Diagnosis of tuberculosis in dialysis and kidney transplant patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In patients with chronic kidney disease the risk of developing Tuberculosis is increased, while the presentation is often atypical making the diagnosis more difficult. The aim of this study is to describe the presentation of Tuberculosis in dialysis and kidney transplant patients, including the range of diagnostic approaches and the utility of different sample types. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: In this retrospective study, case records of dialysis and kidney transplant patients were reviewed, including all those treated for Tuberculosis between January 2009 and December 2020. RESULTS: Over 12 years, there were 143 cases of Tuberculosis in 141 patients (aged 17-86, 50.4% male). Tuberculosis was most common in Asian patients (64%) and those receiving hemodialysis (82%), particularly during the first year after dialysis initiation (54% of dialysis cases). Non-pleural/pulmonary disease accounted 40% of cases, and non-organ-specific presenting features were prominent including fever, lymphadenopathy, and weight loss. The diagnosis was confirmed microbiologically or histologically in 87 cases (61%), with low sensitivity observed for many types of samples including sputum (18%) and pleural fluid (12%). Higher sensitivity was observed with tissue samples including bronchoscopic lymph node aspiration (75%) and other lymph node sampling (92%). In the 52 cases where drug sensitivities were available, resistance to a first line treatment, most commonly isoniazid, was seen in 12 cases (23%). Furthermore, 1- and 5-year survival from diagnosis were 78% and 61%, respectively. Baseline variables independently associated with poorer survival were age (OR 1.8 per decade, 95% CI 1.4-2.3), weight loss over 10% (OR 1.9, 95% CI 1.0-3.5), and a non-confirmed diagnosis (OR 1.6, 95% CI 1.2-2.1). CONCLUSIONS: Tuberculosis is common in dialysis and kidney transplant patients, particularly during the first year of dialysis. Short-term mortality is high, but the diagnostic sensitivity of many types of samples is low, so that diagnosis is difficult, with treatment often initiated without confirmation. These data highlight the importance of judgment and clinical experience with this complex patient group.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".