Evidence map›Paper›PMID 37527381›Full record

ArticleThe western journal of emergency medicine2023

Examining Predictors of Early Admission and Transfer to the Critical Care Resuscitation Unit.

Quincy K Tran, Daniel Najafali, Tiffany Cao, Megan Najafali, Nelson Chen, Iana Sahadzic, Ikram Afridi, Ann Matta, William Teeter, Daniel J Haase

Abstract read
In one paragraph

Article in The western journal of emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. 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

10 authors.

Quincy K TranUniversity of Maryland Medical Center, The Critical Care Resuscitation Unit, Baltimore, Maryland.
Daniel NajafaliUniversity of Illinois Urbana-Champaign, Carle Illinois College of Medicine, Champaign, Illinois.
Tiffany CaoUniversity of Maryland School of Medicine, The Research Associate Program in Emergency Medicine and Critical Care, Department of Emergency Medicine, Baltimore, Maryland.
Megan NajafaliUniversity of Maryland School of Medicine, The Research Associate Program in Emergency Medicine and Critical Care, Department of Emergency Medicine, Baltimore, Maryland.
Nelson ChenUniversity of Maryland School of Medicine, Baltimore, Maryland.
Iana SahadzicUniversity of Maryland School of Medicine, The Research Associate Program in Emergency Medicine and Critical Care, Department of Emergency Medicine, Baltimore, Maryland.
Ikram AfridiUniversity of Maryland School of Medicine, The Research Associate Program in Emergency Medicine and Critical Care, Department of Emergency Medicine, Baltimore, Maryland.
Ann MattaUniversity of Maryland Medical Center, The Critical Care Resuscitation Unit, Baltimore, Maryland.
William TeeterUniversity of Maryland Medical Center, The Critical Care Resuscitation Unit, Baltimore, Maryland.
Daniel J HaaseUniversity of Maryland Medical Center, The Critical Care Resuscitation Unit, Baltimore, Maryland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPrevious studies have demonstrated that rapid transfer to definitive care improves the outcomes for many time-sensitive conditions. The critical care resuscitation unit (CCRU) improves the operations of the University of Maryland Medical Center (UMMC) by expediting the transfers and resuscitations for critically ill patients who exceed the resources at other facilities. In this study we investigated CCRU transfer patterns to determine patient characteristics and logistical factors that influence bed assignments and transfer to the CCRU. We hypothesized that CCRU physicians prioritize transfer for critically ill patients. Therefore, those patients would be transferred faster.

methodsWe performed a retrospective review of all non-traumatic adult patients transferred to the CCRU from other hospitals between January 1-December 31, 2018. The primary outcome was the interval from transfer request to CCRU bed assignment. The secondary outcome was the interval from transfer request to CCRU arrival. We used multivariate logistic regressions to determine associations with the outcomes of interest.

resultsA total of 1,741 patients were admitted to the CCRU during the 2018 calendar year. Of those patients, 1,422 were transferred from other facilities and were included in the final analysis. Patients' mean age was 57 ± 17 years with a median Sequential Organ Failure Assessment (SOFA) score of 3 [interquartile range 1-6]. Median time from transfer request to CCRU bed assignment was 8 (0-70) minutes. A total of 776 (55%) patients underwent surgical intervention after arrival. Using the median transfer request to bed assignment time, we found that patients requiring stroke neurology (odds ratio [OR] 5.49, 95% confidence interval [CI] 2.85-10.86), having higher SOFA score (OR 1.04, 95% CI 1.001-1.07), and needing an immediate operation (OR 2.85, 95% CI 1.98-4.13) were associated with immediate bed assignment time (≤8 minutes). Patients who were operated on (OR 0.74, 95% CI 0.55-0.99) were significantly less likely to have an immediate bed assignment time.

conclusionThe CCRU expedited the transfer of critically ill patients who needed urgent interventions from outside facilities. Higher SOFA scores and the need for urgent neurological or surgical intervention were associated with near-immediate CCRU bed assignment. Other institutions with similar models to the CCRU should perform studies to confirm our observations.

Indexed as

Critical IllnessIntensive Care UnitsAdultAgedCritical CareHospitalizationHumansMiddle AgedRetrospective Studies

Identifiers

PMID37527381
PMCPMC10393446

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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.