Active Public Health & Healthcare NIHR-supported project Lungs & Breathing

The burden, management startegies adopted and outcomes of severe respiratory tract infections in intensive units- wessex clinical research collaboration from wessex intensive care resarch network

In plain English

AI plain-English summary

One in five patients admitted to intensive care in the UK will not leave the hospital alive, yet doctors have little data on what happens to the survivors in the years after discharge. This study tackles a blind spot in critical care. National audits track short-term survival, but they rarely follow patients beyond hospital walls or account for the specific disease, treatments, and patient characteristics that shape long-term recovery. The researchers will analyse records from a single major intensive care unit in Wessex, focusing on adults with severe respiratory tract infections. They will examine how factors such as oxygen therapy, fluids, nutrition, steroids, and antimicrobial use affect outcomes up to three years later. They will also map the lung microbiome—the community of microbes normally present—and track how antibiotic resistance develops during treatment. If successful, this work could give intensive care doctors clearer evidence on which treatments improve not just survival but meaningful long-term recovery. It could also sharpen antimicrobial stewardship by linking specific prescribing patterns to resistance and patient outcomes. The findings will be specific to one region, but the methods could be replicated elsewhere, helping to close a persistent gap in how critical care is evaluated and improved.

View original technical description
Critical-illnesses are a heterogeneous group of medical conditions that cause significant morbidity and mortality. Among patients admitted with critical-illness to critical care units, hospital mortality is approximately 20%. However, there are several factors that influence not only patient survival but also recovery from the acute insult itself. Disease specific long-term outcomes corrected for several confounding factors are rarely reported. In the UK, a national audit office (Intensive Care National Audit & Research Centre - ICNARC) collects data from most intensive care units and publish outcome data intermittently. However, this is not informative with regards to long-term mortality and may not be applicable to our local population. This study aims to retrospectively measure long-term outcomes (up to 3 years) for adult patients (>18 years old) with specific critical illnesses within a single, tertiary centre. Moreover, we want to analyse the impact of specific patient factors, disease types and intensive care unit interventions on overall patient outcomes. Specifically: The epidemiology of normal lung microbiome and pathogenic organisms, combined with the demographics of severe respiratory tract infections in the ICU; Assess the impact of oxygen, fluid, nutrition, corticosteroids, and the use of adjunct therapies (E.g. but not limited to prone positioning, NIV, mechanical ventilation); Antimicrobial practices, biomarkers/guideline use for antimicrobial stewardship, and developing resistant patterns in the ICU; to evaluate patient survival, hospital/ICU length of stay, readmission and post-ICU complications and to evaluate research participation of patients with acute respiratory infections in the ICU.

Researchers

Ahilanandan Dushianthan (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

REFLECT - Recovery Following Intensive Care Treatment
The short and long-term cardiovascular consequences of critical illness: The C3 Study
Outcomes of Patients Admitted with Critical-Illness to the General Intensive Care Unit - a Retrospective Observational Study. No recruitment, just analysis of data.
Safe staffing in ICU: development and testing of a staffing model
Risk modelling for quality improvement in the critically ill: making best use of routinely available data

Original classification

Data, Health and Society (DHS)

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.