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. 2020 Aug;70(4):313–327. doi: 10.30802/AALAS-CM-19-000090

Table 2.

Retrospective performance evaluation: performance of breathing rate alerting algorithm according to study (n = 9)

Type of study or model n Alerts for subject with health event (TP) Alerts for subject with no health event (FP) Positive predictive value Unalerted subjects (FN) Accuracy (%) Frequency of alerts (% total subject days)
Respiratory 17 20 0 100 0 100 6.6
 (bleomycin induction)
Phenotyping (aging) 24 0 2 0 0 99.7 0.3
Kidney disease 20 1 5 16.7 1 99.0 1.0
 (nephrectomy induction)
Aging (C57BL/6J) 117 2 10 16.7 2 99.7 0.3
Aging (4-way cross) 27 0 2 0 1 99.6 0.2
Aging (C57BL/6J) 39 0 37 0 3 96.7 3.0
Phenotyping (metabolic) 1 0 0 na 0 100 0
Phenotyping (CNS) 32 0 0 na 0 100 0
Oncology (ES2 cell induction) 54 15 0 100 2 99.8 1.5
Summary (total no. of alerts [%]) 38 of 94 (40.4%) 56 of 94 (59.6%)

FN, false negative; FP, false positive; TP, true positive

A health event was defined by any of the following and was documented through clinical observations at the time of study execution: 1) early endpoint (i.e., animal found dead or at humane endpoint), 2) adverse response to an invasive procedure, or 3) expected signs of disease induction.