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Abstract
Introduction. Pathological diagnosis (PD) is of great importance for the optimal management of the patient. It is therefore imperative that the analyses of tissue sample comply with all relevant norms and standards. Objective. To identify Non-Conformities (NC) on histological samples received in Pathology Laboratories (PL). Method. A descriptive cross-sectional study was conducted at the PL of the University Teaching Hospital Yaounde (UTHY) and the Yaounde Central Hospital (YCH) from 05 March to 06 April 2018. Using a NC data collection sheet, NC were collected on all histological samples received, focusing on exam form, container, fixative and large samples specificities. Data collected were analysed using Microsoft Excel 2010 software, and proportions of different types of NC stated. Results We received 78 samples, including 8 large samples; 48 (61.54%) samples had at least one NC. These NC was found in 31 (39.74) exam forms, 10 (12.82) containers, 7 (10.45) fixatives and 7 (10.45) large samples. A total of 128 NCs were observed; Ninety-two (71.9%) NCs were related to the exam forms, 17 (12.28%) to the containers, 9 (7%) to the fixative and 10 (7.8%) specific to the large sample. Two (1.6%) NCs were considered major. Conclusion: samples received at the PL of UTHY and YCH have many NCs that could affect the quality of the PD. Improved pre-analysis performance is needed to enhance the quality of the PD through training of health personnels on proper handling of histologic samples in Cameroon.
Introduction. Le diagnostic pathologique (DP) est d'une grande importance pour la prise en charge optimale du patient. Il est donc impératif que les analyses d'échantillons de tissus soient conformes à toutes les normes et standards pertinents. Objectif. Identifier les non-conformités (NC) sur les échantillons histologiques reçus dans les laboratoires de pathologie (PL). Méthodologie. Une étude transversale descriptive a été menée au laboratoire de Pathologie du Centre Hospitalier et Universitaire de Yaoundé (CHUY) et de l'Hôpital Central de Yaoundé (HCY) du 05 mars au 06 avril 2018. A l'aide d'une fiche de collecte de données NC, les NC ont été collectées sur tous les échantillons histologiques reçus, en se concentrant sur la forme de l'examen, le contenant, le fixateur et les spécificités des grands échantillons. Les données recueillies ont été analysées à l'aide du logiciel Microsoft Excel 2010, et les proportions des différents types de NC indiquées. Résultats. Nous avons reçu 78 échantillons, dont 8 échantillons de grande taille ; 48 (61,54%) échantillons présentaient au moins une NC. Ces NC ont été trouvées dans 31 (39,74) formulaires d'examen, 10 (12,82) conteneurs, 7 (10,45) fixateurs et 7 (10,45) grands échantillons. Au total, 128 NC ont été observées ; 92 (71,9 %) NC étaient liées aux formulaires d'examen, 17 (12,28 %) aux conteneurs, 9 (7 %) au fixateur et 10 (7,8 %) spécifiques au grand échantillon. Deux (1,6 %) NC ont été considérées comme majeures. Conclusion : les échantillons reçus au LP du CHUY et de l'HCY présentent de nombreuses NC susceptibles d'affecter la qualité du DP. Il est nécessaire d'améliorer les performances pré-analytiques afin d'améliorer la qualité du DP en formant le personnel de santé à la manipulation correcte des échantillons histologiques.
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References
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- Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021;71(3):209–49.
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References
:00-17:00. ISO 15189:2012 [Internet]. ISO. 2021 [cited 2023 Mar 13]. Available from: https://www.iso.org/fr/standard/56115.html
Types and frequency of preanalytical mistakes in the first Thai ISO 9002:1994 certified clinical laboratory, a 6 – month monitoring | BMC Clinical Pathology | Full Text [Internet]. [cited 2023 Mar 13]. Available from: https://bmcclinpathol.biomedcentral.com/articles/10.1186/1472-6890-1-5
3Carraro P, Plebani M. Errors in a Stat Laboratory: Types and Frequencies 10 Years Later. Clinical Chemistry. 2007 Jul 1;53(7):1338–42.
Hollensead SC, Lockwood WB, Elin RJ. Errors in pathology and laboratory medicine: Consequences and prevention. Journal of Surgical Oncology. 2004;88(3):161–81.
Plebani M, Carraro P. Mistakes in a stat laboratory: types and frequency. Clin Chem. 1997 Aug;43(8 Pt 1):1348–51.
Rao S. Quality Measures in Pre-Analytical Phase of Tissue Processing: Understanding Its Value in Histopathology. JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH [Internet]. 2016 [cited 2023 Mar 13]; Available from: http://www.jcdr.net/article_fulltext.asp?issn=0973-709x&year=2016&volume=10&issue=1&page=EC07&issn=0973-709x&id=7087
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021;71(3):209–49.
Guide sur l’assurance qualité en anatomopathologie - Phases pré-analytique et analytique – Comité consultatif en anatomopathologie.