Verification of the Reliability of an Automated Urine Test Strip Colorimetric Program Using Colorimetric Analysis: Survey Study
Notice bibliographique
Résumé
Background: One method for noninvasive and simple urinary microalbumin testing is urine test strips. However, when visually assessing urine test strips, accurate assessment may be difficult due to environmental influences-such as lighting color and intensity-and the physical and psychological influences of the assessor. These complicate the formation of an objective assessment. objectives: This study developed an "automated urine test strip colorimetric program" (hereinafter referred to as "this program") to objectively assess urine test strips. Using this program may allow urine tests to be conducted at home. In this study, urine samples from hospitalized or outpatient patients were randomly obtained, and the reliability of this program was verified by comparing the agreement rate between this program and an automatic urine analyzer (US-3500 [Eiken Chemical Co, Ltd] and LABOSPECT 006 [Hitachi High-Tech Co, Ltd]). Furthermore, the sensitivity and specificity of the urine albumin test were investigated, and its applicability to screening for microalbuminuria was verified. Methods: A urine test strip was placed in a photography box with constant light intensity and color temperature conditions. The image taken with a smartphone camera on top of the photography box was judged by this program. This program used Accelerated KAZE to perform image-matching processing to reduce the effect of misalignment during photography. It also calculated and judged the item with the smallest color difference between the color chart and the urine test strip using the CIEDE2000 color difference formula. The agreement rate of the results of this program was investigated using the results of an automatic urine analyzer as the gold standard. Results: Compared with the judgments of an automatic urine analyzer, the average agreement rate for 12 items (protein, glucose, urobilinogen, bilirubin, ketone bodies, specific gravity, occult blood, pH, white blood cells, nitrite, creatinine, and albumin) was 78.6%. Furthermore, the average agreement rate of the 12 items within ±1 rank was 95.4%. The results showed a sensitivity of 100% and a specificity of 58.6% in determining albumin in urine, which is important for determining the stage of diabetic nephropathy. Finally, the area under the curve (0.907) derived from the receiver operating characteristic curve was satisfactory. Conclusions: The program developed by the authors can determine urine test strips without requiring calibration in a certain shooting environment. If this program can be used at home to perform urinary microalbumin tests, the early detection and treatment of diabetic nephropathy may prevent the condition from becoming severe.
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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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,022 |
| 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 ».