Qu'est-ce qu'un diagnostic médical ?

C'est l'identification d'une maladie ou d'un état de santé à partir des symptômes et examens.

Comment établir un diagnostic différentiel ?

Il s'agit de comparer les symptômes pour exclure d'autres maladies possibles.

Quel rôle jouent les antécédents médicaux dans le diagnostic ?

Ils aident à comprendre le contexte de la maladie et à orienter les examens.

Pourquoi les examens complémentaires sont-ils importants ?

Ils fournissent des informations supplémentaires pour confirmer ou infirmer un diagnostic.

Qu'est-ce qu'un diagnostic clinique ?

C'est un diagnostic basé sur l'observation des signes et symptômes du patient.

Comment définir un symptôme ?

C'est une manifestation subjective d'une maladie ressentie par le patient.

Quelle est la différence entre un signe et un symptôme ?

Un signe est observable par le médecin, tandis qu'un symptôme est rapporté par le patient.

Quels sont les symptômes courants d'une infection ?

Fièvre, fatigue, douleur, rougeur et gonflement sont des symptômes fréquents.

Comment évaluer la gravité des symptômes ?

On utilise des échelles de douleur et des critères cliniques pour évaluer la gravité.

Pourquoi est-il important de documenter les symptômes ?

Cela aide à suivre l'évolution de la maladie et à ajuster le traitement.

Qu'est-ce que la prévention en santé ?

C'est l'ensemble des actions visant à éviter l'apparition de maladies.

Quels sont les types de prévention ?

Prévention primaire, secondaire et tertiaire, chacune ayant des objectifs spécifiques.

Comment promouvoir la prévention dans la population ?

Par des campagnes d'éducation, des dépistages et des vaccinations.

Pourquoi la vaccination est-elle importante ?

Elle protège contre des maladies infectieuses et contribue à l'immunité collective.

Quel rôle joue l'alimentation dans la prévention ?

Une alimentation équilibrée réduit le risque de maladies chroniques et améliore la santé.

Qu'est-ce qu'un traitement médical ?

C'est l'ensemble des interventions visant à soulager ou guérir une maladie.

Comment choisir un traitement approprié ?

On évalue l'efficacité, les effets secondaires et les préférences du patient.

Quels sont les types de traitements disponibles ?

Médicaments, chirurgie, thérapies physiques et psychologiques sont des options.

Quelle est l'importance du suivi du traitement ?

Le suivi permet d'évaluer l'efficacité et d'ajuster le traitement si nécessaire.

Qu'est-ce qu'un traitement préventif ?

C'est une intervention visant à prévenir l'apparition d'une maladie.

Qu'est-ce qu'une complication médicale ?

C'est un effet indésirable ou une condition qui survient à la suite d'une maladie.

Comment prévenir les complications ?

Par un suivi régulier, une gestion adéquate des traitements et une éducation du patient.

Quels sont les exemples de complications courantes ?

Infections, saignements, et défaillance d'organes sont des complications fréquentes.

Pourquoi est-il crucial de reconnaître les complications ?

Une détection précoce permet d'intervenir rapidement et d'améliorer le pronostic.

Quel impact les complications ont-elles sur le traitement ?

Elles peuvent prolonger le traitement, nécessiter des interventions supplémentaires.

Qu'est-ce qu'un facteur de risque ?

C'est une caractéristique ou un comportement qui augmente la probabilité d'une maladie.

Comment identifier les facteurs de risque d'une maladie ?

Par des études épidémiologiques et l'analyse des antécédents médicaux.

Quels sont les facteurs de risque modifiables ?

Alimentation, activité physique, tabagisme et consommation d'alcool peuvent être modifiés.

Pourquoi est-il important de connaître les facteurs de risque ?

Cela permet de mettre en place des stratégies de prévention ciblées et efficaces.

Comment les facteurs de risque influencent-ils la santé ?

Ils augmentent la probabilité de développer des maladies et peuvent affecter le pronostic.

Enseignement médical premier cycle - Informations médicales vérifiées

Excellent agreement of Norwegian trauma registry data compared to corresponding data in electronic patient records.

26 Sep 2023

DOI: 10.1186/s13049-023-01118-5 PMID: 37752614

The Norwegian Trauma Registry (NTR) is designed to monitor and improve the quality and outcome of trauma care delivered by Norwegian trauma hospitals. Patient care is evaluated through specific qualit... We validated 49 of the 118 variables registered in the NTR by comparing those with the corresponding ones in electronic patient records for 180 patients with a trauma diagnosis admitted in 2019 at eig... Almost perfect agreement (AC... All tested variables in the Norwegian Trauma Registry displayed excellent agreement with the corresponding variables in electronic patient records. Variables in the registry that showed missing data n...

Humans Electronic Health Records Routinely Collected Health Data Registries Data Accuracy +2 autres

Assessment of immunization data management practices in Cameroon: unveiling potential barriers to immunization data quality.

27 Sep 2023

DOI: 10.1186/s12913-023-09965-9 PMID: 37759205

One crucial obstacle to attaining universal immunization coverage in Sub-Saharan Africa is the paucity of timely and high-quality data. This challenge, in part, stems from the fact that many frontline... A descriptive cross-sectional study was conducted, involving health districts and health facilities in all 10 regions in Cameroon selected by a multi-stage sampling scheme. Structured questionnaires a... A total of 265 facilities in 68 health districts were assessed. There was limited availability of some data recording tools like vaccination cards (43%), maintenance registers (8%), and stock cards (5... Our findings unveil important gaps in data collection practices at the facility level that could adversely affect Cameroon's immunization data quality. It highlights the urgent need for systematic cap...

Child Humans Data Management Data Accuracy Cameroon +6 autres

Mdwgan-gp: data augmentation for gene expression data based on multiple discriminator WGAN-GP.

13 Nov 2023

DOI: 10.1186/s12859-023-05558-9 PMID: 37957576

Although gene expression data play significant roles in biological and medical studies, their applications are hampered due to the difficulty and high expenses of gathering them through biological exp... In this study, an improved data augmentation approach MDWGAN-GP, a generative adversarial network model with multiple discriminators, is proposed. In addition, a novel method is devised for enriching ... The experimental results have demonstrated that compared with other state-of-the-art methods, the MDWGAN-GP method can produce higher quality generated gene expression data in most cases....

Data Accuracy Gene Expression

Thirty-three myths and misconceptions about population data: from data capture and processing to linkage.

2023

DOI: 10.23889/ijpds.v8i1.2115 PMID: 37636835

Databases covering all individuals of a population are increasingly used for research and decision-making. The massive size of such databases is often mistaken as a guarantee for valid inferences. How...

Humans Data Accuracy Data Collection Databases, Factual Information Storage and Retrieval +2 autres

Accuracy of ethnicity records at primary and secondary healthcare services in Waikato region, Aotearoa New Zealand.

06 Sep 2024

DOI: 10.26635/6965.6445 PMID: 39236329

Ethnicity is an important variable, and in Aotearoa New Zealand it is used to monitor population health needs, health services outcomes and to allocate resources. However, there is a history of underc... Through individual record linkage, prospective self-reported ethnicity, collected using New Zealand Census and Ministry of Health - Manatū Hauora ethnicity protocol as a "gold standard", was compared ... Māori were undercounted in secondary NHI (32.5%) and primary care (31.3%) datasets compared to self-reported (34.6%). Between 9.5-11% of individuals had a different ethnicity recorded in health datase... Routine health datasets fail to adequately collect ethnicity, particularly for those with multiple ethnicities. Inaccuracies disproportionately affect Māori and urgent efforts are needed to improve co...

Humans New Zealand Primary Health Care Male Female +13 autres

Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering.

2023

DOI: 10.1016/bs.mie.2022.11.002 PMID: 36641205

Key to small-angle scattering (SAS) maturing and becoming a mainstream structural biology technique was the work done by the SAS community to establish standards for data quality, model validation and...

Data Accuracy Models, Molecular Databases, Protein Molecular Biology Scattering, Small Angle +1 autres

Drivers and Barriers to Improved Data Quality and Data-Use Practices: An Interpretative Qualitative Study in Addis Ababa, Ethiopia.

15 09 2022

DOI: 10.9745/GHSP-D-21-00689 PMID: 36109055

An objective of the Information Revolution Roadmap of Ethiopia's Health Sector Transformation Plan was to improve health management information system (HMIS) data quality and data use at the point of ... We conducted an interpretative qualitative study across all 11 health centers in 3 subcities of Addis Ababa, Ethiopia: Yeka, Akaki-Kaliti, and Ledeta. A total of 40 key informant interviews and 6 focu... Our findings indicate that the main drivers of data quality and use at the point of service delivery were the use of the Connected Woreda strategy and its tools, capacity-building activities including... Improvements in quality and use of HMIS data at health facilities are expected to result in delivering better-quality health services to the community as data enable health workers to identify gaps in...

Data Accuracy Ethiopia Focus Groups Health Facilities Humans +1 autres

Data quality evaluation in wearable monitoring.

10 Dec 2022

DOI: 10.1038/s41598-022-25949-x PMID: 36496546

Wearable recordings of neurophysiological signals captured from the wrist offer enormous potential for seizure monitoring. Yet, data quality remains one of the most challenging factors that impact dat...

Humans Wearable Electronic Devices Data Accuracy Reproducibility of Results Seizures +1 autres

Clinical annotations for prostate cancer research: Defining data elements, creating a reproducible analytical pipeline, and assessing data quality.

08 2022

DOI: 10.1002/pros.24363 PMID: 35538298

Routine clinical data from clinical charts are indispensable for retrospective and prospective observational studies and clinical trials. Their reproducibility is often not assessed. We developed a pr... For men with prostate cancer who had clinical-grade paired tumor-normal sequencing at a comprehensive cancer center, we performed team-based retrospective data collection from the electronic medical r... Data elements on demographics, diagnosis and staging, disease state at the time of procuring a genomically characterized sample, and clinical outcomes were piloted and then abstracted for 2261 patient... With a prostate cancer-specific data dictionary and quality control measures, manual clinical annotations by a multidisciplinary team can be scalable and reproducible. The data dictionary and the R pa...

Data Accuracy Electronic Health Records Humans Male Prostatic Neoplasms +2 autres

Validation of Multi-State EHR-Based Network for Disease Surveillance (MENDS) Data and Implications for Improving Data Quality and Representativeness.

13 Jun 2024

DOI: 10.5888/pcd21.230409 PMID: 38870031

Surveillance modernization efforts emphasize the potential use of electronic health record (EHR) data to inform public health surveillance and prevention. However, EHR data streams vary widely in thei... We developed a validation process for the Multi-State EHR-Based Network for Disease Surveillance (MENDS) pilot project to identify and resolve data quality issues that could affect chronic disease pre... We identified gaps in the EHR databases of data contributors and in the processes to extract, map, integrate, and analyze their EHR data. Examples of source-data problems included missing data on race... Validation protocols identified critical errors in both EHR source data and in the processes used to transform these data for analysis. Our experience highlights the value and importance of data valid...

Electronic Health Records Humans Data Accuracy Pilot Projects Population Surveillance +3 autres

Enseignement médical premier cycle : Questions médicales fréquentes

Termes MeSH sélectionnés :

Sources (10000 au total)