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Predicting Severity and Disease Progression in Influenza-like Illness (Including COVID-19)

Predicting Severity and Disease Progression in Influenza-like Illness

Status
Terminated
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04664075
Acronym
PREDICT-ILI
Enrollment
8
Registered
2020-12-11
Start date
2021-01-25
Completion date
2022-04-30
Last updated
2024-05-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Covid19, Infection, Bacterial, Infection Viral, Influenza, Respiratory Tract Infections, Respiratory Viral Infection, RNA Virus Infections, SARS (Severe Acute Respiratory Syndrome)

Keywords

Flu, Influenza, SARS-CoV-2, Covid19, Respiratory, Predict, Infection, RNA

Brief summary

Respiratory infections such as colds, flu and pneumonia affect millions of people around the world every year. Most cases are mild, but some people become very unwell. Influenza ('flu') is one of the most common causes of lung infection. Seasonal flu affects between 10% and 46% of the population each year and causes around 12 deaths in every 100,000 people infected. In addition, both influenza and coronaviruses have caused pandemics in recent years, leading to severe disease in many people. Although flu vaccines are available, these need to change every year to overcome rapid changes in the virus and are not completely protective. This study aims to find and develop predictive tests to better understand how and when flu-like illness progresses to more severe disease. This may help to decide which people need to be admitted to hospital, and how their treatment needs to be increased or decreased during infection. The aim is to recruit 100 patients admitted to hospital due to a respiratory infection. It is voluntary to take part and participants can choose to withdraw at any time. The study will involve some blood and nose samples. This will be done on Day 0, Day 2 and Discharge from hospital, and an out-patient follow-up visit on Day 28. The data will be used to develop novel diagnostic tools to assist in rational treatment decisions that will benefit both individual patients and resource allocation. It will also establish research preparedness for upcoming pandemics.

Detailed description

Despite clinical advances and decades of research, the ability to reliably predict the course of respiratory viral diseases such as influenza and coronavirus infections remains poor. The aim of this project is to develop a platform for identifying and developing predictive tests by combining physiological data and correlates of severity in influenza-like infections so that progression to severe pulmonary involvement can be anticipated during respiratory viral infection. This would then permit safe discharge of patients with self-limiting disease or more rapid intensification of treatment as appropriate. Respiratory infections are among the most important causes of severe disease worldwide, with the major respiratory viruses responsible for overwhelming pressure on health services each winter due to annual surges in incidence. The two most common viral causes of severe lung disease, influenza and respiratory syncytial virus (RSV), are responsible for \ 50% of hospital admissions in children and 22% in adults, with mortality greatest in older people. As the population ages, this burden of disease is steadily increasing. Furthermore, the continual risk of newly emergent pandemic influenza strains that arise unpredictably is universally considered one of the most critical threats to global health and socioeconomic stability. This has been demonstrated by the recent COVID-19 pandemic. Risk factors for severe influenza have been investigated extensively in clinical cohorts, with older age, co-morbidities, obesity and pregnancy all increasing the likelihood of severe disease. However, accurate prognostic markers remain elusive and the dynamics of the response to respiratory viral infection has not been explored in naturally-infected patients. Furthermore, biomarker discovery has been limited by heterogeneity in virus strain and dose; delays in timing of presentation; and patient-level confounders. To address these issues, the investigators have conducted controlled human infections with influenza and RSV since 2010, to investigate mechanisms of immunopathogenesis with a particular focus on disease in the human respiratory tract. Recent preliminary data from a cohort of volunteers infected with the influenza A(H1N1)2009 strain showed that rapid changes in the transcriptome of whole blood occurred within 2 days of virus exposure. During the 2009 influenza pandemic, similar studies were also performed with hospitalised patients. There, transcriptomic analysis of blood showed similar antiviral signatures in less severely unwell individuals but divergent signatures associated with poor clinical outcomes. The aim of this project is to identify and test predictors of disease progression and clinical deterioration in patients with influenza-like illness, in order to develop novel methods to more accurately determine the need for hospital admission and treatment intensification during respiratory viral infection. To further develop and test these biomarkers in an independent cohort of naturally-infected patients, hospitalised adults with influenza-like illness will be recruited within 24 hours of admission and samples obtained from blood and nose at 3 subsequent time-points. Using these data, predictive transcriptomic signatures will be identified. Longitudinal samples and clinical data will then be used to test, validate and refine them in affected local populations. These findings will then be translated into novel diagnostic tools and a biobank established for further investigation of the virology and immunopathogenesis of severe respiratory viral infections.

Interventions

BIOLOGICALRespiratory infections

With biological samples and longitudinal observations, the aim is to find and develop predictive tests to better understand how and when flu-like illness progresses to more severe disease. This may help to decide which people need to be admitted to hospital, and how their treatment needs to be increased or decreased during infection.

Sponsors

Imperial College London
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Healthy persons aged ≥ 18, and able to give informed consent * Patient is admitted to hospital * Primary reason for hospital admission is clinical suspicion of a new episode of ARI * Onset of the following symptoms within the last 7 days: i. Sudden onset of self-reported fever OR temperature of ≥ 38°C at presentation AND ii. At least one respiratory symptom (cough, sore throat, runny or congested nose, dyspnoea) AND iii. At least one systemic symptom (headache, muscle ache, sweats or chills or tiredness).

Exclusion criteria

* Patient lacks capacity to provide informed consent * Patient has been transferred from another hospital * Patient has been previously enrolled in the study

Design outcomes

Primary

MeasureTime frameDescription
Describe the Aetiology of Influenza-like Illness in Hospitalised AdultsDay 0 to Day 28The identity of pathological organisms associated with influenza-like illness (including respiratory viruses and bacteria) will be obtained from the patient's medical record
Describe the Clinical Outcomes of Influenza-like Illness in Hospitalised AdultsDay 0 to Day 28Data collection on Day 28 will consist of clinical diagnosis at discharge, any febrile illness in the 7 days preceding the visit, mortality and complications between Day 0 and 28.
Describe the Clinical Management of Influenza-like Illness in Hospitalised AdultsDay 0 to Day 28Describe the Clinical Management of Influenza-like Illness in Hospitalised Adults

Secondary

MeasureTime frameDescription
Identify Changes in Cytokine Levels During Influenza-like Illness in Hospitalised AdultsDay 0 to Day 28Cytokine levels (in pg/mL) will be measured in plasma and nasal lining fluid samples by MesoScale Discovery

Countries

United Kingdom

Participant flow

Participants by arm

ArmCount
Healthy Persons Aged ≥ 18 Years
Healthy persons aged ≥ 18 years who meet the inclusion/exclusion criteria
8
Total8

Baseline characteristics

CharacteristicHealthy Persons Aged ≥ 18 Years
Age, Categorical
<=18 years
0 Participants
Age, Categorical
>=65 years
4 Participants
Age, Categorical
Between 18 and 65 years
4 Participants
Age, Continuous55 years
Race/Ethnicity, Customized
Race and Ethnicity
Asian or Asian British (Indian)
3 Participants
Race/Ethnicity, Customized
Race and Ethnicity
Mixed (White and Asian)
2 Participants
Race/Ethnicity, Customized
Race and Ethnicity
White British
2 Participants
Race/Ethnicity, Customized
Race and Ethnicity
White Other
1 Participants
Region of Enrollment
United Kingdom
8 participants
Sex: Female, Male
Female
2 Participants
Sex: Female, Male
Male
6 Participants

Adverse events

Event typeEG000
affected / at risk
deaths
Total, all-cause mortality
0 / 8
other
Total, other adverse events
0 / 8
serious
Total, serious adverse events
1 / 8

Outcome results

Primary

Describe the Aetiology of Influenza-like Illness in Hospitalised Adults

The identity of pathological organisms associated with influenza-like illness (including respiratory viruses and bacteria) will be obtained from the patient's medical record

Time frame: Day 0 to Day 28

Population: 8 participants were enrolled into this study with a diagnosis of ARI (Acute Respiratory Infection)

ArmMeasureCategoryValue (COUNT_OF_PARTICIPANTS)
Healthy Persons Aged ≥ 18 YearsDescribe the Aetiology of Influenza-like Illness in Hospitalised AdultsSARS-CoV-24 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Aetiology of Influenza-like Illness in Hospitalised AdultsNo pathogen4 Participants
Primary

Describe the Clinical Management of Influenza-like Illness in Hospitalised Adults

Describe the Clinical Management of Influenza-like Illness in Hospitalised Adults

Time frame: Day 0 to Day 28

Population: 8 participants were enrolled into this study. 6 participants, 3 of which with confirmed SARS-CoV-2 infection, received a steroid treatment. 7 participants received a treatment course of antibiotics.~1 participant did not receive any antibiotics, this participant did not have a confirmed causative respiratory pathogen found. 4 participants received Remdesivir (antiviral), three of which had a positive PCR test for SARS-CoV-2, one without.

ArmMeasureCategoryValue (COUNT_OF_PARTICIPANTS)
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Management of Influenza-like Illness in Hospitalised AdultsAntibiotic + Steroid Treatment3 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Management of Influenza-like Illness in Hospitalised AdultsAntibiotic Treatment1 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Management of Influenza-like Illness in Hospitalised AdultsAntibiotic + Antiviral Treatment1 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Management of Influenza-like Illness in Hospitalised AdultsAntibiotic + Antiviral + Steroid Treatment2 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Management of Influenza-like Illness in Hospitalised AdultsAntiviral + Steroid Treatment1 Participants
Primary

Describe the Clinical Outcomes of Influenza-like Illness in Hospitalised Adults

Data collection on Day 28 will consist of clinical diagnosis at discharge, any febrile illness in the 7 days preceding the visit, mortality and complications between Day 0 and 28.

Time frame: Day 0 to Day 28

Population: 8 participants who were enrolled had a diagnosis of Acute Respiratory Illness (ARI) then recovered and were discharged home.

ArmMeasureGroupValue (COUNT_OF_PARTICIPANTS)
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Outcomes of Influenza-like Illness in Hospitalised AdultsAcute Lung Injury/Acute Respiratory Distress syndrome1 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Outcomes of Influenza-like Illness in Hospitalised AdultsARI and hyperglycaemia1 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Outcomes of Influenza-like Illness in Hospitalised AdultsARI secondary to SARS-CoV-2 infection2 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Outcomes of Influenza-like Illness in Hospitalised AdultsARI with no causative pathogen found1 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Outcomes of Influenza-like Illness in Hospitalised AdultsARI with no causative pathogen found with partial middle lobe collapse and anaemia2 Participants
Healthy Persons Aged ≥ 18 YearsDescribe the Clinical Outcomes of Influenza-like Illness in Hospitalised AdultsARI with left lower lobe abscess and dermatitis1 Participants
Secondary

Identify Changes in Cytokine Levels During Influenza-like Illness in Hospitalised Adults

Cytokine levels (in pg/mL) will be measured in plasma and nasal lining fluid samples by MesoScale Discovery

Time frame: Day 0 to Day 28

Population: As we only recruited 8 participants out of the 100 recruitment target, the cytokine assays were not run and therefore no results are available for this outcome measure due to the poor recruitment.

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026