ArticleAmerican journal of respiratory and critical care medicine2023
Linking Acute Physiology to Outcomes in the ICU: Challenges and Solutions for Research.
Article in American journal of respiratory and critical care medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Seeing the random forest for the Zzz's: machine learning's new role in sleep science.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- Article
- Recruitment-to-inflation ratio reflects the impact of peep on dynamic lung strain in a highly recruitable model of ARDS.Annals of intensive care · 2024Article
- Reply to Fernández.American journal of respiratory and critical care medicine · 2023Article
- Models That Link Physiology with Outcomes.American journal of respiratory and critical care medicine · 2023Article
Corrections and comments
- Commented on by
Authors and funding
9 authors.
Funding
Abstract
ICU clinicians rely on bedside physiological measurements to inform many routine clinical decisions. Because deranged physiology is usually associated with poor clinical outcomes, it is tempting to hypothesize that manipulating and intervening on physiological parameters might improve outcomes for patients. However, testing these hypotheses through mathematical models of the relationship between physiology and outcomes presents a number of important methodological challenges. These models reflect the theories of the researcher and can therefore be heavily influenced by one's assumptions and background beliefs. Model building must therefore be approached with great care and forethought, because failure to consider relevant sources of measurement error, confounding, coupling, and time dependency or failure to assess the direction of causality for associations of interest before modeling may give rise to spurious results. This paper outlines the main challenges in analyzing and interpreting these models and offers potential solutions to address these challenges.
Indexed as
Identifiers
36705985What 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.