| Literature DB >> 31720000 |
David C Wong1, Samuel D Relton2, Victoria Lane3, Mohamed Ismail2, Victoria Goss4, Jane Bytheway5, Robert M West2, Jim Deuchars6, Jonathan Sutcliffe3.
Abstract
BACKGROUND: There is no definitive method of accurately diagnosing appendicitis before surgery. We evaluated the feasibility of collecting breath samples in children with abdominal pain and gathered preliminary data on the accuracy of breath tests.Entities:
Keywords: Appendicitis; Biomarkers; Breathomics; Child; Exhalation; Volatile organic compounds
Year: 2019 PMID: 31720000 PMCID: PMC6833160 DOI: 10.1186/s40814-019-0502-x
Source DB: PubMed Journal: Pilot Feasibility Stud ISSN: 2055-5784
Fig. 1Example of a single VOC signature with 12 sensors. The time captured includes three phases: a a small warm-up phase (0–2 s), b the sensor readings as the sample is passed through the device (2–13 s) and c a post-sample phase consisting of noise in the sensors whilst the device is reset (17–30 s)
Fig. 2Study enrolment flow diagram
Baseline clinical data
| Non-appendicitis ( | Appendicitis ( | |
|---|---|---|
| Sex | ||
| Female | 21 | 2 |
| Male | 24 | 3 |
| Mean age in years (std) | 10.6 (2.9) | 9.9 (2.9) |
| Operated? | ||
| Yes | 2 | 5 |
| No | 43 | 0 |
| Regular medication | ||
| Yes | 3 | 0 |
| No | 33 | 5 |
| Not recorded | 9 | 0 |
| Antibiotics | ||
| Yes | 2 | 5 |
| No | 43 | 0 |
Fig. 3Negative correlation between age and difficulty of sample collection (y = 7.6–0.03x, Pearson R = − 0.396)
Confusion matrix for the Lasso regression model
| Predicted negative | Predicted positive | |
|---|---|---|
| No appendicitis | 36 | 9 |
| Appendicitis | 1 | 4 |
Classification table for the Lasso regression model
| Precision | Recall | F1 score | Support | |
|---|---|---|---|---|
| No appendicitis | 0.97 | 0.80 | 0.88 | 45 |
| Appendicitis | 0.31 | 0.80 | 0.40 | 5 |
| Weighted average | 0.91 | 0.80 | 0.83 |
Classification table summarising the model that uses VOC signatures to predict appendicitis, with a weighted average of each column based on the number of positive and negative patients.