Evidence map›Paper›PMID 31933216›Full record

ArticleNeurocritical care2020

Glucose Variability as Measured by Inter-measurement Percentage Change is Predictive of In-patient Mortality in Aneurysmal Subarachnoid Hemorrhage.

Ofer Sadan, Chen Feng, Branislav Vidakovic, Yajun Mei, Kathleen Martin, Owen Samuels, C L Hall

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Article in Neurocritical care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
1.7field-weighted citation impact, top 15% 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, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.

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  6. Group-based trajectory modeling identifies distinct glycemic patterns predictive of mortality in aneurysmal subarachnoid hemorrhage.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
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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

7 authors at 2 institutions in 1 country.

Ofer Sadan *Department of Neurology and Neurosurgery, Division of Neurocritical Care, Emory University Hospital, Emory University School of Medicine, 1364 Clifton Rd. NE, Atlanta, GA, 30322, USA. ofer.sadan@gmail.com.ORCID http://orcid.org/0000-0002-0050-3025
Chen Feng *H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Branislav VidakovicH. Milton Stewart School of Industrial & Systems Engineering and Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332-0205, USA.
Yajun MeiH. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Kathleen MartinDepartment of Neurology and Neurosurgery, Division of Neurocritical Care, Emory University Hospital, Emory University School of Medicine, 1364 Clifton Rd. NE, Atlanta, GA, 30322, USA.
Owen SamuelsDepartment of Neurology and Neurosurgery, Division of Neurocritical Care, Emory University Hospital, Emory University School of Medicine, 1364 Clifton Rd. NE, Atlanta, GA, 30322, USA.
C L HallDepartment of Neurology and Neurosurgery, Division of Neurocritical Care, Emory University Hospital, Emory University School of Medicine, 1364 Clifton Rd. NE, Atlanta, GA, 30322, USA.
Emory University Hospital · USGeorgia Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCritically ill aneurysmal subarachnoid hemorrhage (aSAH) patients suffer from systemic complications at a high rate. Hyperglycemia is a common intensive care unit (ICU) complication and has become a focus after aggressive glucose management was associated with improved ICU outcomes. Subsequent research has suggested that glucose variability, not a specific blood glucose range, may be a more appropriate clinical target. Glucose variability is highly correlated to poor outcomes in a wide spectrum of critically ill patients. Here, we investigate the changes between subsequent glucose values termed "inter-measurement difference," as an indicator of glucose variability and its association with outcomes in patients with aSAH.

methodsAll SAH admissions to a single, tertiary referral center between 2002 and 2016 were screened. All aneurysmal cases who had more than 2 glucose measurements were included (n = 2451). We calculated several measures of variability, including simple variance, the average consecutive absolute change, average absolute change by time difference, within subject variance, median absolute deviation, and average or median consecutive absolute percentage change. Predictor variables also included admission Hunt and Hess grade, age, gender, cardiovascular risk factors, and surgical treatment. In-patient mortality was the main outcome measure.

resultsIn a multiple regression analysis, nearly all forms of glucose variability calculations were found to be correlated with in-patient mortality. The consecutive absolute percentage change, however, was most predictive: OR 5.2 [1.4-19.8, CI 95%] for percentage change and 8.8 [1.8-43.6] for median change, when controlling for the defined predictors. Survival to ICU discharge was associated with lower glucose variability (consecutive absolute percentage change 17% ± 9%) compared with the group that did not survive to discharge (20% ± 15%, p < 0.01). Interestingly, this finding was not significant in patients with pre-admission poorly controlled diabetes as indicated by HbA1c (OR 0.45 [0.04-7.18], by percentage change). The effect is driven mostly by non-diabetic patients or those with well-controlled diabetes.

conclusionsReduced glucose variability is highly correlated with in-patient survival and long-term mortality in aSAH patients. This finding was observed in the non-diabetic and well-controlled diabetic patients, suggesting a possible benefit for personalized glucose targets based on baseline HbA1c and minimizing variability. The inter-measure percentage change as an indicator of glucose variability is not only predictive of outcome, but is an easy-to-use tool that could be implemented in future clinical trials.

Indexed as

Subarachnoid HemorrhageGlucoseHospital MortalityHumansRetrospective StudiesTreatment OutcomeGlucoseCritical careDiabetes mellitusGlucoseInsulinSubarachnoid hemorrhageVariability

Identifiers

PMID31933216
OpenAlexW3000628538

What OpenQuestion holds

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Read underepoch 390

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.