Evidence map›Paper›PMID 38550708›Full record

ArticleHospital pharmacy2023

Medication regimen complexity (MRC-ICU) for in-hospital mortality prediction in COVID-19 patients.

Hanna Azimi, Logan Johnson, Carly Loudermilk, Aaron Chase, Christy Cecil Forehand, Andrea Sikora

Abstract read
In one paragraph

Article in Hospital pharmacy, 2023. 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. Observational
  2. Article
  3. 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

6 authors.

Hanna AzimiAugusta University Medical Center, Augusta, GA, USA.
Logan JohnsonUniversity of Georgia College of Pharmacy, Augusta, GA, USA.
Carly LoudermilkUniversity of Georgia College of Pharmacy, Augusta, GA, USA.
Aaron ChaseAugusta University Medical Center, Augusta, GA, USA.ORCID https://orcid.org/0000-0002-5891-4492
Christy Cecil ForehandAugusta University Medical Center, Augusta, GA, USA.ORCID https://orcid.org/0000-0001-7523-0490
Andrea SikoraAugusta University Medical Center, Augusta, GA, USA.ORCID https://orcid.org/0000-0003-2020-0571

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The medication regimen complexity-intensive care unit (MRC-ICU) score was developed prior to the existence of COVID-19. The purpose of this study was to assess if MRC-ICU could predict in-hospital mortality in patients with COVID-19. Methods: A single-center, observational study was conducted from August 2020 to January 2021. The primary outcome of this study was the area under the receiver operating characteristic (AUROC) for in-hospital mortality for the 48-hour MRC-ICU. Age, sequential organ failure assessment (SOFA), and World Health Organization (WHO) COVID-19 Severity Classification were assessed. Logistic regression was performed to predict in-hospital mortality as well as WHO Severity Classification at 7 days. Results: A total of 149 patients were included. The median SOFA score was 8 (IQR 5-11) and median MRC-ICU score at 48 hours was 15 (IQR 7-21). The in-hospital mortality rate was 36% (n = 54). The AUROC for MRC-ICU was 0.71 (95% Confidence Interval (CI), 0.62-0.78) compared to 0.66 for age, 0.81 SOFA, and 0.72 for the WHO Severity Classification. In univariate analysis, age, SOFA, MRC-ICU, and WHO Severity Classification all demonstrated significant association with in-hospital mortality, while SOFA, MRC-ICU, and WHO Severity Classification demonstrated significant association with WHO Severity Classification at 7 days. In univariate analysis, all 4 characteristics showed significant association with mortality; however, only age and SOFA remained significant following multivariate analysis. Conclusion: In the first analysis of medication-related variables as a predictor of severity and in-hospital mortality in COVID-19, MRC-ICU demonstrated acceptable predictive ability as represented by AUROC; however, SOFA was the strongest predictor in both AUROC and regression analysis.

Indexed as

COVID-19COVID severity scorecritical caremedication regimen complexityquality improvementsequential organ failure assessment (SOFA)

Identifiers

PMID38550708
PMCPMC10158809

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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.