03 April 2023: Clinical Research
Evaluation of a Previously Developed Predictive Model for Infective Endocarditis in 320 Patients Presenting with Fever at 4 Centers in Japan Between January 2018 and December 2020
Shun Yamashita 1ABCDEF* , Masaki Tago 1ACDEF , Yoshinori Tokushima 1BCDF , Yukinori Harada 2ABD , Yudai Suzuki 2ABCD , Yuki Aizawa 2ABCD , Taiju Miyagami 3ABCD , Fumiaki Sano 3ABCD , Yosuke Sasaki 4ABCD , Fumiya Komatsu 4ABCD , Taro Shimizu 2BCD , Toshio Naito 3BCD , Yoshihisa Urita 4BCD , Shu-ichi Yamashita 1BCDEDOI: 10.12659/MSM.939640
Med Sci Monit 2023; 29:e939640
Table 5 Validation of the prediction model with the cut-off points determined in the present study and the original study.
| Statistics for 3 cutoff points | Using cutoff value of the present study | Using cutoff value of the original study |
|---|---|---|
| Cutoff value for scores | −1.75 | −1.68 |
| Probability* | 15 | 16 |
| Sensitivity | 90 | 90 |
| Specificity | 49 | 52 |
| Positive predictive value | 52 | 53 |
| Negative predictive value | 90 | 90 |
| Cutoff value for scores | −0.72 | −1.1 |
| Probability* | 33 | 25 |
| Sensitivity | 86 | 87 |
| Specificity | 64 | 58 |
| Positive predictive value | 59 | 55 |
| Negative predictive value | 88 | 88 |
| Cutoff value for scores | 3.15 | −0.38 |
| Probability* | 96 | 40 |
| Sensitivity | 32 | 82 |
| Specificity | 90 | 67 |
| Positive predictive value | 66 | 60 |
| Negative predictive value | 69 | 87 |
| * Calculated as the probability of a prediction model for IE among patients with undiagnosed fever. | ||