READ ME File For 'Airway pressure release ventilation (APRV) as a rescue measure for severe hypoxemic respiratory failure- outcomes and oxy-genation response from an observational cohort'

Dataset DOI:   https://doi.org/10.5258/SOTON/D3845

Date that the file was created: Febuary, 2026

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GENERAL INFORMATION
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ReadMe Author: Mark Brown, University of Southampton [OPTIONAL add ORCID ID]

Date of data collection: 01/01/2018 - 30/01/2024

Information about geographic location of data collection: University Hospital Southampton NHS Trust 

Related projects:
Airway pressure release ventilation (APRV) as a rescue measure for severe hypoxemic respiratory failure- outcomes and oxy-genation response from an observational cohort

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SHARING/ACCESS INFORMATION
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Licenses/restrictions placed on the data, or limitations of reuse: CC YB 

Recommended citation for the data:

This dataset supports the publication: (TBC)
AUTHORS: Harriet Jacobs, Mark Brown, Elizabeth Webb, Olivia Cox, Isis Terrington, Tanvi Dabke, Diana David, Benjamin Eastwood, Ryan Beecham, Michael P. W. Grocott, and Ahilanandan Dushianthan
TITLE: Outcome and Oxygenation Response to Airway Pressure Release Ventilation (APRV) Used as a Rescue Strategy for Severe Hypoxemic Respiratory Failure—An Observational Study
JOURNAL: Journal of Clinical Medicine
PAPER DOI IF KNOWN: 10.3390/jcm15072668.

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DATA & FILE OVERVIEW
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This dataset contains:

- Read me 
- Arterial blood gas data 
- Patient level characteristics and clinical outcomes.
- Data dictionary 

Relationship between files, if important for context:  Study_id as a common identifier across all data sets. 

Additional related data collected that was not included in the current data package: Data used for the publications of kaplan meiers curves has not been published with this data, however, can be produced on request. 

If data was derived from another source, list source:

If there are there multiple versions of the dataset, list the file updated, when and why update was made:

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METHODOLOGICAL INFORMATION
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This was a retrospective, observational cohort study conducted in a general intensive care unit (ICU)  based in a tertiary centre in the South of England. All patients ventilated with APRV mode from 01/01/2018 to 30/09/2024. Data was gathered using ICU and hospital clinical notes from the two online platforms used at the trust, MetaVision (iMDsoft, Tel Aviv, Israel) and CHARTS (custom software for University Hospital Southampton NHS Trust, version 35). Response to airway pressure release ventilation (APRV) was determined by using the mean P/F ratio for the 6 hours pre-intervention compared to the mean P/F ratio for the subsequent 6 hours post-intervention.  The primary outcome was improvement in mean oxygenation (P/F ratio) following APRV use after 6 hours. Secondary outcomes included in-hospital mortality, ICU mortality, duration of mechanical ventilation, ICU length of stay and effects on COVID-19 patients. 

Descriptive and outcome characteristics were reported as median and interquartile ranges (IQR) for continuous variables and counts with percentages for categorical variables. Comparison of groups were made by Mann-Whitney U and Fisher’s exact test for continuous and categorical variables respectively. Kaplan Meier’s were used to describe overall survival and time to liberation from invasive mechanical ventilation. To describe the effect of APRV on physiological parameters (PO2, PCO2, and pH) across the cohort, an interrupted time series (ITS) model was constructed. We used a linear mixed effects model allowing random effects specified for physiological parameters (PO2, PCO2, and pH) while clustering at the participant level. For predictive modelin, variables with a P value < 0.25 from univariable logistic regression for ICU mortality were included in a multivariable model. Subsequent backwards selection was performed using the Akaike Information Criterion (AIK) to produce a final model. All model assumptions were tested graphically. Analysis was conducted in R (version 4.5.0) using the nlme, survival and MASS packages.   

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DATA-SPECIFIC INFORMATION 
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patient_level_data

Number of variables: 25

Number of cases/rows: 152

Variable list, defining any abbreviations, units of measure, codes or symbols used: See data dictionary 
   
Missing data codes: Left as “”  which will code as NA in R or Python 

Specialized formats or other abbreviations used: snake case used, see data dictionary 

interrupted_time_series 

Number of variables: 9

Number of cases/rows: 6503

Variable list, defining any abbreviations, units of measure, codes or symbols used: See data dictionary 
   
Missing data codes: Left blank 

Specialized formats or other abbreviations used: snake case used, see data dictionary 

peri_aprv_intitiation

Number of variables: 15

Number of cases/rows: 152

Variable list, defining any abbreviations, units of measure, codes or symbols used: See data dictionary 
   
Missing data codes: Left blank 

Specialized formats or other abbreviations used: snake case used, see data dictionary