A-345 Evaluating the Clinical Utility of Urine hCG testing in Community Laboratory Service
Bibliographic record
Abstract
Abstract Background Accurate and sensitive pregnancy detection is needed to identify patients that require timely access to prenatal care and to ensure medications or treatments that may be harmful to the pregnant patient and/or their fetus are avoided. Human chorionic gonadotropin (hCG), detectable in urine and blood, is a reliable biomarker of pregnancy due to its rapid rise post-implantation. Qualitative urine hCG testing is non-invasive but has drawbacks, such as lower analytical sensitivity and the need for manual processing that can lead to patient misidentification. Conversely, quantitative serum hCG offers higher analytical sensitivity, can be fully automated, detects conditions such as ectopic and molar pregnancies via serial measurements, and is commonly performed on the primary specimen preventing aliquoting errors. Despite these benefits, the invasive nature of blood collection may deter some patients from serum hCG testing. In our health system, both urine and serum hCG testing is offered to community patients, presenting an opportunity to optimize resource use. When a blood specimen with the appropriate container type has been concurrently collected to facilitate other laboratory testing (ie. TSH, serum creatinine), replacing a urine hCG order with a serum hCG order can improve diagnostic accuracy for the patient and provide workflow efficiencies for the laboratory without an additional venipuncture. However, the feasibility of replacing urine hCG with serum hCG testing in a community setting remains unclear. This study assessed urine hCG test utilization and identified opportunities to transition to serum hCG testing without an additional blood collection. Methods Data between April 2022 and March 2024 were extracted from the laboratory information system for urine hCG tests performed at the two large community testing laboratories in Alberta, Canada (catchment population 4.8 million). Urine hCG samples that also had a serum or plasma collected within two hours were identified. For these samples, we assessed the number of urine collections that could be avoided if urine hCG was the sole test ordered on the urine specimen. Cost savings were estimated by comparing the costs of urine and serum hCG testing, factoring in the elimination of the urine collection. Results Between April 2022 and March 2024, 20,090 urine hCG tests were performed at two community reference laboratory sites. 72.0% and 72.9 % of urine hCG tests at Site 1 and Site 2 respectively, had concurrent blood draws with specimen types suitable for serum hCG testing. Urine hCG was the sole urine test ordered in 42.7% and 44.8% of the tests performed at Site 1 and Site 2, respectively. Shifting from urine to serum hCG testing when there is a concurrent draw of an appropriate blood specimen would lead to 19.7% and 20.6% reduction in the cost for hCG testing at Site 1 and Site 2, respectively. Conclusion In a community setting, as many patients have suitable blood specimens collected at the same time the transition from urine to serum hCG testing in these patients can improve diagnostic accuracy and enhance resource utilization.
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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 | 0.017 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".