The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Serum Drug Concentrations Predictive of Pulmonary Tuberculosis Outcomes
Open accessAbstract
BACKGROUND: Based on a hollow-fiber system model of tuberculosis, we hypothesize that microbiologic failure and acquired drug resistance are primarily driven by low drug concentrations that result from pharmacokinetic variability. METHODS: Clinical and pharmacokinetic data were prospectively collected from 142 tuberculosis patients in Western Cape, South Africa. Compartmental pharmacokinetic parameters of isoniazid, rifampin, and pyrazinamide were identified for each patient. Patients were then followed for up to 2 years. Classification and regression tree analysis was used to identify and rank clinical predictors of poor long-term outcome such as microbiologic failure or death, or relapse. RESULTS: Drug concentrations and pharmacokinetics varied widely between patients. Poor long-term outcomes were encountered in 35 (25%) patients. The 3 top predictors of poor long-term outcome, by rank of importance, were a pyrazinamide 24-hour area under the concentration-time curve (AUC) ≤ 363 mg·h/L, rifampin AUC ≤ 13 mg·h/L, and isoniazid AUC ≤ 52 mg·h/L. Poor outcomes were encountered in 32/78 patients with the AUC of at least 1 drug below the identified threshold vs 3/64 without (odds ratio = 14.14; 95% confidence interval, 4.08-49.08). Low rifampin and isoniazid peak and AUC concentrations preceded all cases of acquired drug resistance. CONCLUSIONS: Low drug AUCs are predictive of clinical outcomes in tuberculosis patients.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,522
The Fractal Geometry of Nature
Mandelbrot, B. B., & Wheeler, J. A. (1983) · American Journal of Physics · doi:10.1119/1.13295 · Cited by 21,832
(2003) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.167.4.603 · Cited by 1,944
Timing of Initiation of Antiretroviral Drugs during Tuberculosis Therapy
Abdool Karim, S. S., Naidoo, K., Grobler, A., Padayatchi, N., Baxter, C., Gray, A., Gengiah, T., Nair, G., Bamber, S., Singh, A., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa0905848 · Cited by 666
Classification and Regression Trees
(2022) · The R Book · doi:10.1002/9781119634461.ch20 · Cited by 499
Therapeutic Drug Monitoring in the Treatment of Tuberculosis
Peloquin, C. A. (2002) · Drugs · doi:10.2165/00003495-200262150-00001 · Cited by 446
Classification Trees With Unbiased Multiway Splits
Kim, H., & Loh, W.-Y. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753168271 · Cited by 391
Concentration-Dependent Mycobacterium tuberculosis Killing and Prevention of Resistance by Rifampin
Gumbo, T., Louie, A., Deziel, M. R., Liu, W., Parsons, L. M., Salfinger, M., & Drusano, G. L. (2007) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01533-06 · Cited by 345
Self-citationBactericidal and Sterilizing Activities of Antituberculosis Drugs during the First 14 Days
Jindani, A., Doré, C. J., & Mitchison, D. A. (2003) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.200210-1125oc · Cited by 321
Basic Mechanisms of Chemotherapy
Mitchison, D. A. (1979) · Chest · doi:10.1378/chest.76.6.771 · Cited by 301
Cited by
Ellington, M. J., Ekelund, O., Aarestrup, F. M., Canton, R., Doumith, M., Giske, C., Grundman, H., Hasman, H., Holden, M. T. G., Hopkins, K. L., et al. (2017) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2016.11.012 · Cited by 603
Therapeutic Drug Monitoring in the Treatment of Tuberculosis: An Update
Alsultan, A., & Peloquin, C. A. (2014) · Drugs · doi:10.1007/s40265-014-0222-8 · Cited by 444
Horsburgh, C. R., Barry, C. E., & Lange, C. (2015) · New England Journal of Medicine · doi:10.1056/nejmra1413919 · Cited by 323
A Dose-Ranging Trial to Optimize the Dose of Rifampin in the Treatment of Tuberculosis
Boeree, M. J., Diacon, A. H., Dawson, R., Narunsky, K., du Bois, J., Venter, A., Phillips, P. P. J., Gillespie, S. H., McHugh, T. D., Hoelscher, M., et al. (2015) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201407-1264oc · Cited by 309
Aklillu, E., Carrillo, J. A., Makonnen, E., Bertilsson, L., & Djordjevic, N. (2018) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-018-2448-y · Cited by 28
Metadata
- Authors
- Pasipanodya, J. G., McIlleron, H., Burger, A., Wash, P. A., Smith, P., & Gumbo, T.
- Venue
- Journal of Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-07-29
- Volume
- 208
- Issue
- 9
- Pages
- 1464-1473
- ISSN
- 0022-1899 (ISSN-L)
- 1537-6613
- OpenAlex
- W2107834145
- Cited by
- 444
- References
- 32
- FWCI
- 25.80
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Serum Drug Concentrations Predictive of Pulmonary Tuberculosis Outcomes. https://app.cochat.ai/papers/10.1093/infdis/jit352
- The paper
- Pasipanodya, J. G., McIlleron, H., Burger, A., Wash, P. A., Smith, P., & Gumbo, T. (2013). Serum Drug Concentrations Predictive of Pulmonary Tuberculosis Outcomes. Journal of Infectious Diseases. https://doi.org/10.1093/infdis/jit352
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.