Novel risk scoring system for predicting acute respiratory distress syndrome among hospitalized patients with coronavirus disease 2019 in Wuhan, China

Abstract

Background The mortality rate from acute respiratory distress syndrome (ARDS) is high among hospitalized patients with coronavirus disease 2019 (COVID-19). Hence, risk evaluation tools are required to immediately identify high-risk patients upon admission for early intervention. Methods A cohort of 220 consecutive patients with COVID-19 were included in this study. To analyze the risk factors of ARDS, data obtained from approximately 70% of the participants were randomly selected and used as training dataset to establish a logistic regression model. Meanwhile, data obtained from the remaining 30% of the participants were used as test dataset to validate the effect of the model. Results Lactate dehydrogenase, blood urea nitrogen, D-dimer, procalcitonin, and ferritin levels were included in the risk score system and were assigned a score of 25, 15, 34, 20, and 24, respectively. The cutoff value for the total score was > 35, with a sensitivity of 100.00% and specificity of 81.20%. The area under the receiver operating characteristic curve and the Hosmer–Lemeshow test were 0.967 (95% confidence interval [CI]: 0.925–0.989) and 0.437(P Value = 0.437). The model had excellent discrimination and calibration during internal validation. Conclusions The novel risk score may be a valuable risk evaluation tool for screening patients with COVID-19 who are at high risk of ARDS.

Prediction of in‐hospital mortality with machine learning for COVID‐19 patients treated with steroid and remdesivir

“…Our risk model is valuable to predict the risk of death for moderate or severe COVID‐19 patients treated with steroid and remdesivir. We demonstrated blood urea nitrogen as important variables rather than C‐reactive protein, D ‐dimer using SHAP 26,35 …”

“…We demonstrated blood urea nitrogen as important variables rather than C-reactive protein, D-dimer using SHAP. 26,35 Another strength of this study is the website calculator, which will enable frontline providers to identify high-risk patients immediately at the time of admission for patients requiring steroid and remdesivir. We consider risk prediction model is really useful especially when frontline providers can utilize it.…”

Development of a scoring system for the prediction of in-hospital mortality among COVID-19 patients

“…In addition, the sensitivity and specificity of these previous proposed scores have been reported anywhere between 70 and 100%. 13 , 14 , 15 However, after the internal validation of the previous scores, the most effective has been reported to be in the study of shang et al with 93.8% validated AUC. 16 On the other hand, the scoring system in the current study can be used as a prognostic tool due to the adequacy of its validity indicators in addition to the compatibility of its variables with other scores which were established after measuring its external validity.…”

Cardiovascular Disease Complicating COVID-19 in the Elderly

“…While moderate CRP elevation in the 3–10 mg/L range is useful in cardiovascular risk prediction, CRP values in COVID-19 may exceed 40 mg/L, reflecting an acute inflammatory response unrelated to the heart [ 173 , 174 ]. Ferritin, critical for iron homeostasis, is also associated with a high risk of arterial hypertension and has utility in predicting the risk of ARDS in COVID-19 patients [ 175 , 176 ]. Ferritin is used to monitor systemic inflammation and may also be considered a marker of a hypercoagulable state [ 177 ].…”