A-345 Evaluating the Clinical Utility of Urine hCG testing in Community Laboratory Service
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».