transferred from another center and whose data could not be reached were excluded. Demographic information, comorbid diseases, variables of the scores, laboratory results, and outcomes were recorded. A total of 575 consecutive patients were included. The 30-day mortality, ICU admission, and MV need rate were 5.7% (n = 33), 9.6% (n = 55), and 13.7% (n = 79), respectively. Each score had moderate-to-excellent performance in predicting MV need and ICU admission, while their performance in predicting mortality was poor. CREWS is the most successful score in predicting 30-day mortality (AUC 0.695), ICU admission (AUC 0.841), and MV need (AUC 0.924). ICU admission, age, and creatinine levels were associated with mortality (p < 0.05). All scores have better performance in predicting ICU admission and MV need than mortality. ICU admission, age, and creatinine levels may be the predictors of mortality among AECOPD patients.
Collapse
Affiliation(s)
- Buğra İlhan
- Department of Emergency Medicine, University of Health Sciences, Bakırköy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey.
| | - Göksu Bozdereli Berikol
- Department of Emergency Medicine, University of Health Sciences, Bakırköy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
| | - Halil Doğan
- Department of Emergency Medicine, University of Health Sciences, Bakırköy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
| |
Collapse
|
12
|
Khari S, Salimi Akin Abadi A, Pazokian M, Yousefifard M. CURB-65, qSOFA, and SIRS Criteria in Predicting In-Hospital Mortality of Critically Ill COVID-19 Patients; a Prognostic Accuracy Study. ARCHIVES OF ACADEMIC EMERGENCY MEDICINE 2022; 10:e36. [PMID: 35765619 PMCID: PMC9187131 DOI: 10.22037/aaem.v10i1.1565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
INTRODUCTION Outcome prediction of intensive care unit (ICU)-admitted patients is one of the important issues for physicians. This study aimed to compare the accuracy of Quick Sequential Organ Failure Assessment (qSOFA), Confusion, Urea, Respiratory Rate, Blood Pressure and Age Above or Below 65 Years (CURB-65), and Systemic Inflammatory Response Syndrome (SIRS) scores in predicting the in-hospital mortality of COVID-19 patients. METHODS This prognostic accuracy study was performed on 225 ICU-admitted patients with a definitive diagnosis of COVID-19 from July to December 2021 in Tehran, Iran. The patients' clinical characteristics were evaluated at the time of ICU admission, and they were followed up until discharge from ICU. The screening performance characteristics of CURB-65, qSOFA, and SIRS in predicting their mortality was compared. RESULTS 225 patients with the mean age of 63.27±14.89 years were studied (56.89% male). The in-hospital mortality rate of this series of patients was 39.10%. The area under the curve (AUC) of SIRS, CURB-65, and qSOFA were 0.62 (95% CI: 0.55 - 0.69), 0.66 (95% CI: 0.59 - 0.73), and 0.61(95% CI: 0.54 - 0.67), respectively (p = 0.508). In cut-off ≥1, the estimated sensitivity values of SIRS, CURB-65, and qSOFA were 85.23%, 96.59%, and 78.41%, respectively. The estimated specificity of scores were 34.31%, 6.57%, and 38.69%, respectively. In cut-off ≥2, the sensitivity values of SIRS, CURB-65, and qSOFA were evaluated as 39.77%, 87.50%, and 15.91%, respectively. Meanwhile, the specificity of scores were 72.99%, 34.31%, and 92.70%. CONCLUSIONS It seems that the performance of SIRS, CURB-65, and qSOFA is similar in predicting the ICU mortality of COVID-19 patients. However, the sensitivity of CURB-65 is higher than qSOFA and SIRS.
Collapse
Affiliation(s)
- Sorour Khari
- Student Research Committee, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Atefe Salimi Akin Abadi
- Clinical Research Development Center, Shahid Modarres Educational Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Marzieh Pazokian
- Department of Medical- Surgical Nursing, School of Nursing and Midwifery, Clinical Research Development Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. ,Corresponding author: Marzieh Pazokian; Department of Medical- Surgical Nursing, School of Nursing and Midwifery, Clinical Research Development Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. , ORCID: 0000-0002-7583-1824, Tel: 0098-21-88202519, Fax: 0098-21-88202518
| | - Mahmoud Yousefifard
- Physiology Research Center, Iran University of Medical Sciences, Tehran, Iran.,Corresponding author: Marzieh Pazokian; Department of Medical- Surgical Nursing, School of Nursing and Midwifery, Clinical Research Development Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. , ORCID: 0000-0002-7583-1824, Tel: 0098-21-88202519, Fax: 0098-21-88202518
| |
Collapse
|
13
|
Atmaja HK, Pranata S, Augustin K, Luthfia E. Accessibility of e-EWSS versus Manual EWSS for Detecting the Emergency Condition among Patients with Coronavirus Disease 2019: A Survey Research on Register Nurse in Indonesia. Open Access Maced J Med Sci 2022. [DOI: 10.3889/oamjms.2022.8678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND: The early warning scoring system (EWSS) during the coronavirus disease 2019 (COVID-19) pandemic is essential, because it will reduce the risk of organ damage and the death of patients with COVID-19. Health professionals argue that EWSS will be needed in electronic form, because it will be easier to use and quick to identify patient conditions in an emergency situation. There is no study that provides information on the comparison between the use of Electronic EWSS (e-EWSS) and manual EWSS in accessibility among health professionals in a clinical setting.
AIM: The purpose of this study was to analyze the difference of accessibility of e-EWSS versus manual EWSS through survey research on registered nurses in Indonesia.
METHODS: A survey research was designed in this study. A study was conducted from July to November 2021 on 38 nurses at the COVID-19 referral hospital in Mataram city. Data were collected by a questionnaire containing 12 questions related to the accessibility of e-EWSS and manual EWSS in 19 participants on intervention and 19 participants in the control group.
RESULTS: The response to the accessibility of e-EWSS was more positive, namely, 64.5%, while the negative accessibility response was 35.5%. On the other hand, for EWSS, the response to accessibility was more negative, namely, 51.6%, while the response to accessibility was positive as much as 48.4%. The accessibility of emergency examinations of patients with COVID-19 using the e-EWSS was easier than the EWSS with p = 0.000.
CONCLUSION:e-EWSS was easier in accessibility compared to EWSS by convenience, speed, and effectiveness indicators. The computerized system on the e-EWSS was capable of performing calculations automatically about patients’ emergency situations.
Collapse
|
14
|
Levenfus I, Ullmann E, Petrowski K, Rose J, Huber LC, Stüssi-Helbling M, Schuurmans MM. The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients. Diagnostics (Basel) 2022; 12:diagnostics12030604. [PMID: 35328157 PMCID: PMC8947178 DOI: 10.3390/diagnostics12030604] [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: 01/31/2022] [Revised: 02/16/2022] [Accepted: 02/23/2022] [Indexed: 11/16/2022] Open
Abstract
Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has caused a global burden for health care systems due to high morbidity and mortality rates, leading to caseloads that episodically surpass hospital resources. Due to different disease manifestations, the triage of patients at high risk for a poor outcome continues to be a major challenge for clinicians. The AIFELL score was developed as a simple decision instrument for emergency rooms to distinguish COVID-19 patients in severe disease stages from less severe COVID-19 and non-COVID-19 cases. In the present study, we aimed to evaluate the AIFELL score as a prediction tool for clinical deterioration and disease severity in hospitalized COVID-19 patients. During the second wave of the COVID-19 pandemic in Switzerland, we analyzed consecutively hospitalized patients at the Triemli Hospital Zurich from the end of November 2020 until mid-February 2021. Statistical analyses were performed for group comparisons and to evaluate significance. AIFELL scores of patients developing severe COVID-19 stages IIb and III during hospitalization were significantly higher upon admission compared to those patients not surpassing stages I and IIa. Group comparisons indicated significantly different AIFELL scores between each stage. In conclusion, the AIFELL score at admission was useful to predict the disease severity and progression in hospitalized COVID-19 patients.
Collapse
Affiliation(s)
- Ian Levenfus
- Department of Pulmonology, University Hospital Zurich, 8091 Zurich, Switzerland;
- Faculty of Medicine, University of Zurich, 8032 Zurich, Switzerland
- Correspondence: or
| | - Enrico Ullmann
- Department of Medicine, Technical University Dresden, 01307 Dresden, Germany;
- Department of Pediatric Psychiatry, Psychotherapy and Psychosomatics, University of Leipzig Medical Center, 04103 Leipzig, Germany
- Department of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia
| | - Katja Petrowski
- Medical Psychology and Sociology, Johannes Gutenberg University Mainz, 55131 Mainz, Germany;
| | - Jutta Rose
- Clinic for Internal Medicine, Department of Internal Medicine, City Hospital Zurich Triemli, 8063 Zurich, Switzerland; (J.R.); (L.C.H.); (M.S.-H.)
| | - Lars C. Huber
- Clinic for Internal Medicine, Department of Internal Medicine, City Hospital Zurich Triemli, 8063 Zurich, Switzerland; (J.R.); (L.C.H.); (M.S.-H.)
| | - Melina Stüssi-Helbling
- Clinic for Internal Medicine, Department of Internal Medicine, City Hospital Zurich Triemli, 8063 Zurich, Switzerland; (J.R.); (L.C.H.); (M.S.-H.)
| | - Macé M. Schuurmans
- Department of Pulmonology, University Hospital Zurich, 8091 Zurich, Switzerland;
- Faculty of Medicine, University of Zurich, 8032 Zurich, Switzerland
| |
Collapse
|
15
|
Kaeley N, Mahala P, Kabi A, Choudhary S, Hazra AG, Vempalli S. Utility of early warning scores to predict mortality in COVID-19 patients: A retrospective observational study. Int J Crit Illn Inj Sci 2021; 11:161-166. [PMID: 34760663 PMCID: PMC8547678 DOI: 10.4103/ijciis.ijciis_64_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 08/26/2021] [Indexed: 12/19/2022] Open
Abstract
Background: Coronavirus disease 2019 (COVID19) has evolved as a global pandemic. The patients with COVID-19 infection can present as mild, moderate, and severe disease forms. The reported mortality of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection is around 6.6%, which is lower than that of SARS-CoV and (middle east respiratory syndrome CoV). However, the fatality rate of COVID-19 infection is higher in the geriatric age group and in patients with multiple co-morbidities. The study aimed to evaluate the utility of early warning scores (EWS) to predict mortality in patients with moderate to severe COVID-19 infection. Methods: This retrospective study was carried out in a tertiary care institute of Uttarakhand. Demographic and clinical data of the admitted patients with moderate-to-severe COVID-19 infection were collected from the hospital record section and utilized to calculate the EWS-National early warning score (NEWS), modified early warning score (MEWS), Rapid Acute Physiology Score (RAPS), rapid emergency medicine score (REMS), and worthing physiological scoring system (WPS). Results: The area under the curve for NEWS, MEWS, RAPS, REMS, and WPS was 0.813 (95% confidence interval [CI]; 0.769–0.858), 0.770 (95% CI; 0.717–0.822), 0.755 (95% CI; 0.705–0.805), 0.892 (95% CI; 0.859–0.924), and 0.892 (95% CI; 0.86–0.924), respectively. Conclusion: The EWS at triage can be used for early assessment of severity as well as predict mortality in patients with COVID-19 patients.
Collapse
Affiliation(s)
- Nidhi Kaeley
- Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Prakash Mahala
- Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Ankita Kabi
- Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Suman Choudhary
- Department of Microbiology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Anirban Ghosh Hazra
- Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Subramanyam Vempalli
- Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| |
Collapse
|
16
|
Akdur G, Daş M, Bardakci O, Akman C, Sıddıkoğlu D, Akdur O, Akçalı A, Erbaş M, Reşorlu M, Beyazit Y. Prediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index. Am J Emerg Med 2021; 50:546-552. [PMID: 34547696 PMCID: PMC8411577 DOI: 10.1016/j.ajem.2021.08.079] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/25/2021] [Accepted: 08/30/2021] [Indexed: 10/25/2022] Open
Abstract
INTRODUCTION The assessment of disease severity and the prediction of clinical outcomes at early disease stages can contribute to decreased mortality in patients with Coronavirus disease 2019 (COVID-19). This study was conducted to develop and validate a multivariable risk prediction model for mortality with using a combination of computed tomography severity score (CT-SS), national early warning score (NEWS), and quick sequential (sepsis-related) organ failure assessment (qSOFA) in COVID-19 patients. METHODS We retrospectively collected medical data from 655 adult COVID-19 patients admitted to our hospital between July and November 2020. Data on demographics, clinical characteristics, and laboratory and radiological findings measured as part of standard care at admission were used to calculate NEWS, qSOFA score, CT-SS, peripheral perfusion index (PPI) and shock index (SI). Logistic regression and Cox proportional hazard models were used to predict mortality, which was our primary outcome. The predictive accuracy of distinct scoring systems was evaluated by the receiver-operating characteristic (ROC) curve analysis. RESULTS The median age was 50.0 years [333 males (50.8%), 322 females (49.2%)]. Higher NEWS and SI was associated with time-to-death within 90-days, whereas higher age, CT-SS and lower PPI were significantly associated with time-to-death within both 14 days and 90 days in the adjusted Cox regression model. The CT-SS predicted different mortality risk levels within each stratum of NEWS and qSOFA and improved the discrimination of mortality prediction models. Combining CT-SS with NEWS score yielded more accurate 14 days (DBA: -0.048, p = 0.002) and 90 days (DBA: -0.066, p < 0.001) mortality prediction. CONCLUSION Combining severity tools such as CT-SS, NEWS and qSOFA improves the accuracy of predicting mortality in patients with COVID-19. Inclusion of these tools in decision strategies might provide early detection of high-risk groups, avoid delayed medical attention, and improve patient outcomes.
Collapse
Affiliation(s)
- Gökhan Akdur
- Department of Emergency Medicine, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Murat Daş
- Department of Emergency Medicine, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Okan Bardakci
- Department of Emergency Medicine, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey.
| | - Canan Akman
- Department of Emergency Medicine, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Duygu Sıddıkoğlu
- Department of Biostatistics, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Okhan Akdur
- Department of Emergency Medicine, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Alper Akçalı
- Department of Medical Microbiology, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Mesut Erbaş
- Department of Anesthesiology and Reanimation, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Mustafa Reşorlu
- Department of Radiology, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| | - Yavuz Beyazit
- Department of Internal Medicine, Faculty of Medicine, Çanakkale Onsekiz Mart University, 17020 Çanakkale, Turkey
| |
Collapse
|
17
|
Wang H, Ai H, Fu Y, Li Q, Cui R, Ma X, Ma YF, Wang Z, Liu T, Long Y, Qu K, Liu C, Zhang J. Development of an Early Warning Model for Predicting the Death Risk of Coronavirus Disease 2019 Based on Data Immediately Available on Admission. Front Med (Lausanne) 2021; 8:699243. [PMID: 34490294 PMCID: PMC8416661 DOI: 10.3389/fmed.2021.699243] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 07/16/2021] [Indexed: 02/02/2023] Open
Abstract
Introduction: COVID-19 has overloaded worldwide medical facilities, leaving some potentially high-risk patients trapped in outpatient clinics without sufficient treatment. However, there is still a lack of a simple and effective tool to identify these patients early. Methods: A retrospective cohort study was conducted to develop an early warning model for predicting the death risk of COVID-19. Seventy-five percent of the cases were used to construct the prediction model, and the remaining 25% were used to verify the prediction model based on data immediately available on admission. Results: From March 1, 2020, to April 16, 2020, a total of 4,711 COVID-19 patients were included in our study. The average age was 63.37 ± 16.70 years, of which 1,148 (24.37%) died. Finally, age, SpO2, body temperature (T), and mean arterial pressure (MAP) were selected for constructing the model by univariate analysis, multivariate analysis, and a review of the literature. We used five common methods for constructing the model and finally found that the full model had the best specificity and higher accuracy. The area under the ROC curve (AUC), specificity, sensitivity, and accuracy of full model in train cohort were, respectively, 0.798 (0.779, 0.816), 0.804, 0.656, and 0.768, and in the validation cohort were, respectively, 0.783 (0.751, 0.815), 0.800, 0.616, and 0.755. Visualization tools of the prediction model included a nomogram and an online dynamic nomogram (https://wanghai.shinyapps.io/dynnomapp/). Conclusion: We developed a prediction model that might aid in the early identification of COVID-19 patients with a high probability of mortality on admission. However, further research is required to determine whether this tool can be applied for outpatient or home-based COVID-19 patients.
Collapse
Affiliation(s)
- Hai Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Haibo Ai
- Rehabilitation Medicine Department, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China
| | - Yunong Fu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qinglin Li
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ruixia Cui
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiaohua Ma
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yan-Fen Ma
- Department of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zi Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Tong Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yunxiang Long
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Kai Qu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jingyao Zhang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Surgical ICU, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| |
Collapse
|
18
|
Accordino S, Sozzi F, Canetta C. Performance of NEWS and NEWS-C in acute medical no COVID-19 patients. Resuscitation 2021; 166:83-84. [PMID: 34302923 PMCID: PMC8295049 DOI: 10.1016/j.resuscitation.2021.07.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 07/02/2021] [Indexed: 10/26/2022]
Affiliation(s)
- Silvia Accordino
- High Care Internal Medicine Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milano, Italy.
| | - Fabiola Sozzi
- Cardiology Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milano, Italy
| | - Ciro Canetta
- High Care Internal Medicine Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milano, Italy
| |
Collapse
|
19
|
Zhang K, Zhang X, Ding W, Xuan N, Tian B, Huang T, Zhang Z, Cui W, Huang H, Zhang G. National Early Warning Score Does Not Accurately Predict Mortality for Patients With Infection Outside the Intensive Care Unit: A Systematic Review and Meta-Analysis. Front Med (Lausanne) 2021; 8:704358. [PMID: 34336903 PMCID: PMC8319382 DOI: 10.3389/fmed.2021.704358] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 06/21/2021] [Indexed: 12/29/2022] Open
Abstract
Background: The prognostic value of the national early warning score (NEWS) in patients with infections remains controversial. We aimed to evaluate the prognostic accuracy of NEWS for prediction of in-hospital mortality in patients with infections outside the intensive care unit (ICU). Methods: We searched PubMed, Embase, and Scopus for related articles from January 2012 to April 2021. Sensitivity, specificity, and likelihood ratios were pooled by using the bivariate random-effects model. Overall prognostic performance was summarized by using the area under the curve (AUC). We performed subgroup analyses to assess the prognostic accuracy of NEWS in selected populations. Results: A total of 21 studies with 107,008 participants were included. The pooled sensitivity and specificity of NEWS were 0.71 and 0.60. The pooled AUC of NEWS was 0.70, which was similar to quick sequential organ failure assessment (qSOFA, AUC: 0.70) and better than systemic inflammatory response syndrome (SIRS, AUC: 0.60). However, the sensitivity (0.55) and AUC (0.63) of NEWS were poor in elder patients. The NEWS of 5 was more sensitive, which was a better threshold for activating urgent assessment and treatment. Conclusions: The NEWS had good diagnostic accuracy for early prediction of mortality in patients with infections outside the ICU, and the sensitivity and specificity were more moderate when compared with qSOFA and SIRS. Insufficient sensitivity and poor performance in the elder population may have limitations as an early warning score for adverse outcomes. NEWS should be used for continuous monitoring rather than a single time point predictive tool.
Collapse
Affiliation(s)
- Kai Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xing Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Medical Security Bureau of Yinzhou District, Ningbo, China
| | - Wenyun Ding
- Department of Respiration and Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Department of Respiration Medicine, Community Health Service Center, Shanghai, China
| | - Nanxia Xuan
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Baoping Tian
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tiancha Huang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhaocai Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wei Cui
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Huaqiong Huang
- Department of Respiration and Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Gensheng Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| |
Collapse
|
20
|
Zhang K, Zhang X, Ding W, Xuan N, Tian B, Huang T, Zhang Z, Cui W, Huang H, Zhang G. The Prognostic Accuracy of National Early Warning Score 2 on Predicting Clinical Deterioration for Patients With COVID-19: A Systematic Review and Meta-Analysis. Front Med (Lausanne) 2021; 8:699880. [PMID: 34307426 PMCID: PMC8298908 DOI: 10.3389/fmed.2021.699880] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 06/07/2021] [Indexed: 01/08/2023] Open
Abstract
Background: During the coronavirus disease 2019 (COVID-19) pandemic, the National Early Warning Score 2 (NEWS2) is recommended for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. Therefore, our purpose is to assess the prognostic accuracy of NEWS2 on predicting clinical deterioration for patients with COVID-19. Methods: We searched PubMed, Embase, Scopus, and the Cochrane Library from December 2019 to March 2021. Clinical deterioration was defined as the need for intensive respiratory support, admission to the intensive care unit, or in-hospital death. Sensitivity, specificity, and likelihood ratios were pooled by using the bivariate random-effects model. Overall prognostic performance was summarized by using the area under the curve (AUC). We performed subgroup analyses to assess the prognostic accuracy of NEWS2 in different conditions. Results: Eighteen studies with 6,922 participants were included. The NEWS2 of five or more was commonly used for predicting clinical deterioration. The pooled sensitivity, specificity, and AUC were 0.82, 0.67, and 0.82, respectively. Benefitting from adding a new SpO2 scoring scale for patients with hypercapnic respiratory failure, the NEWS2 showed better sensitivity (0.82 vs. 0.75) and discrimination (0.82 vs. 0.76) than the original NEWS. In addition, the NEWS2 was a sensitive method (sensitivity: 0.88) for predicting short-term deterioration within 72 h. Conclusions: The NEWS2 had moderate sensitivity and specificity in predicting the deterioration of patients with COVID-19. Our results support the use of NEWS2 monitoring as a sensitive method to initially assess COVID-19 patients at hospital admission, although it has a relatively high false-trigger rate. Our findings indicated that the development of enhanced or modified NEWS may be necessary.
Collapse
Affiliation(s)
- Kai Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xing Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Medical Security Bureau of Yinzhou District, Ningbo, China
| | - Wenyun Ding
- Department of Respiration and Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Nanxia Xuan
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Baoping Tian
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tiancha Huang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhaocai Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wei Cui
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Huaqiong Huang
- Department of Respiration and Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Gensheng Zhang
- Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| |
Collapse
|
21
|
Azimirad M, Magnusson C, Wiseman A, Selander T, Parviainen I, Turunen H. British and Finnish nurses' attitudes, practice, and knowledge on deteriorating patient in-service education: A study in two acute hospitals. Nurse Educ Pract 2021; 54:103093. [PMID: 34052539 DOI: 10.1016/j.nepr.2021.103093] [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: 10/12/2020] [Revised: 04/12/2021] [Accepted: 05/17/2021] [Indexed: 10/21/2022]
Abstract
AIM The aim was to assess both nurses' attitudes about in-service education, and the impact had by attending in-service education on nurses' management and knowledge of deteriorating patients. BACKGROUND In-service education cannot reach its best potential outcomes without strong leadership. Nurse managers are in a position of adopting leadership styles and creating conditions for enhancing the in-service education outcomes. DESIGN We conducted a comparative cross-sectional study between British and Finnish nurses (N = 180; United Kingdom: n = 86; Finland: n = 94). METHODS A modified "Rapid Response Team Survey" was used in data collection. A sample of medical and surgical registered nurses were recruited from acute care hospitals. Self-reporting, self-reflection, and case-scenarios were used to assess nurses' attitudes, practice, and knowledge. Data were analyzed by Mann-Whitney-U and Chi-square tests. RESULTS Nurses' views on education programs were positive; however, low confidence, delays caused by hospital culture, and fear of criticism remained barriers to post education management of deteriorating patients. Nurses' self-reflection on their management of deteriorating patients indicates that 20-25% of deteriorating patients are missed. CONCLUSION Nurse managers should promote a no-blame culture, mitigate unnecessary hospital culture and routines, and facilitate in-service education focusing on identification and management of deteriorating patients, simultaneously improving nurses' confidence.
Collapse
Affiliation(s)
- Mina Azimirad
- University of Eastern Finland (UEF), Department of Nursing Science, POBox 1627, 70211 Kuopio, Finland.
| | - Carin Magnusson
- Duke of Kent Building, School of Health Sciences, Faculty of Health & Medical Sciences, University of Surrey, Guildford, Surrey, UK.
| | - Allison Wiseman
- College of Health & Life Sciences, Brunel University London, Uxbridge UB8 3BH, UK.
| | | | | | - Hannele Turunen
- University of Eastern Finland (UEF), Department of Nursing Science, POBox 1627, 70211 Kuopio, Finland; Kuopio University Hospital, Kuopio, Finland.
| |
Collapse
|