Mortality estimation using APACHE and CT scores with stepwise linear regression method in COVID-19 intensive care unit: A retrospective study

Ayvat, Pınar; Ömeroğlu, Şeyda Kayhan

doi:10.1016/j.clinimag.2022.04.017

Cited by 7 publications

(2 citation statements)

References 30 publications

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“…In the study performed by Ayvat et al, mean APACHE score of all patients was 17.95, mean APACHE II score of non-survivor group was 20.28, and mortality rate was 69.86 [40].…”

Section: Discussionmentioning

confidence: 92%

Evaluation of clinical features and laboratory findings in critical intensive care unit patients with severe coronavirus disease‐19 who underwent extracorporeal cytokine adsorption

Yavuz

Orhan

Rollas³

et al. 2023

Ther Apher Dial

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AimTo evaluate the inflammatory parameters and oxygenation in severe coronavirus disease‐19 patients who underwent extracorporeal cytokine adsorption (CA).MethodsPatients who underwent extracorporeal CA for cytokine storm were included in the study. The changes in oxygenation, laboratory parameters, and mortality rates were investigated.ResultsThirty‐six patients were included in the study. The hemoglobin, thrombocyte, and C‐reactive protein (CRP) decreased, and PaO2/FiO2 ratio increased (p < 0.001; p < 0.01; p < 0.001; p = 0.04, respectively). Twelve (33.3%) patients received a single session, 24 (66.6%) received 2 or more sessions. CRP and fibrinogen levels decreased, and PaO2/FIO2 ratio increased in the single session group (p = 0.04; p = 0.04; p = 0.01, respectively). In the multi‐session group, the hemoglobin, platelet, procalcitonin, and CRP levels decreased, and PaO2/FIO2 ratio increased (p < 0.01; p = 0.02; p = 0.02; p < 0.01; p = 0.01, respectively). Day 15, 30, and 90 mortality rates were 61.1%, 83.3%, and 88.9%.ConclusionCA with hemoperfusion reduced CRP and improved oxygenation; however, mortality rates were high.

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“…In the study performed by Ayvat et al, mean APACHE score of all patients was 17.95, mean APACHE II score of non-survivor group was 20.28, and mortality rate was 69.86 [40].…”

Section: Discussionmentioning

confidence: 92%

Evaluation of clinical features and laboratory findings in critical intensive care unit patients with severe coronavirus disease‐19 who underwent extracorporeal cytokine adsorption

Yavuz

Orhan

Rollas³

et al. 2023

Ther Apher Dial

View full text Add to dashboard Cite

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“…A stepwise regression analysis was conducted to determine the essential/dominant characters related to the main character (Ayvat and Omeroglu 2022). The generated model by stepwise analysis was considered more precise in predicting the results based on the resulting model than the correlation involving all observation variables (Andayani et al 2016).…”

Section: Correlation Of Important Character To the Yieldmentioning

confidence: 99%

Secondary trait and index selection determination for maize genotype selection in acidic tidal swamp environment

et al. 2022

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Abstract. Suwarti, Ghulamahdi M, Sopandie D, Trikoesoemaningtyas, Sulistyono E, Azrai M. 2022. Secondary trait and index selection determination for maize genotype selection in acidic tidal swamp environment. Biodiversitas 23: 4169-4179. Determining secondary traits as complementary selection in maize genotypes for abiotic stress environment is compulsory since yield-based selection usually provides biased result. This study aimed to obtain secondary traits for maize selection in an abiotic multi-stresses of Fe, Al, and temporary flooding environments of acid sulfate tidal swamp land using multivariate analysis. A total of 150 (un-repeated) maize inbred lines and five check genotypes in five replicates were arranged in a randomized augmented plot design in three environments to generate 525 single plots. Three types of environments based on irrigation regimes were applied on acid soil tidal swamp land to study the agronomic characteristics of maize genotypes in each environment. Saturated Cultivation Technology (SSC) was considered the optimal environment. Dryland treatment was the condition to let the irrigation only depend on rainwater. Temporary flooding treatment was carried out at five stages of different growth periods. Several steps of analysis were applied in this study by taking variance, and heritability was used as the basis for selections. The characters affected by treatments with medium to high heritability were then analyzed with correlation and pathway analysis. Seven selection indexes, SSI, GMP, YSI, YI, TOL, STI, and MP, that have a high correlation to yield in both optimum and stress environments, were applied simultaneity with the selected trait characters to screen the genotypes utilizing PCA biplot analysis. Venn analysis was used to group the genotypes based on the result of the analysis. Indices of STI, MP, GMP, and traits of rows number per ear and the weight of 6 ears were selected as secondary characters for the maize genotypes selection in Saturated Soil culture with temporary flooding stress. Meanwhile, STI, MP, and ear stand height were the selected characters in the dryland of acid sulfate tidal swamp land. Based on the combination of all secondary character selection, genotypes were grouped into five types of stress tolerance in SSC+TF and DL environments. Eight genotypes were tolerant to both SSC+TF and DL stress, and two genotypes were susceptible to both environments.

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Prognostic models in COVID-19 infection that predict severity: a systematic review

et al. 2023

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Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

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Mortality estimation using APACHE and CT scores with stepwise linear regression method in COVID-19 intensive care unit: A retrospective study

Cited by 7 publications

References 30 publications

Evaluation of clinical features and laboratory findings in critical intensive care unit patients with severe coronavirus disease‐19 who underwent extracorporeal cytokine adsorption

Evaluation of clinical features and laboratory findings in critical intensive care unit patients with severe coronavirus disease‐19 who underwent extracorporeal cytokine adsorption

Secondary trait and index selection determination for maize genotype selection in acidic tidal swamp environment

Prognostic models in COVID-19 infection that predict severity: a systematic review

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