Abstract
Background
COVID-19 is spreading rapidly all over the world, the patients’ symptoms can be easily confused with other pneumonia types. Therefore, it is valuable to seek a laboratory differential diagnostic protocol of COVID-19 and other pneumonia types on admission, and to compare the dynamic changes in laboratory indicators during follow-up.
Methods
A total of 143 COVID-19, 143 bacterial pneumonia and 145 conventional viral pneumonia patients were included. The model group consisted of 140 COVID-19, 80 bacterial pneumonia and 60 conventional viral pneumonia patients, who were age and sex matched. We established a differential diagnostic model based on the laboratory results of the model group on admission via a nomogram, which was validated in an external validation group. We also compared the 400-day dynamic changes of the laboratory indicators among groups.
Results
LASSO regression and multivariate logistic regression showed that eosinophils (Eos), total protein (TP), prealbumin (PA), potassium (K), high-density lipoprotein cholesterol (HDLC), and low-density lipoprotein cholesterol (LDLC) could differentiate COVID-19 from other pneumonia types. The C-index of the nomogram model was 0.922. Applying the nomogram to the external validation group showed an area under the curve (AUC) of 0.902. The 400-day change trends of the laboratory indexes varied among subgroups divided by sex, age, oxygenation index (OI), and pathogen.
Conclusion
The laboratory model was highly accurate at providing a new method to identify COVID-19 in pneumonia patients. The 400-day dynamic changes in laboratory indicators revealed that the recovery time of COVID-19 patients was not longer than that of other pneumonia types.
【저자키워드】 COVID-19, Viral pneumonia, Follow-up, bacterial pneumonia, differential diagnosis, 【초록키워드】 Pneumonia, High-density lipoprotein cholesterol, diagnostic, Sex, Symptom, eosinophil, Laboratory, Protein, pathogen, Patient, age, Potassium, change, Admission, patients, Bacterial, COVID-19 patient, external validation, AUC, subgroup, Low-Density Lipoprotein cholesterol, C-index, multivariate logistic regression, oxygenation index, diagnostic protocol, Result, identify, the patient, changes in, groups, age and sex, Applying, laboratory result, 【제목키워드】 change,