ArticleCritical care (London, England)2021
Novel criteria to classify ARDS severity using a machine learning approach.
Article in Critical care (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06430619 (New Criteria for Classifying Acute Respiratory Distress Syndrome Severity Using a Machine Learning Approach), which is not on this map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
New Criteria for Classifying Acute Respiratory Distress Syndrome Severity Using a Machine Learning Approach: Novel Oxygenation and Saturation Indices
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of machine learning models for management, prediction and classification of ARDS.Respiratory research · 2024Pooled it
- Effect of different levels of PEEP on mortality in ICU patients without acute respiratory distress syndrome: systematic review and meta-analysis with trial sequential analysis.Journal of critical care · 2021Pooled it
- Integrating the Hospital Frailty Risk Score into Explainable Machine Learning to Predict Mortality in Older Adults with Pneumonia: A Chilean Population-Based Study.Diagnostics (Basel, Switzerland) · 2026Article
- Respiratory physiology after resupination following prone ventilation to predict 28-day mortality in mechanically ventilated patients: a machine learning analysis.Scientific reports · 2026Article
- Article
- Deciphering Oxygenation Metrics in ARDS: A Deep Dive into the OXIVA-CARDS Study.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025Article
- Comparison of artificial intelligence and logistic regression models for mortality prediction in acute respiratory distress syndrome: a systematic review and meta-analysis.Intensive care medicine experimental · 2025Review
- Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning.Scientific reports · 2025Article
- The development of a C5.0 machine learning model in a limited data set to predict early mortality in patients with ARDS undergoing an initial session of prone positioning.Intensive care medicine experimental · 2024Article
- Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach.Scientific reports · 2024Observational
- Novel Oxygenation and Saturation Indices for Mortality Prediction in COVID-19 ARDS Patients: The Impact of Driving Pressure and Mechanical Power.Journal of intensive care medicine · 2024Article
- An early screening model for preeclampsia: utilizing zero-cost maternal predictors exclusively.Hypertension research : official journal of the Japanese Society of Hypertension · 2024Article
- Article
- Acute respiratory distress syndrome in patients with COVID-19 vs. Non-COVID-19: clinical characteristics and outcomes in a tertiary care setting in Mexico City.BMC pulmonary medicine · 2023Observational
- Artificial Intelligence-Driven Respiratory Distress Syndrome Prediction for Very Low Birth Weight Infants: Korean Multicenter Prospective Cohort Study.Journal of medical Internet research · 2023Article
- Machine learning predicts lung recruitment in acute respiratory distress syndrome using single lung CT scan.Annals of intensive care · 2023Article
- Predicting Duration of Mechanical Ventilation in Acute Respiratory Distress Syndrome Using Supervised Machine Learning.Journal of clinical medicine · 2021Article
- Article
- The impact of pneumoperitoneum and steep Trendelenburg positioning on novel oxygenation and saturation indices in robot-assisted laparoscopic prostatectomies: A prospective observational study.Saudi journal of anaesthesiaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundUsually, arterial oxygenation in patients with the acute respiratory distress syndrome (ARDS) improves substantially by increasing the level of positive end-expiratory pressure (PEEP). Herein, we are proposing a novel variable [PaO
methodsWe examined P/FP
resultsP/FP
conclusionsThe novel P/FP
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.