Unraveling the Secrets Behind the Multidrug-Resistant Tuberculosis Treatment Outcome in Chronic Renal Failure Patients Requiring Hemodialysis: A Systematic Review
Bibliographic record
Abstract
Multidrug-resistant/rifampicin-resistant tuberculosis (MDR/RR TB) is a global concern, with 450,000 new cases and 191,000 deaths in 2021. TB and chronic kidney disease (CKD) have been associated since 1974, with suggested explanations such as oxidative stress, malnutrition, dysfunction in vitamin D metabolism, and a compromised cell-mediated immune response. End-stage renal failure patients are more likely to acquire drug resistance due to poor adherence, adverse drug reactions, and inappropriate dose adjustment. We then aim to evaluate the therapeutic outcome of multidrug-resistant TB of the lungs in patients who require hemodialysis in terms of successful treatment (cured and treatment completed) and the associated factors for a favorable outcome. Our secondary goal is to identify unfavorable treatment outcomes (treatment failed, patient died, or patient lost to follow-up) and the underlying associated factors. We conformed to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Guidelines for this systematic review. We included adults (>19 years old) with chronic kidney disease who needed hemodialysis and had microbiologically confirmed multidrug-resistant pulmonary TB, excluding patients who had a renal allograft transplant, were on peritoneal dialysis, had extrapulmonary TB, were children and pregnant patients. We searched PubMed, MEDLINE, PubMed Central, ScienceDirect, Public Library of Science (PLOS), and Google Scholar. Keywords were combined with the Boolean "AND" operator to gather results as well as the medical subject heading (MeSH) search strategy. After screening study articles by reading their titles and abstracts, the following tools were used to assess the risk of bias: the Newcastle-Ottawa scale for observational studies, the Assessment of Multiple Systematic Reviews (AMSTAR) checklist for systematic reviews, and the Joanna Briggs Institute (JBI) assessment tool for case reports. Primary and secondary outcomes were assessed, and a conclusion was made. We gathered 21,570 studies from the databases between 2013 and 2023, with 30,062 total participants. There were eight eligible studies for review. Patients with CKD, particularly those on dialysis, are at increased risk of TB due to a combination of factors that contribute to immunosuppression. TB reactivation is common in chronic renal failure patients. Diagnostic samples such as sputum and pleural fluid had lower sensitivity rates compared to tissue samples, which led to delays in diagnosis and treatment and, most importantly, contributed to drug resistance. All new dialysis patients should undergo interferon-gamma release assay testing. TB-infected patients with severe renal disease (eGFR 30 ml/min) had increased morbidity and mortality; however, the use of directly observed treatment, short-course (DOTS), and renal-dose adjustment of anti-TB medications significantly reduced these risks. Drug-induced hepatitis and cutaneous reactions were common adverse effects of anti-TB medications. A therapeutic drug monitoring guideline is required to reduce these adverse events and even mortality. Additional research is required to assess the safety and efficacy of therapeutic regimens, as well as their outcomes, in this population with multidrug-resistant TB.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".