Evidence map›Paper›PMID 31194793›Full record

ArticlePloS one2019

Sensitivity and specificity of an electronic nose in diagnosing pulmonary tuberculosis among patients with suspected tuberculosis.

Antonia M I Saktiawati, Ymkje Stienstra, Yanri W Subronto, Ning Rintiswati, Sumardi, Jan-Willem Gerritsen, Henny Oord, Onno W Akkerman, Tjip S van der Werf

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Breath Prints for Diagnosing Asthma in Children.Journal of clinical medicine · 2023
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Diagnosing Tuberculosis: What Do New Technologies Allow Us to (Not) Do?Respiration; international review of thoracic diseases · 2022
    Review
  11. Article
  12. Review
  13. Article
  14. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Antonia M I SaktiawatiDepartment of Internal Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.ORCID 0000-0001-5896-0846
Ymkje StienstraUniversity of Groningen, University Medical Center Groningen, Department of Internal Medicine-Infectious Diseases, Groningen, the Netherlands.
Yanri W SubrontoDepartment of Internal Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Ning RintiswatiCenter for Tropical Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia.
SumardiDepartment of Internal Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Jan-Willem GerritseneNose B.V. (The eNose Company), Zutphen, The Netherlands.
Henny OordeNose B.V. (The eNose Company), Zutphen, The Netherlands.
Onno W AkkermanUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases and Tuberculosis, Groningen, the Netherlands.
Tjip S van der WerfUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases and Tuberculosis, Groningen, the Netherlands.ORCID 0000-0002-4824-1642

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the potency of a hand-held point-of-care electronic-nose to diagnose pulmonary tuberculosis (PTB) among those suspected of PTB.

methodsSetting: Lung clinics and Dr. Sardjito Hospital, Yogyakarta, Indonesia. Participants: patients with suspected PTB and healthy controls. Sampling: 5 minutes exhaled breath. Sputum-smear-microscopy, culture, chest-radiography, and follow-up for 1.5-2.5 years, were used to classify patients with suspected PTB as active PTB, probably active PTB, probably no PTB, and no PTB. After building a breath model based on active PTB, no PTB, and healthy controls (Calibration phase), we validated the model in all patients with suspected PTB (Validation phase). In each variable (sex, age, Body Mass Index, co-morbidities, smoking status, consumption of alcohol, use of antibiotics, flu symptoms, stress, food and drink intake), one stratum's Receiver Operating Characteristic (ROC)-curve indicating sensitivity and specificity of the breath test was compared with another stratum's ROC-curve. Differences between Area-under-the-Curve between strata (p<0.05) indicated an association between the variable and sensitivity-specificity of the breath test. Statistical analysis was performed using STATA/SE 15.

resultsOf 400 enrolled participants, 73 were excluded due to extra-pulmonary TB, incomplete data, previous TB, and cancer. Calibration phase involved 182 subjects, and the result was validated in 287 subjects. Sensitivity was 85% (95%CI: 75-92%) and 78% (95%CI: 70-85%), specificity was 55% (95%CI: 44-65%) and 42% (95%CI: 34-50%), in calibration and validation phases, respectively. Test sensitivity and specificity were lower in men.

conclusionThe electronic-nose showed modest sensitivity and low specificity among patients with suspected PTB. To improve the sensitivity, a larger calibration group needs to be involved. With its portable form, it could be used for TB screening in remote rural areas and health care settings.

Indexed as

Electronic NoseAdolescentAdultAgedBreath TestsCase-Control StudiesFemaleHumansIndonesiaMaleMiddle AgedPoint-of-Care SystemsROC CurveSensitivity and SpecificityTuberculosis, PulmonaryYoung Adult

Identifiers

PMID31194793
PMCPMC6563983

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.