Pneumonia severity indices predict prognosis in coronavirus disease-2019

Uçan, Eyüp Sabri; Alpaydın, Aylin Özgen; Ermis, Saliha Selin Özuygur; Ercan, Gülsüm Songül; Unal, Belgin; Sayıner, Ayça Arzu; Ergan, Begüm; Gökmen, Necati; Savran, Yusuf; Kılınç, Oğuz; Oğuz, Vildan Avkan

doi:10.1016/j.resmer.2021.100826

Cited by 11 publications

(11 citation statements)

References 17 publications

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“…Fourth, data on causes of death, such as venous thromboembolism, which affects the course of the disease and shows seasonal characteristics were not collected. Finally, previous studies from Turkey have reported mortality rates in the first wave varying from 4.2% to 75.8% 15–20 . This variation was possibly driven by differences in study settings and patient population characteristics.…”

Section: Limitationsmentioning

confidence: 81%

“…Finally, previous studies from Turkey have reported mortality rates in the first wave varying from 4.2% to 75.8%. [15][16][17][18][19][20] This variation was possibly driven by differences in study settings and patient population characteristics. However, we are not aware of any studies from Turkey that reported a mortality rate of the second wave or compared mortality rates between the first and second waves.…”

Section: Limitationsmentioning

confidence: 99%

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Comparison of demographic and clinical characteristics of hospitalized COVID‐19 patients with severe/critical illness in the first wave versus the second wave

Altunok

Satıcı

Dinc

et al. 2021

Journal of Medical Virology

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Due to current advances and growing experience in the management of coronavirus Disease 2019 , the outcome of COVID-19 patients with severe/critical illness would be expected to be better in the second wave compared with the first wave. As our hospitalization criteria changed in the second wave, we aimed to investigate whether a favorable outcome occurred in hospitalized COVID-19 patients with only severe/critical illness. Among 642 laboratory-confirmed hospitalized COVID-19 patients in the first wave and 1121 in the second wave, those who met World Health Organization (WHO) definitions for severe or critical illness on admission or during follow-up were surveyed. Data on demographics, comorbidities, C-reactive protein (CRP) levels on admission, and outcomes were obtained from an electronic hospital database. Univariate analysis was performed to compare the characteristics of patients in the first and second waves. There were 228 (35.5%) patients with severe/critical illness in the first wave and 681 (60.7%) in the second wave. Both groups were similar in terms of age, gender, and comorbidities, other than chronic kidney disease. Median serum CRP levels were significantly higher in patients in the second wave compared with those in the first wave [109 mg/L (interquartile range [IQR]: 65-157) vs. 87 mg/L (IQR: 39-140); p < 0.001]. However, intensive care unit admission and mortality rates were similar among the waves.Even though a lower mortality rate in the second wave has been reported in previous studies, including all hospitalized COVID-19 patients, we found similar demographics and outcomes among hospitalized COVID-19 patients with severe/ critical illness in the first and second wave.

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Section: Limitationsmentioning

confidence: 81%

Section: Limitationsmentioning

confidence: 99%

Comparison of demographic and clinical characteristics of hospitalized COVID‐19 patients with severe/critical illness in the first wave versus the second wave

Altunok

Satıcı

Dinc

et al. 2021

Journal of Medical Virology

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“…A-DROP score had the highest second rank in predicting in-hospital mortality with 0.929 AUROC (95% CI 0.911–0.948). In contradiction, there are also studies reporting that A-DROP score performs better than the PSI/PORT in predicting the in-hospital mortality of COVID-19 patients AUROCs for A-DROP 0.87 (95% CI 0.84–0.90) vs. PSI 0.85 (95% CI 0.81–0.88) [ 16 ] and AUROCs for A-DROP 0.875 (95% CI; 0.822–0.937) vs. PSI 0.873 (95% CI 0.820–0.925) [ 68 ]. These findings suggest that involving advanced age [ 4 , 8 , 18 ], which is related to higher COVID-19 mortality, places A-DROP score in a superior situation compared to CURB-65 in predicting mortality.…”

Section: Discussionmentioning

confidence: 99%

“…In our study, the capability of PSI /PORT (AUROC 0.971) and A-DROP (AUROC 0.929) to predict hospital mortality was better than other studies in COVID-19 pneumonia, with the results of AUROC PSI/PORT values of 0.85 (95% CI 0.81–0.88) [ 16 ], 0.85 (95% CI 0.78–0.90) [ 37 ], 0.835 (95% CI 0.826–0.845) [ 60 ], 0.874 (95% CI 0.808–0.939) [ 18 ], 0.873(95% CI 0.820–0.925) [ 68 ], while AUROC A-DROP results were 0.87 (95% CI 0.84–0.90) [ 16 ] and 0.875 (95% CI 0.822–0.937) [ 68 ].…”

Section: Discussionmentioning

confidence: 99%

Comparison of Pneumonia Severity Indices, qCSI, 4C-Mortality Score and qSOFA in Predicting Mortality in Hospitalized Patients with COVID-19 Pneumonia

Akıllı

Bilge

Guz

et al. 2022

JPM

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This is a retrospective and observational study on 1511 patients with SARS-CoV-2, who were diagnosed with COVID-19 by real-time PCR testing and hospitalized due to COVID-19 pneumonia. 1511 patients, 879 male (58.17%) and 632 female (41.83%) with a mean age of 60.1 ± 14.7 were included in the study. Survivors and non-survivors groups were statistically compared with respect to survival, discharge, ICU admission and in-hospital death. Although gender was not statistically significant different between two groups, 80 (60.15%) of the patients who died were male. Mean age was 72.8 ± 11.8 in non-survivors vs. 59.9 ± 14.7 in survivors (p < 0.001). Overall in-hospital mortality was found to be 8.8% (133/1511 cases), and overall ICU admission was 10.85% (164/1511 cases). The PSI/PORT score of the non-survivors group was higher than that of the survivors group (144.38 ± 28.64 versus 67.17 ± 25.63, p < 0.001). The PSI/PORT yielding the highest performance was the best predictor for in-hospital mortality, since it incorporates the factors as advanced age and comorbidity (AUROC 0.971; % 95 CI 0.961–0.981). The use of A-DROP may also be preferred as an easier alternative to PSI/PORT, which is a time-consuming evaluation although it is more comprehensive.

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“…However, effective triage is crucial for informing clinical decision making and facilitating resource allocation. Several tests have been proposed for COVID-19 patients and have been examined as triaging tools for in-hospital clinical deterioration, such as the Rothman Index, a well-established acuity measure score, the quick Sequential (Sepsis-related) Organ Failure Assessment (SOFA) score that identifies non-ICU patients with suspected infection who are at a high risk for in-hospital mortality, the CURB-65 or CRB-65 and the A-DROP (a modified CURB-65 score) that estimate the mortality of community acquired pneumonia, the National Early Warning Score (NEWS) score that determines the degree of illness of a patient and prompts critical care intervention, the Modified Early Warning Score (MEWS) that identifies patients who are at risk for clinical deterioration and who may require a higher level of care, the Rapid Emergency Medicine Score (REMS) that predicts in-hospital mortality in nonsurgical patients presenting to the ED, and the pneumonia severity index (PSI) that calculates the probability of morbidity and mortality among patients with community acquired pneumonia ( Table 1 ) [ 13 , 14 , 15 , 16 , 17 , 18 ]. However, none of these tests have reached sufficient performance and cannot be used in clinical decision-making in COVID-19 patients.…”

Section: Predicting Deterioration Riskmentioning

confidence: 99%

Management of COVID-19 Patients in the Emergency Department

Pantazopoulos

Tsikrika

Kolokytha

et al. 2021

JPM

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COVID-19 is an emerging disease of global public health concern. As the pandemic overwhelmed emergency departments (EDs), a restructuring of emergency care delivery became necessary in many hospitals. Furthermore, with more than 2000 papers being published each week, keeping up with ever-changing information has proven to be difficult for emergency physicians. The aim of the present review is to provide emergency physician with a summary of the current literature regarding the management of COVID-19 patients in the emergency department.

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Pneumonia severity indices predict prognosis in coronavirus disease-2019

Cited by 11 publications

References 17 publications

Comparison of demographic and clinical characteristics of hospitalized COVID‐19 patients with severe/critical illness in the first wave versus the second wave

Comparison of demographic and clinical characteristics of hospitalized COVID‐19 patients with severe/critical illness in the first wave versus the second wave

Comparison of Pneumonia Severity Indices, qCSI, 4C-Mortality Score and qSOFA in Predicting Mortality in Hospitalized Patients with COVID-19 Pneumonia

Management of COVID-19 Patients in the Emergency Department

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