| Literature DB >> 35507601 |
Xiaoxu Zhang1, Yan Zhang1, Wenjun Xia1, Yajie Liu2, Hongkai Mao1, Liangliang Bao1, MingQin Cao1.
Abstract
BACKGROUND: Vitamin D is related to human immunity, so we used Bayesian network model to analyze and infer the relationship between vitamin D level and the acid-fast bacilli (AFB) smear-positive after two months treatment among pulmonary tuberculosis (TB) patients.Entities:
Mesh:
Substances:
Year: 2022 PMID: 35507601 PMCID: PMC9067663 DOI: 10.1371/journal.pone.0267917
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.752
Fig 1Flow chart of implementation process.
Comparison of second AFB smear-positive status among different TB patients.
| Groups | Number | second AFB smear-test | χ2 |
| ||
|---|---|---|---|---|---|---|
| Positive | Incidence (%) | |||||
| gender | men | 433 | 29 | 6.7 | 2.378 | 0.123 |
| women | 298 | 12 | 4.0 | |||
| Age groups | ≤30 | 213 | 9 | 4.2 | 1.563 | 0.458 |
| 31~59 | 304 | 17 | 5.6 | |||
| ≥60 | 214 | 15 | 7.0 | |||
| Nation | Han | 511 | 28 | 5.5 | 0.054 | 0.817 |
| Minority | 220 | 13 | 5.9 | |||
| District | Suburbs | 230 | 10 | 4.3 | 1.008 | 0.315 |
| Centre | 501 | 31 | 6.2 | |||
| Address | Floating population | 186 | 15 | 8.1 | 2.842 | 0.092 |
| Local population | 545 | 26 | 4.8 | |||
| Patient source | track | 390 | 17 | 4.4 | 6.290 | 0.043 |
| Referral | 263 | 22 | 8.4 | |||
| Other | 78 | 2 | 2.6 | |||
| Treatment classification | Initial treatment | 685 | 33 | 4.8 | 10.607 | 0.010 |
| Retreatment | 46 | 8 | 17.4 | |||
| Diagnostic classification | Secondary | 669 | 41 | 6.1 | 2.951 | 0.086 |
| Non secondary | 62 | 0 | 0 | |||
| Baseline AFB smear-test | Negative | 475 | 3 | 0.6 | 63.466 | <0.001 |
| Positive | 256 | 38 | 14.8 | |||
| Cavity | No | 590 | 19 | 3.2 | 32.959 | <0.001 |
| Yes | 141 | 22 | 15.6 | |||
| Treatment management | Intensive supervision | 426 | 2 | 0.5 | 60.050 | <0.001 |
| Full supervision | 224 | 34 | 15.2 | |||
| Full management | 81 | 5 | 6.2 | |||
Patient source: TB patients are classified according to different sources; Track: Under the guidance of CDC, the primary medical institutions should follow up the TB patients who have not visited TB designated institutions or who have close contacts with suspicious symptoms, so that they can go to TB designated medical institutions for treatment; Referral: Refers to the suspected or confirmed TB patients at all levels of medical and health institutions transferred to TB designated medical institutions; Other: Including physical examination and who was close contact inspection. Treatment management: The management of TB patients in China is mainly based on non-hospitalization, including full supervision, intensive supervision, full management and self-medication; Intensive supervision: In the intensive period of treatment, patients were treated with direct supervision chemotherapy every time, and the full management was adopted in the continuous period; Full supervision: In the whole process of tuberculosis treatment, each time the patient takes anti-tuberculous drugs, they are under the direct supervision of medical staff or trained volunteer supervisors; Full management: In the whole process of patient treatment, urge patients to complete the whole course of treatment through various ways and channels.
Assignment table of dependent variable and independent variables.
| Variable type | Variables | Assignment |
|---|---|---|
| Dependent variable | Second AFB smear-test | Negative = 0 Positive = 1 |
| Independent variable | Patient source | Track = (0,0) Referral = (1,0) Other = (0,1) |
| Treatment classification | Initial treatment = 0 retreatment = 1 | |
| Baseline AFB smear-test | Negative = 0 Positive = 1 | |
| Cavity | No = 0 Yes = 1 | |
| Treatment management | Intensive supervision = (0,0) | |
| Full supervision = (1,0) | ||
| Full management = (0,1) |
Fig 2The result of logistic regression.
Second AFB smear-test results of TB patients with different vitamin D levels.
| Vitamin D levels | Second AFB smear-test | χ2 | P | |
|---|---|---|---|---|
| Positive | Incidence (%) | |||
| Sufficient | 24 | 7.6 | 4.148 | 0.042 |
| Deficiency | 17 | 4.5 | ||
The definition and assignment table of Bayesian network nodes.
| Variables | node | Assignment |
|---|---|---|
| Baseline AFB smear-test | Baseline | Negative = 0 Positive = 1 |
| Cavitary | Cavity | No = 0 Yes = 1 |
| Treatment management | Management | Intensive supervision = 0 |
| Full supervision = 1 | ||
| Full management = 2 | ||
| Vitamin D levels | VitD | Sufficient = 0 Deficiency = 1 |
| Second AFB smear-test | Second | Negative = 0 Positive = 1 |
Fig 3Bayesian network model for second AFB smear-positive in TB patients.
A: Initial network structure. B: Bayesian network structure after adding constraints according to prior knowledge. C: Trimmed Bayesian network structure.
Edges and edge type probabilities of Bayesian network node.
| Node 1 | Interaction | Node 2 | Ensemnle | No dege |
|---|---|---|---|---|
| Baseline |
| Cavity | 1.0000 | 0.0000 |
| Baseline |
| Management | 1.0000 | 0.0000 |
| Baseline |
| VitD | 0.0340 | 0.9660 |
| Baseline |
| Second | 0.8791 | 0.1209 |
| Cavity |
| Management | 0.7852 | 0.2148 |
| Cavity |
| VitD | 0.1568 | 0.8432 |
| Cavity |
| Second | 0.8252 | 0.1748 |
| Management |
| Second | 0.8302 | 0.1698 |
| VitD |
| Second | 0.0709 | 0.9291 |
Fig 4Conditional probability table of second AFB smear-positive.