Evidence map›Paper›PMID 36371171›Full record

ArticleBMC emergency medicine2022

Predicting hypoglycemia after treatment of hyperkalemia with insulin and glucose (Glu-K60 score).

Weerapriya Kijprasert, Nilanut Tarudeeyathaworn, Chananthita Loketkrawee, Thidarat Pimpaporn, Pornpiyapat Pattarasettaseranee, Theerapon Tangsuwanaruk

Open access · goldAbstract read
In one paragraph

Article in BMC emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Weerapriya KijprasertFaculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Nilanut TarudeeyathawornFaculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Chananthita LoketkraweeFaculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Thidarat PimpapornFaculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Pornpiyapat PattarasettaseraneeFaculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Theerapon TangsuwanarukDepartment of Emergency Medicine, Faculty of Medicine, Chiang Mai University, 110 Inthawaroros Road, Sribhumi, Amphoe Muang, Chiang Mai, 50200, Thailand. theerapon.t@cmu.ac.th.ORCID 0000-0003-1783-3095
Chiang Mai University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperkalemia can lead to fatal cardiac arrhythmias. Ten units of intravenous (IV) regular insulin with 25 g of glucose is the mainstay for treating hyperkalemia. However, the most important complication of this treatment is hypoglycemia. We aimed to develop a scoring model to predict hypoglycemia after the treatment of hyperkalemia.

methodsA retrospective study was conducted at a university-based hospital between January 2013 and June 2021. We included the hyperkalemic patients (> 5.3 mmol/L) who were ≥ 18 years old and treated with 10 units of IV regular insulin with 25 g of glucose. Incomplete data on posttreatment blood glucose, pregnancy, and diabetes mellitus were excluded. Endpoint was posttreatment hypoglycemia (≤ 70 mg/dL or ≤ 3.9 mmol/L). Multivariable logistic regression was used to establish a full model and a subsequently reduced model using the backward elimination method. We demonstrated the model performance using the area under the receiver operating characteristic curve (AuROC), calibration plot, and Hosmer-Lemeshow goodness-of-fit test. Internal validation was done with a bootstrap sampling procedure with 1000 replicates. Model optimism was estimated.

resultsThree hundred and eighty-five patients were included, with 97 posttreatment hypoglycemia (25.2%). The predictive model comprised the following three criteria: age > 60 years old, pretreatment blood glucose ≤ 100 mg/dL (≤ 5.6 mmol/L), and pretreatment potassium > 6 mmol/L. The AuROC of this model was 0.671 (95% confidence interval [CI] 0.608 to 0.735). The calibration plot demonstrated consistency with the original data. Hosmer-Lemeshow goodness-of-fit test showed no evidence of lack-of-fit (p 0.792); therefore, the model was also fit to the original data. Internal validation via bootstrap sampling showed a consistent AuROC of 0.670 (95% CI 0.660 to 0.670) with minimal model optimism. A high risk for posttreatment hypoglycemia was indicated if the patient met at least one of those criteria. Sensitivity and specificity were 95.9% and 14.9%, respectively.

conclusionHigh risk was indicated when at least one of the criteria was met: age > 60 years old, pretreatment blood glucose ≤ 100 mg/dL (≤ 5.6 mmol/L), and pretreatment potassium > 6 mmol/L. Blood glucose levels should frequently check in the high-risk group.

trial registrationTCTR20210225002 ( www.thaiclinicaltrials.org ).

Indexed as

HyperkalemiaHypoglycemiaAdolescentBlood GlucoseFemaleGlucoseHumansInsulinMiddle AgedPotassiumPregnancyRetrospective StudiesBlood GlucoseGlucoseInsulinPotassiumHyperkalemiaHypoglycemiaInsulinPrediction

Identifiers

PMID36371171
PMCPMC9652909
OpenAlexW4309073101

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.