The Ligurian Human Immunodeficiency Virus Clinical Network: A Web Tool to Manage Patients With Human Immunodeficiency Virus in Primary Care and Multicenter Clinical Trials
Notice bibliographique
Résumé
BACKGROUND: In recent years, Highly-Active Anti-Retroviral Therapies (HAARTs) have modified the Human Immunodeficiency Virus (HIV) life-cycle and the disease is now considered chronic. Consequently, a longitudinal and complex follow-up is now required for HIV positive patients during their lifetime. Moreover, patients often encounter various complications due to comorbidities, related to the immunodeficiency state and HAARTs' side effects. Thus, HIV positive patients are involved in multicenter clinical trials (MCTs) to improve treatments and discover a preventive vaccine. Therefore, physicians require proper instruments to access comprehensive patient data for managing patients during follow-ups, and tools for data collection and analysis in MCTs. OBJECTIVE: The Ligurian HIV Clinical Network aims to provide physicians with a Web-tool to administrate HIV positive patients' data within primary-care and to reuse the collected clinical information to perform MCTs in Northern Italy. METHODS: The key aspect of the system is a relational database which allows the storage of various types of clinical information (eg, related to HIV, cardiovascular, or hepatic diseases) in multiple formats. The modular design of the database permits a rapid insertion of new parameters without requiring any changes in the database structure. Furthermore, codes from biomedical ontologies controlled vocabularies ("Logical Observation Identifier Names and Codes", and "International Classification of Diseases 9") and ontologies ("Systematized Nomenclature of Medicine Clinical Terms"), units and normality ranges used by all partners participating in the project were collected to achieve a complete semantic interoperability. Accordingly, data can be automatically normalized through the z score formula and physicians can extract and correctly compare information with external statistical tools. Moreover, to respect patients' privacy and legal issues, a local identifier, determined through an HASH cryptography algorithm, is assigned to each patient during the registration process. The database is managed by a user-friendly Web-platform which allows quick access to information during medical examinations and the reusing of the collected data for present and future MCTs. Furthermore, a bidirectional middleware was created in order to import/export information through HL7 messaging. Hence, data can be manually entered by physicians or automatically collected within HL7-compliant Hospital Information systems. RESULTS: Presently, the direct storage of patients' information from the San Paolo Hospital (Savona, Italy), and San Martino and Galliera hospitals in Genoa is in a test phase. Currently, 8 centers of Infectious Diseases (located in Liguria and Piedmont) are participating in the project and almost 400 HIV positive patients have been recorded in the system. Patient data has been used for primary care and research purposes. Currently, there are 4 on-going MCTs and preliminary results have already been presented at International HIV congresses. CONCLUSIONS: The Web-platform allows effective management, sharing and reuse of information within primary care and clinical research. In the future it is planned to share the clinical information from this network with other HL7-compliant workgroups and to extend the platform to other infective diseases (eg, hepatitis).
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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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».