Table 4.
Test Statistics per Quartile
| Quartile | Bacterial | Non-bacterial | Likelihood Ratio | Test Purpose | Sensitivity in Quartile | Specificity in Quartile |
|---|---|---|---|---|---|---|
| A: Immunocompetent cohort, bacterial vs nonbacterial | ||||||
| Quartile 1 (lowest) | 2 | 32 | 0.07 | Rule out | 95.3 | |
| Quartile 2 | 4 | 30 | 0.15 | Rule out | 90.1 | |
| Quartile 3 | 12 | 23 | 2.92 | Rule in | 75.3 | |
| Quartile 4 (highest) | 25 | 8 | 4.87 | Rule in | 91.4 | |
| B: Immunocompromised cohort, bacterial vs nonbacterial | ||||||
| Quartile | Bacterial | Non-bacterial | Likelihood Ratio | Test Purpose | Sensitivity in Quartile | Specificity in Quartile |
| Quartile 1 (lowest) | 6 | 28 | 0.17 | Rule out | 90.1 | |
| Quartile 2 | 12 | 21 | 0.27 | Rule out | 81.3 | |
| Quartile 3 | 18 | 15 | 3.33 | Rule in | 78.6 | |
| Quartile 4 (highest) | 28 | 6 | 6.51 | Rule in | 91.4 | |
| C: Immunocompetent cohort, viral vs nonviral | ||||||
| Quartile | Viral | Nonviral | Likelihood Ratio | Test Purpose | Sensitivity in Quartile | Specificity in Quartile |
| Quartile 1 (lowest) | 1 | 33 | 0.03 | Rule out | 98.1 | |
| Quartile 2 | 4 | 30 | 0.12 | Rule out | 92.3 | |
| Quartile 3 | 17 | 17 | 3.32 | Rule in | 79.7 | |
| Quartile 4 (highest) | 30 | 4 | 8.81 | Rule in | 95.2 | |
| D: Immunocompromised cohort, viral vs nonviral | ||||||
| Quartile | Bacterial | Non-bacterial | Likelihood Ratio | Test Purpose | Sensitivity in Quartile | Specificity in Quartile |
| Quartile 1 (lowest) | 1 | 33 | 0.05 | Rule out | 96.4 | |
| Quartile 2 | 1 | 33 | 0.05 | Rule out | 96.4 | |
| Quartile 3 | 9 | 23 | 3.08 | Rule in | 78.3 | |
| Quartile 4 (highest) | 17 | 17 | 2.45 | Rule in | 84.0 | |
Results are presented for the bacterial vs nonbacterial model in the immunocompetent cohort (A) and immunocompromised cohort (B). Results for the viral vs nonviral model are presented for the immunocompetent (C) and immunocompromised (D) cohorts. Since the purpose of the lower quartiles (1 and 2) is to “rule out” the specified condition, only sensitivity is reported. The sensitivity and specificity for each quartile were calculated by omitting the number of subjects in that quartile from the numerator and dividing by all subjects. Higher bands have high specificities to rule in disease while lower bands have high sensitivities to rule out disease. For example, the sensitivity in quartile 2 of Table 8a is calculated by (2 + 12 + 25)/(2 + 4 + 12 + 25) and the specificity in quartile 3 of Table 8a is calculated by (32 + 30 + 8)/(32 + 30 + 23 + 8).