Optimising Resource Allocation Via Prediction of Outcomes for Covid-19
NCT04473105 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 11134
Last updated 2024-04-09
Summary
The investigators plan to use all of the information available within their local NHS hospitals Trust to work out what happens to people admitted with both suspected and proven Covid-19 infections. The investigators will use all of the information that they can to provide the most evidence possible to use in their investigation as this will make the results more accurate. This will include information on existing health conditions (e.g. by looking at previous discharge letters, GP summaries), clinical observations recorded in the hospital (e.g. temperature, blood pressure, pulse, oxygen levels) and laboratory measures (e.g. blood markers of infection). The investigators experienced team will then analyse all of this together with information about whether the person has Covid-19 to help work out what any new patients' risk will be. To do this the investigators need to use individual patients' information, however once removed from the hospital records system it will not be identifiable and will be held securely within the hospital at all times. As a result of this work the investigators plan to be able to do two things:
1. When a patient is admitted to hospital with possible or confirmed Covid-19 the investigators will be able to make a highly accurate prediction of what is likely to happen to them (e.g. being admitted to high dependency or intensive care, dying or surviving to discharge) which will help health care professional make decisions about their care.
2. By knowing what is likely to happen to a patient the investigators are able to make informed decisions about how to distribute healthcare resources e.g. which areas are likely to need more ventilators (machines to help with breathing), need for intensive care beds, discharge planning.
Conditions
- COVID19
Sponsors & Collaborators
-
East Midlands Academic Health Sciences Network
collaborator UNKNOWN -
Nottingham University Hospitals NHS Trust
lead OTHER
Principal Investigators
-
Timothy R Card, FRCP, PhD · University of Nottingham
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2020-05-01
- Primary Completion
- 2021-12-31
- Completion
- 2022-03-31
Countries
- United Kingdom
Study Locations
More Related Trials
-
Risk Prediction and Therapy Monitoring in Patients With SARS-Cov-2 Infection / COVID 19
NCT04456075 ·Status: UNKNOWN
-
PHenotyping patiENts Admitted to Hospital With cOvid-19 Infection and idenTifYing Prognostic markErs
NCT04459351 ·Status: UNKNOWN
-
poSt Covid-19 Infection centraL sENsitisaTion
NCT04703452 ·Status: UNKNOWN
-
Testing for COVID-19 Infection in Asymptomatic Persons
NCT04345510 ·Status: COMPLETED
-
Long-term Follow-up Study of COVID-19
NCT05986435 ·Status: UNKNOWN
-
Risk Factors and Prognoses in Patients Hospitalized for COVID-19
NCT04824677 ·Status: COMPLETED
-
Characterizing the Perioperative Epidemiology of SARS-CoV-2 (COVID-19) Spread for Quality Improvement of Perioperative Infection Control Program
NCT04443803 ·Status: COMPLETED
-
Utility of Empiric Antibiotics for Non-intubated Novel Coronavirus Diseases 2019 Patients
NCT04674410 ·Status: WITHDRAWN
-
Characteristics and Outcomes of Hospitalized Patients With COVID-19 in Spain
NCT04355871 ·Status: COMPLETED
-
COG-UK Project Hospital-Onset COVID-19 Infections Study
NCT04405934 ·Status: COMPLETED ·Phase: NA
-
Long-term Effects of COVID-19: a Comparative Cohort Study
NCT05002205 ·Status: UNKNOWN
-
Prognostication of Oxygen Requirement in Non-severe SARS-CoV-2 Infection
NCT04441372 ·Status: UNKNOWN
-
Clinical Characteristics And Outcome Of COVID-19 Infection In Patients With Chronic Respiratory Diseases.
NCT05054127 ·Status: UNKNOWN
-
Predictive Factors COVID-19 Patients
NCT04427345 ·Status: WITHDRAWN
-
Pattern and Outcomes of Chest Diseases
NCT06053528 ·Status: UNKNOWN
-
poSt Covid-19 Infection centraL Sensitisation 2
NCT04701892 ·Status: UNKNOWN
-
Oxygen Requirements and Use in Patients With COVID-19 in LMICs
NCT04918875 ·Status: UNKNOWN
-
Health Professional Exposure Assessment to Covid-19
NCT04429724 ·Status: COMPLETED ·Phase: NA
-
Mechanisms for Covid-19 Disease Complications
NCT04314232 ·Status: UNKNOWN
-
Network-Targeted Strategies for Efficient Community SARS-CoV-2 (COVID-19) Sampling
NCT04437706 ·Status: COMPLETED
-
Artificial Intelligence for Respiratory Infections SEverity Prediction
NCT07047768 ·Status: ACTIVE_NOT_RECRUITING
-
Specific Respiratory Infections as Triggers of Acute Medical Events
NCT02984280 ·Status: COMPLETED
-
Institutional Registry on Outpatient and Hospitalized COVID-19 Infected Patients
NCT04839107 ·Status: UNKNOWN
-
Long-term Pulmonary Outcomes After Infection With Sars-CoV-2
NCT04401163 ·Status: COMPLETED
-
Longitudinal Population-based Observational Study of COVID-19 in the UK Population
NCT04330599 ·Status: RECRUITING