Prediction model for prolonged fever in patients with Mycoplasma pneumoniae pneumonia: a retrospective study of 716 pediatric patients

Table 6 Prediction of RMPP-5 (fever > 120 h) in the test cohort

Prediction method	Used variables	p-value	AUC area (95% CI)	Sensitivity (%)	Specificity (%)	PPV (Precision) (%)	NPV (%)	Overall accuracy (%)	Youden Index
Conventional logistic model	ALC, CRP, LDH	0.251	0.565 (0.447, 0.682)	12.9	100.0	100.0	87.1	87.4	0.129
Conventional logistic model	Radiologic grouping	0.181	0.575 (0.457, 0.693)	16.1	98.9	71.4	87.5	87.0	0.150
Conventional logistic model	ALC, CRP, LDH, Radiologic grouping	0.181	0.575 (0.457, 0.693)	16.1	98.9	71.4	87.5	87.0	0.150
Conventional logistic model	Fever profiles*	0.010	0.645 (0.525, 0.765)	32.3	96.7	62.5	89.4	87.4	0.290
Conventional logistic model	Fever profiles*, Radiologic grouping	0.019	0.632 (0.512, 0.751)	29.0	97.3	64.3	89.1	87.4	0.263
Deep neural network	12 sequential fever data	< 0.001	0.803 (0.699, 0.908)	64.5	96.2	74.1	94.1	91.6	0.607

RMPP-5 Refractory Mycoplasma pneumoniae pneumonia with fever for ≥ 120 h, AUC Area under the curve, ALC Absolute lymphocyte count, CRP C-reactive protein, LDH Lactate dehydrogenase, PPV Positive predictive value, NPV Negative predictive value
^*Fever profiles: highest body temperature, lowest body temperature, frequency of peak fever over 39 °C, frequency of peak fever over 40 °C, and total frequency of peak fever

ISSN: 1471-2466