Evidence map›Paper›PMID 34322317›Full record

ArticlePeerJ2021

Development of a preoperative index-based nomogram for the prediction of hypokalemia in patients with pituitary adenoma: a retrospective cohort study.

Wenpeng Li, Lexiang Zeng, Deping Han, Shanyi Zhang, Bingxi Lei, Meiguang Zheng, Yuefei Deng, Lili You

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 49% 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

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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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

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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

8 authors at 2 institutions in 1 country.

Wenpeng Li *Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Lexiang Zeng *Pediatric Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Deping HanNeurosurgery, JieXi People's Hospital, JieXi, China.
Shanyi ZhangNeurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Bingxi LeiNeurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Meiguang ZhengNeurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Yuefei DengNeurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Lili YouEndocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Sun Yat-sen Memorial Hospital · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and validate a preoperative index-based nomogram for the prediction of hypokalemia in patients with pituitary adenoma (PA).

methodsThis retrospective cohort study included 205 patients with PAs between January 2013 and April 2020 in the Sun Yat-sen Memorial Hospital, Guangzhou, China. The patients were randomly classified into either a training set (

resultsThe incidence of hypokalemia was 38.05%. Seven preoperative indices were identified for the construction of the nomogram: age, type of PA, weight, activated partial thromboplastin time, urea, eosinophil percentage, and plateletocrit. The AUCs of the nomogram for predicting hypokalemia were 0.856 (95% CI [0.796-0.915]) and 0.652 (95% CI [0.514-0.790]) in the training and validation sets, respectively. Restricted cubic splines demonstrated that there was no nonlinear association between hypokalemia and the selected variables.

conclusionIn this study, we constructed a preoperative indices-based nomogram that can assess the risk of hypokalemia after the surgical treatment of pituitary adenomas. This nomogram may also help to identify high risk patients who require close monitoring of serum potassium.

Indexed as

NomogramPituitary adenomaPostoperative hypokalemiaPreoperative index

Identifiers

PMID34322317
PMCPMC8297473
OpenAlexW3185666174

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LicenceCC BY
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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.