CompletedNot Applicable

Neural Network-Based Prediction in Critical COVID-19 Patients

Turkey (Türkiye)113 participantsStarted 2024-02-01

Plain-language summary

In the context of an emerging pandemic without an established prognostic scoring system, deep learning approaches can be used to quickly develop empirical prognostic models. This study aimed to present an artificial neural network (ANN) model to predict the duration of mechanical ventilation and mortality in COVID-19 patients at the intensive care unit. Methods: Data were collected from medical records of 113 COVID-19 patients who had followed up at the intensive care unit between February 2020 and June 2020. An ANN approach was used to predict the length of mechanical ventilation and mortality in COVID-19 patients by evaluating patients' clinical data (demographic, laboratory, and comorbidities).

Who can participate

Age range18 Years – 98 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: Age ≥ 18 years Confirmed diagnosis of COVID-19 Admission to the intensive care unit (ICU) between February 1, 2020 and June 30, 2020 Availability of complete clinical, laboratory, and outcome data in medical records Exclusion Criteria: Age \< 18 years Incomplete or missing clinical data Transfer to another institution before outcome assessment Readmission to ICU during the same hospitalization (only first admission included)

What they're measuring

All-cause ICU Mortality

Timeframe: From ICU admission until hospital discharge or death (up to 90 days)

Trial details

NCT IDNCT07436572

SponsorUniversity of Gaziantep

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2025-02-01

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