Novel phenotypes of coronavirus disease: a temperature-based trajectory model

Annals of Intensive Care

Table 4 Association between in-hospital death and temperature-trajectory phenotype in logistic regression models

	Model 1		Model 2		Model 3
	Crude OR (95% CI)	p	Multivariable logistic model aOR (95% CI)	p	Multivariable logistic model with 1000 bootstraps, aOR (95% CI)	p
Normothermic	Ref.	–	Ref.	–	Ref.	–
Fever, fast resolvers	2.0 (1.3–3.0)	< 0.001	1.2 (0.7–2.2)	0.377	1.2 (0.6–2.2)	0.364
Gradual fever onset	2.6 (1.7–4.1)	< 0.001	2.1 (1.1–4.0)	0.021	2.1 (1.1–3.9)	0.013
Fever, slow resolvers	3.2 (1.6–3.9)	< 0.001	3.3 (1.4–8.2)	0.005	3.4 (1.3–8.5)	0.007
Age > 65 (years)			3.4 (2.2–5.1)	< 0.001	3.4 (2.1–5.3)	< 0.001
Vasopressor use			3.1 (2.0–4.7)	< 0.001	3.0 (1.9–4.8)	< 0.001
Maximum creatinine level			1.01 (1.00–1.01)	< 0.001	1.01 (1.00–1.01)	0.010
Maximum WBC count			1.2 (1.1–1.3)	< 0.001	1.2 (1.2–1.3)	< 0.001
APACHE II score			1.2 (1.1–1.3)	< 0.001	1.3 (1.1–1.4)	< 0.001

Three logistic models were used to evaluate the association between in-hospital death and four body temperature trajectory groups. Compared to the normothermic group, there was a trend toward increasing risk of in-hospital death from fever, fast resolvers to fever, and slow resolvers. Bootstrapping (1000 resamples) were used for calculating 95% CI in Model 3 and the results remained stable
aOR adjusted odds ratio, APACHE II acute physiology and chronic health evaluation; CI confidence interval, WBC white blood cell