Evidence map›Paper›PMID 28353579›Full record

Trial reportMedicine2017

Intensive insulin therapy for preventing postoperative infection in patients with traumatic brain injury: A randomized controlled trial.

Yan Wang, Jin-Ping Li, Ying-Lun Song, Qi-Huang Zhao

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
1.4field-weighted citation impact, top 18% of its field
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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 21 citations in OpenAlex.

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  8. Perioperative glycaemic control for people with diabetes undergoing surgery.The Cochrane database of systematic reviews · 2023
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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

4 authors at 2 institutions in 1 country.

Yan WangDepartment of Neurosurgery (Intensive Care Unit) Department of Neurosurgery, Beijing ChaoYang Hospital, Capital Medical University, Beijing, China.
Jin-Ping Li
Ying-Lun Song
Qi-Huang Zhao
Beijing Chao-Yang Hospital · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess the effect of intensive insulin therapy (IIT) for preventing postoperative infection in patients with traumatic brain injury (TBI).

methodsIn total, 88 patients with TBI were randomly divided into 2 groups, 44 in each group. One group (group ITT) received IIT and the other group (group CIT) received conventional insulin therapy (CIT). This study was conducted between February 2013 and January 2016. Outcomes included infection rate, mortality, and neurological outcome (measured by the Glasgow Outcome Scale [GOS]).

resultsA total of 81 patients completed the study. IIT showed greater efficacy than CIT, with a decreased infection rate in the IIT group compared to the CIT group (31.9% vs 52.3%, P = 0.03), and also a reduced duration of stay in intensive care unit (ICU) (IIT group, 4.5 ± 2.1 days vs CIT group, 5.7 ± 2.8 days, P = 0.02). In addition, a significant difference in scores on the GOS scale was observed between the 2 groups (P = 0.04). The mortality rates in hospital and at the 26-week follow-up were similar between the 2 groups.

conclusionIIT leads to a reduced infection rate, shorter stays in ICU, and improved neurological outcome.

Indexed as

AdultBrain Injuries, TraumaticChinaCritical CareFemaleHumansHypoglycemic AgentsInsulinLength of StayMaleMiddle AgedPostoperative ComplicationsHypoglycemic AgentsInsulin

Identifiers

PMID28353579
PMCPMC5380263
OpenAlexW2602034410

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.