Initial Drug Resistance and Tuberculosis Treatment Outcomes: Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Despite the increasing prevalence of drug-resistant tuberculosis, most low- and middle-income countries use standardized regimens, without assessment of drug susceptibility. PURPOSE: To perform a systematic review and meta-analysis of the effect of initial drug resistance and treatment regimen on tuberculosis treatment outcomes. DATA SOURCES: PubMed, the Cochrane Central Database of Clinical Trials, and EMBASE were searched for studies published in English from 1965 to June 2007. Additional studies were identified from cited references. STUDY SELECTION: Randomized, controlled trials and cohort studies of standardized treatment of previously untreated patients with culture-confirmed pulmonary tuberculosis. Drug-susceptibility testing was done on pretreatment isolates from all patients and from patients with treatment failure or relapse. DATA EXTRACTION: Two authors reviewed the studies for methods, initial drug resistance, treatment regimens, and outcomes. DATA SYNTHESIS: Pooled cumulative incidences were computed with random-effects meta-analyses. Association between risk factors and outcomes were determined by using stratified analyses. The cumulative incidence of acquired drug resistance with initially pan-sensitive strains was 0.8% (95% CI, 0.5% to 1.0%) compared with 6% (CI, 4% to 8%) with initially single drug-resistant strains and 14% (CI, 9% to 20%) with initially polydrug-resistant strains. Failure and relapse were most strongly associated with initial drug resistance. Failure was also associated with shorter duration of rifampin therapy and nonuse of streptomycin, whereas the rate of relapse was higher with shorter duration of rifampin therapy and nonuse of pyrazinamide. LIMITATIONS: Few studies included HIV-infected persons, and treatment outcomes were pooled despite considerable heterogeneity. CONCLUSION: Treatment outcomes were substantially worse in the presence of initial drug resistance, which has important implications in resource-limited settings in which drug resistance is prevalent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.051 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".