Table 3.

Effectiveness of Different Sets of Home-Collected Data in Decision Support Systems Classifying Asthma Exacerbations Measured Using AUC

Parameter or Set of Parameters Used for Classifier DevelopmentAUC, % (95% CI)
Children Aged 0-5 yChildren Aged 6-17 yAdults
Wheezes83.8 (82.3-85.4)79.5 (77.2-81.8)71.3 (67.3-75.3)
Rhonchi77.0 (75.0-79.0)81.3 (79.0-83.5)75.4 (72.6-78.3)
Fine crackles71.9 (69.7-74.2)77.3 (74.9-79.7)68.3 (64.2-72.5)
Coarse crackles69.7 (67.3-72.0)79.1 (75.1-83.2)61.9 (55.2-68.6)
Heart rate61.1 (58.3-63.9)62.8 (60.0-65.6)65.1 (56.9-73.2)
Respiratory rate61.7 (57.5-65.9)67.6 (64.1-71.0)61.3 (55.7-66.8)
Inspiration-to-expiration ratio59.9 (57.6-62.2)64.6 (62.0-67.2)62.1 (57.4-66.8)
All parameters provided by AI-aided stethoscope93.0 (92.1-93.9)92.4 (91.1-93.7)81.0 (75.1-86.8)
Symptoms (survey)72.0 (70.1-73.9)78.5 (76.8-80.3)92.0 (89.4-94.6)
Peripheral capillary oxygen saturation66.6 (62.6-70.7)68.1 (65.0-71.1)71.5 (66.5-76.5)
Peak expiratory flown/aa62.5 (57.2-67.7)67.8 (58.9-76.8)
All parameters93.2 (92.1-94.4)92.4 (90.9-93.9)93.7 (92.1-95.3)
  • AI = artificial intelligence; AUC = area under the receiver operating characteristic curve; n/a = not applicable.

  • a Acquiring reliable data for younger children poses substantial challenges.1