Evidence map›Paper›PMID 33019268›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2020

Pain and Physical Activity Association in Critically Ill Patients

Anis Davoudi, Tezcan Ozrazgat-Baslanti, Patrick J Tighe, Azra Bihorac, Parisa Rashidi

Abstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Diurnal Pain Classification in Critically Ill Patients using Machine Learning on Accelerometry and Analgesic Data.IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anis Davoudi
Tezcan Ozrazgat-Baslanti
Patrick J Tighe
Azra Bihorac
Parisa Rashidi

Funding

Integrating data, algorithms and clinical reasoning for surgical risk assessmentR01GM110240 · NIGMS · UNIVERSITY OF FLORIDA · PI BIHORAC, AZRA, RASHIDI, PARISA · 2016 to 2025
$5.1M
Finding Good TEMporal PostOperative pain Signatures (TEMPOS)R01GM114290 · NIGMS · UNIVERSITY OF FLORIDA · PI TIGHE, PATRICK J · 2015 to 2019
$2.5M
Autonomous Pain Recognition in Non-Verbal and Critically Ill PatientsR21EB027344 · NIBIB · UNIVERSITY OF FLORIDA · PI RASHIDI, PARISA · 2019 to 2022
$577k
NIBIB NIH HHS R21 EB027344NIGMS NIH HHS R01 GM110240NIGMS NIH HHS R01 GM114290
6 · The paper itself

Abstract

Critical care patients experience varying levels of pain during their stay in the intensive care unit, often requiring administration of analgesics and sedation. Such medications generally exacerbate the already sedentary physical activity profiles of critical care patients, contributing to delayed recovery. Thus, it is important not only to minimize pain levels, but also to optimize analgesic strategies in order to maximize mobility and activity of ICU patients. Currently, we lack an understanding of the relation between pain and physical activity on a granular level. In this study, we examined the relationship between nurse assessed pain scores and physical activity as measured using a wearable accelerometer device. We found that average, standard deviation, and maximum physical activity counts are significantly higher before high pain reports compared to before low pain reports during both daytime and nighttime, while percentage of time spent immobile was not significantly different between the two pain report groups. Clusters detected among patients using extracted physical activity features were significant in adjusted logistic regression analysis for prediction of pain report group.

Indexed as

Critical IllnessPainAnalgesicsExerciseHumansIntensive Care UnitsAnalgesics

Identifiers

PMID33019268
PMCPMC7592073

What OpenQuestion holds

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Registered trials

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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.