Catalan
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)

Assessing Accuracy of Clinical Diagnosis and Lesion Location in Acute Neurological Deficits - How Good Are Neurologists?

Només els usuaris registrats poden traduir articles
Inicieu sessió / registreu-vos
L'enllaç es desa al porta-retalls
EstatReclutament
Patrocinadors
University Hospital Inselspital, Berne

Paraules clau

Resum

The emergency setting for acute neurological conditions, such as stroke, is peculiar due to time pressure and limited resources for further diagnostics. Clinical skills are essential for swift and accurate bedside diagnosis and thus are the basis for early and correct treatment. This is especially evident in the context of computed tomography being the standard neuroimaging method world-wide with its limitations for detecting smaller infarcts, strokes in the posterior fossa and reduced sensitivity for stroke mimics, such as epileptic seizures or migraine aura. To date, the accuracy of clinical bedside diagnosis of stroke by neurologists verified by magnetic resonance imaging (MRI) in the emergency setting has not been studied in detail. In order to improve clinical diagnosing and future treatment it is essential to quantify the accuracy of clinical diagnosis of stroke in the emergency setting ("how good are neurologists?") and to assesses whether there are any differences between experienced staff neurologists and junior physicians.

Descripció

Background:

The emergency setting for acute neurological conditions, such as stroke, is peculiar due to time pressure and limited resources for further diagnostics. Clinical skills are essential for swift and accurate bedside diagnosis and thus are the basis for early and correct treatment. This is especially evident in the context of computed tomography being the standard neuroimaging method world-wide with its limitations for detecting smaller infarcts, strokes in the posterior fossa and reduced sensitivity for stroke mimics, such as epileptic seizures or migraine aura. To date, the accuracy of clinical bedside diagnosis of stroke by neurologists verified by magnetic resonance imaging (MRI) in the emergency setting has not been studied in detail. Management of acute stroke patients is a main interest of the neurovascular research group at Inselspital Bern. For example, the investigators analysed the prediction of large vessel occlusion in acute stroke patients by clinical examination and found a significant association of stroke severity measured with the NIHSS score and location of vessel occlusion. Analysis of outcome in stroke patients with mild and rapidly improving symptoms demonstrated that three of four of these patients had a favourable outcome, but those with a central vessel occlusion were likely to deteriorate with poor outcome. These studies showed that there is a correlation of clinical symptoms with the mechanism of stroke, which is important for the outcome after treatment. Importantly, however, the quality of clinical assessment itself is likely highly variable, for example depending on the experience of the treating physician. Factors influencing this clinical assessment, which needs to be done under high temporal and emotional pressure in the emergency setting have not been investigated so far but might be crucial for rapid and successful treatment ("time is brain").In order to improve clinical diagnosing and future treatment it is essential to quantify the accuracy of clinical diagnosis of stroke in the emergency setting ("how good are neurologists?") and to assesses whether there are any differences between experienced staff neurologists and junior physicians.

Rationale:

By assessing whether prediction of aetiology of acute neurological deficits is experience-based the investigators aim to understand what symptoms/signs impede the in-experienced from swiftly making the correct diagnosis in the emergency setting. This should help to improve resident training and with this treatment of patients with acute neurological deficits.

Dates

Darrera verificació: 06/30/2019
Primer enviat: 01/01/2017
Inscripció estimada enviada: 01/01/2017
Publicat per primera vegada: 01/03/2017
Última actualització enviada: 07/03/2019
Publicació de l'última actualització: 07/07/2019
Data d'inici de l'estudi real: 01/09/2017
Data estimada de finalització primària: 12/30/2020
Data estimada de finalització de l’estudi: 12/30/2020

Condició o malaltia

Stroke Syndrome
Stroke Hemorrhagic
Stroke, Acute
Strokes Thrombotic
Emergencies
Diagnostic Self Evaluation

Intervenció / tractament

Other: No study specific interventions

Fase

-

Criteris d'elegibilitat

Edats elegibles per estudiar 18 Years Per a 18 Years
Sexes elegibles per estudiarAll
Mètode de mostreigNon-Probability Sample
Accepta voluntaris saludables
Criteris

Inclusion Criteria:

- Age ≥ 18 years.

- Non-refusal of "general consent"

- Patients with focal clinical neurological deficits with symptom onset of < 6 hours or wake-up strokes.

Exclusion Criteria:

- Interval from symptom onset to clinical examination of > 6 hours.

- Patients who do not have focal clinical neurological deficit at examination will not be included in the study.

Resultat

Mesures de resultats primaris

1. Proportion of correct initial diagnoses by emergency physicians in patients with focal clinical neurological deficits [7 days +/- 7 days]

Primary endpoint is the proportion of correct initial diagnoses by emergency physicians in patients with focal clinical neurological deficits, calculated by comparing the initial assessment with the final diagnosis at discharge. If the initial assessment was correct, the diagnosis of the emergency physician will be rated as correct (correct answer = Ac), if it was incorrect, it will be rated as incorrect (incorrect answer = Ai). The proportion of accurate initial diagnoses will be calculated as: Ac / (Ac + Ai)

Uneix-te a la nostra
pàgina de Facebook

La base de dades d’herbes medicinals més completa avalada per la ciència

  • Funciona en 55 idiomes
  • Cures a base d'herbes recolzades per la ciència
  • Reconeixement d’herbes per imatge
  • Mapa GPS interactiu: etiqueta les herbes a la ubicació (properament)
  • Llegiu publicacions científiques relacionades amb la vostra cerca
  • Cerqueu herbes medicinals pels seus efectes
  • Organitzeu els vostres interessos i estigueu al dia de les novetats, els assajos clínics i les patents

Escriviu un símptoma o una malaltia i llegiu sobre herbes que us poden ajudar, escriviu una herba i vegeu malalties i símptomes contra els quals s’utilitza.
* Tota la informació es basa en investigacions científiques publicades

Google Play badgeApp Store badge