Prediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index

Akdur, Gökhan; Daş, Murat; Bardakçı, Okan; Akman, Canan; Sıddıkoğlu, Duygu; Akdur, Okhan; Akçalı, Alper; Erbaş, Mesut; Reşorlu, Mustafa; Beyazıt, Yavuz

doi:10.1016/j.ajem.2021.08.079

Cited by 20 publications

(22 citation statements)

References 31 publications

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“…27 In the study done by Akdur etal, PPI relevance with predicting mortality in COVID-19 patients was analyzed and it was found that it has significant relevance in predicting 14- and 90-day mortality at the <1.5 cutoff value. 28 Similar to the literature, in our study, PPI was found to be significant to show COVID-19 seriousness with 70.4% sensitivity and71% specificity at the 2.2 cutoff value.…”

Section: Discussionsupporting

confidence: 90%

Can Peripheral Perfusion Index (PPI) Predict Disease Severity in COVID-19 Patients in the Emergency Department?

Korkut¹,

Bedel²,

Selvi³

et al. 2022

Ibnosina Journal of Medicine and Biomedical Sciences

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Background Coronavirus disease 2019 (COVID-19) causes significant mortality and morbidity in severe patients. Objective In this study, we aimed to examine the relationship between COVID-19 disease severity and peripheral perfusion index (PPI). Patients and Methods This prospective observational study included COVID-19 patients admitted to the tertiary hospital emergency department. Basal clinical and demographic data of the patients and PPI values at the time of admission were recorded. The patients were categorized to severe and nonsevere groups according to clinical severity. The relationship between COVID-19 severity and PPI was examined in comparison with the control group. Results A total of 324 patients who met the inclusion criteria were analyzed. COVID-19 (+) was detected in 180 of these patients. Ninety-two of the COVID-19 (+) patients were in the severe group, and 88 of them were in the non severe group. Note that 164 COVID-19 (–) patients were in the control group. PPI average was found to be 1.44 ± 1.12 in the severe group, and 3.69 ± 2.51 in the nonsevere group. PPI average was found to be significantly lower in the severe group than the nonsevere group (p< 0.01) As for the nonsevere group and control group, PPI averages were found to be 3.69 ± 2.51 and3.54 ± 2.32, respectively, and a significant difference was determined between the two groups (p< 0.05). PPI COVID-19 severity predicting activity was calculated as area under the curve: 0.833, sensitivity:70.4%, andspecificity:71%(p = 0.025) at 2.2 cutoff value. Conclusion The results of our study showed that PPI is an easy-to-apply and useful parameter in the emergency department in determining the severity of COVID-19 patients.

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Section: Discussionsupporting

confidence: 90%

Can Peripheral Perfusion Index (PPI) Predict Disease Severity in COVID-19 Patients in the Emergency Department?

Korkut¹,

Bedel²,

Selvi³

et al. 2022

Ibnosina Journal of Medicine and Biomedical Sciences

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“… 3 – 5 In this context, the NEWS is a well validated prognostication tool that has proven to be effective in ED settings and has shown merit in predicting COVID-19-associated adverse events (eg, viral pneumonia or ARDS) but necessitates seven physiologic variables to compute. 3 – 6 Chest CT has been proposed as a significant determinant for COVID-19 diagnosis and follow-up but the risk of ionizing radiation, high cost, challenges related to infection control, and lack of continuous monitoring limits its value, especially for critically ill patients. 7 …”

Section: Introductionmentioning

confidence: 99%

Point-of-care Lung Ultrasound, Lung CT and NEWS to Predict Adverse Outcomes and Mortality in COVID-19 Associated Pneumonia

Bardakçı

Daş

Akdur

et al. 2022

J Intensive Care Med

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Introduction: The appraisal of disease severity and prediction of adverse outcomes using risk stratification tools at early disease stages is crucial to diminish mortality from coronavirus disease 2019 (COVID-19). While lung ultrasound (LUS) as an imaging technique for the diagnosis of lung diseases has recently gained a leading position, data demonstrating that it can predict adverse outcomes related to COVID-19 is scarce. The main aim of this study is therefore to assess the clinical significance of bedside LUS in COVID-19 patients who presented to the emergency department (ED). Methods: Patients with a confirmed diagnosis of SARS-CoV-2 pneumonia admitted to the ED of our hospital between March 2021 and May 2021 and who underwent a 12-zone LUS and a lung computed tomography scan were included prospectively. Logistic regression and Cox proportional hazard models were used to predict adverse events, which was our primary outcome. The secondary outcome was to discover the association of LUS score and computed tomography severity score (CT-SS) with the composite endpoints. Results: We assessed 234 patients [median age 59.0 (46.8-68.0) years; 59.4% M), including 38 (16.2%) in-hospital deaths for any cause related to COVID-19. Higher LUS score and CT-SS was found to be associated with ICU admission, intubation, and mortality. The LUS score predicted mortality risk within each stratum of NEWS. Pairwise analysis demonstrated that after adjusting a base prediction model with LUS score, significantly higher accuracy was observed in predicting both ICU admission (DBA −0.067, P = .011) and in-hospital mortality (DBA −0.086, P = .017). Conclusion: Lung ultrasound can be a practical prediction tool during the course of COVID-19 and can quantify pulmonary involvement in ED settings. It is a powerful predictor of ICU admission, intubation, and mortality and can be used as an alternative for chest computed tomography while monitoring COVID-19-related adverse outcomes.

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“…Moreover, Akdur and cols. demonstrated that a PPI lower than 1.5 was independently associated with both 14 days and 90 days mortality [25].…”

Section: Discussionmentioning

confidence: 98%

Assessment of Peripheral Perfusion in Severe Acute Respiratory Syndrome Coronavirus 2 (Sars-cov-2) Infection: An Exploratory Analysis With Near-infrared Spectroscopy

Souza

Galindo

Vianna

et al. 2022

Preprint

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Purpose: To investigate clinical and laboratory tissue perfusion in addition to near-infrared spectroscopy (NIRS) static and dynamic-derived parameters in critically ill COVID-19 patients. Methods: A cross-sectional single-center exploratory study was performed. Twenty adult patients with confirmed COVID-19 admitted to the intensive care unit (ICU) within 24 hours were prospectively included in this study. A control group without COVID-19 was composed by forty patients included in recently published study. Accessed NIRS-derived parameters included basal tissue oxygen saturation (StO2), descending slope (%/min), ascending slope (%/min), maximum value of StO2 (StO2max), recovery time (s) and the area under the curve of reactive hyperemia. Results: The median (IQR) age of included patients was 58 (46-69) years. Patients with COVID-19 presented higher SAPS III score [50 (46-53) vs. 45 (30-53), p=0.04] compared with control patients. Patients with SARS-CoV-2 infection showed higher StO2 min [60 (49-79) vs. 54 (48-58) %; p=0.04] and lower descending slope [5.7 (3.4-8.8) vs. 8.1 (6.4-9.7) %/min; p<0.01] compared with ICU patients without COVID-19. Basal StO2 [80 (74-90) vs. 82 (76-86) %; p=0.89], StO2 max [(91 (83-95) vs. 90 (84-94) %; p=0.86], ascending slope [2.0 (1.1-2.9) vs. 2.2 (1.5-3.3) %/min; p=0.43], recovery time [14.5 (12.0-22.0) vs. 21.5 (14.3-28.3) s; p=0.13] and hyperemia area [10.3 (5.8-13.0) vs. 8.6 (4.0-14.3); p=0.55] did not differ between, respectively, COVID-19 and control groups. Conclusion: Severe COVID-19 patients exhibited a lower rate of oxygen extraction by peripheral tissues than non-COVID-19 critically ill patients, which may represent an adaptive mechanism to hypoxemia. This hypothesis needs to be further investigated.

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Prediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index

Cited by 20 publications

References 31 publications

Can Peripheral Perfusion Index (PPI) Predict Disease Severity in COVID-19 Patients in the Emergency Department?

Can Peripheral Perfusion Index (PPI) Predict Disease Severity in COVID-19 Patients in the Emergency Department?

Point-of-care Lung Ultrasound, Lung CT and NEWS to Predict Adverse Outcomes and Mortality in COVID-19 Associated Pneumonia

Assessment of Peripheral Perfusion in Severe Acute Respiratory Syndrome Coronavirus 2 (Sars-cov-2) Infection: An Exploratory Analysis With Near-infrared Spectroscopy

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