Profiling non-tuberculous mycobacteria in an Asian setting: characteristics and clinical outcomes of hospitalized patients in Singapore
Bibliographic record
Abstract
BACKGROUND: Non-tuberculous mycobacteria (NTM) infection is an increasing problem worldwide. The epidemiology of NTM in most Asian countries is unknown. This study investigated the epidemiology, and clinical profile of inpatients in whom NTM was isolated from various anatomical sites in a Singaporean population attending a major tertiary referral centre. METHODS: Demographic profile, clinical data, and characteristics of patients hospitalized with NTM isolates at a major tertiary hospital over two-year period were prospectively assessed (2011-2012). Data collected included patient demographics, ethnicity, smoking status, co-morbidities, NTM species, intensive care unit (ICU) treatment, and mortality. RESULTS: A total of 485 patients (62.1% male) with 560 hospital admissions were analysed. The median patient age was 70 years. Thirteen different NTM species were isolated from this cohort. Mycobacterium abscessus (M. abscessus) (38.4%) was most frequently isolated followed by Mycobacterium fortuitum (M. fortuitum) (16.6%), Mycobacterium avium complex (MAC) (16.3%), Mycobacterium kansasii (M. kansasii) (15.4%), and Mycobacterium gordonae (M. gordonae) (6.8%). Most (91%) NTM was isolated from the respiratory tract. The three most common non-pulmonary sites were; blood (2.7%), skin wounds and abscesses (2.1%), and gastric aspirates (1.1%). A third (34.4%) of the study population had prior pulmonary tuberculosis (PTB). There was a significant association between isolated NTM species, and patient age (p = 0.0002). Eleven (2.2%) patients received intensive care unit (ICU) treatment during the study period and all cause mortality within 1 year of the study was 16.9% (n = 82). Of these, 72 (87.8%) patients died of pulmonary causes. CONCLUSIONS: The profile of NTM species in Singapore is unique. M. abscessus is the commonest NTM isolated, with a higher prevalence in males, and in the elderly. High NTM prevalence is associated with high rates of prior PTB in our cohort.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".