Investigation of sources of potential bias in laboratory surveillance for anti-microbial resistance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: There are a number of biases that may influence the validity of laboratory-based surveillance for antimicrobial resistance. Our objective was to evaluate the potential magnitude of bias in reporting of etiologic agents and their resistance rates associated with inclusion of multiple patient samples and non-random timing and location of sampling. METHODS: All urine cultures submitted to a regional laboratory in the Calgary Health Region during 2004 and 2005 were studied. Comparisons were then made using either the overall cohort or different subgroups compared with the "reference" or gold standard population where only the first isolate per patient per year per species was included. RESULTS: Overall 56,897 organisms were cultured at > or =104 cfu/mL from 53,548 samples from 35,890 patients; 39,835 organisms were included in the reference cohort. Escherichia coli was reported in 37,246 (65.5%) of overall cohort and 28,257 (70.9%) of the reference cohort. Therefore, the overall cohort resulted in a relative underestimation of the importance of E. coli as the principal cause of urinary tract infections by 8%. Similarly, reported rates of resistance to antimicrobial agents most notably ciprofloxacin [6,480/52,544 (12.3%) vs. 2,647/37,086 (7.1%)], gentamicin [2,991/48,070 (6.2%) vs. 1,567/34,608 (4.5%)], and ceftriaxone [1,737/44,922 (3.9%) vs. 889/32,745 (2.7%)] were higher in the overall than in the reference cohorts. There were large differences in both the distribution of organisms and rates of resistance associated with sampling during different times of the day, week, and year as well as from acute care hospitals and outpatient clinics (P< or =0.001). CONCLUSIONS: Reports from laboratory-based surveillance studies may be biased depending on the population studied and method of sampling employed. Care must be taken in interpreting results of surveillance studies that do not protect from these major sources of bias.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it