Comparison of Delay in Tuberculosis Diagnosis Between Migrants and Local Residents in an Eastern County of China: An Analysis of the Electronic Data Between 2015 and 2019
Bibliographic record
Abstract
Introduction: China continues to rank among one of the countries with the highest number of tuberculosis (TB) cases globally. Migrants are a particularly at-risk subgroup for TB and pose a challenge for case management in contemporary China. The early diagnosis and treatment of patients with TB are pivotal for effective TB control. This study investigates the delay in the TB diagnosis of migrants as compared with residents, to provide an evidence base for improved case detection and the better management of migrant patients with TB. Materials and Methods: The data was collected from the Tuberculosis Information Management System (TBIMS) (2015–2019) in an eastern county of China. The total diagnostic delay, consisting of patient delay and health system delay, is defined as the interval between the onset of TB symptoms and the confirmation of TB diagnosis in the designated TB hospital. The comparison of the delay in the TB diagnosis between migrants and residents was conducted using a Mann-Whitney U -test and chi-square test. The difference in the delay curves between these two groups was examined using a log-rank test. Results: Of 2,487 patients with TB, 539 (22%) were migrants. The migrants tended to be younger, presented with less severe conditions, received an initial diagnosis at prefectural and above-level hospitals. Compared with the local patients with TB, the migrant patients with TB had a longer median total diagnostic delay (30 vs. 9, P = 0.000) and a higher proportion of patients with this delay >28 days (52 vs. 13%, P = 0.000). Similarly, the migrant patients with TB also had a longer median patient delay (13 vs. 9, P = 0.000) and a higher proportion of patients with this delay >14 days (47 vs. 30%, P = 0.000), longer median health system delay (9 vs. 0, P = 0.000), and a higher proportion of patients with this delay >14 days (42 vs. 0.5%, P = 0.000) than the local patients with TB. The survival curves of delay showed that the longer the time interval was, the more likely the migrant patients with TB were to be diagnosed ( P < 0.05). Conclusions: Diagnosis is significantly delayed among migrant patients with TB. Our study highlights the importance of early screening and diagnosis for TB especially among migrants, to improve access and ensure better management for all patients with TB.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".