Timing Is Everything. The Importance of Alignment of Time Anchors for Observational Causal Inference Research.

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

3 citing papers in PubMed, 3 citations in OpenAlex.

1. Assessment of the effectiveness of protein in critical illness: the role of statistical shortcomings in explaining discrepancies between observational studies and randomized controlled trials.Critical care (London, England) · 2026
   Review
2. Beyond Confounding: Identifying Selection Bias in Observational Pulmonary and Critical Care Research.Annals of the American Thoracic Society · 2022
   Article
3. Accurately Measuring Preventable Ventilator-associated Pneumonia Deaths Using Observational Data: It's about Time.Annals of the American Thoracic Society · 2021
   Article

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 at 3 institutions in 1 country.

Funding

Abstract

PubMed holds no abstract for this paper.

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