A-215 Slightly cloudy urine: a benign finding or a call for microscopy?
Notice bibliographique
Résumé
Abstract Background Urinalysis testing for community patients in Alberta, Canada is mainly conducted at two central laboratories using automated analyzers. These analyzers employ reflex rules to trigger automated microscopy when certain criteria are met. Although microscopy is automated, many images still require manual review before confirming results. Therefore, it is essential to establish appropriate reflex rules that maximize the detection of pathological elements while minimizing unnecessary reflex microscopy and workload. Currently, our laboratories reflex urine samples to microscopy when there is abnormal color, non-clear clarity, or positive results for blood, protein, nitrites, or leukocytes. Historically, samples with negative chemical urinalysis findings and slight cloudiness did not trigger reflex microscopy. Introducing this criterion as part of standardization initiatives has increased staff workload by requiring additional image reviews from automated microscopy instruments. This study aimed to assess the frequency of pathological elements detected in samples reflexed based solely on slight cloudiness and the impact of introducing this rule on workload. Methods Urinalysis results from July 2023 to June 2024 were extracted from the laboratory information system (LIS) for both community laboratories. Data analysis was conducted using RStudio (version 4.3.0) to determine the percentage of slightly cloudy samples that had clinically significant microscopy findings, defined as any abnormal findings flagged in the electronic medical record. To assess the added value of reflexing slightly cloudy samples, microscopy findings were compared among three groups: clear, slightly cloudy, and cloudy samples. Microscopy results from 100 clear samples with no flagging criteria were obtained by manually reflexing to automated microscopy. Samples that reflexed to microscopy due to additional flagging criteria beyond the clarity criteria were excluded from the analysis. Results A total of 1,286,865 urinalysis results from Beckman iChem® VELOCITY and iQ® 200 SPRINT analyzers were retrieved from the LIS, with 99,212 samples (7.7%) reflexed to microscopy solely due to a slightly cloudy clarity result. This added approximately 270 microscopy reviews per day, potentially requiring staff review. Of these, 43.4% showed abnormal microscopy findings, compared to 53.1% of cloudy samples and 7.0% of manually reflexed clear samples. In the slightly cloudy group, abnormal findings included red blood cells (>2/HPF) in 8.9% of samples, white blood cells (>5/HPF) in 1.2%, squamous/transitional epithelial cells (>5/HPF) in 13.5%, bacteria (>20/HPF) in 4.0%, yeast in 0.8%, hyaline casts (>2/HPF) in 3.5%, calcium oxalate in 20.8%, and uric acid in 0.6%. Conclusion Reflexing urine samples to microscopy based solely on slightly cloudy clarity is beneficial for detecting abnormal elements. Of these samples, 43.4% had abnormal results which is significantly higher than the 7.0% found in clear samples and only slightly lower than the 53.1% observed in cloudy samples. This demonstrates a significant association between slightly cloudy urine and pathological elements, reinforcing the need for its inclusion in microscopy reflex criteria. Including slightly cloudy samples in reflex criteria improves the detection of abnormal findings, making the added workload worthwhile. This approach enhances the identification of clinically significant elements, supporting better patient care and more effective urinalysis screening.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».