Evidence map›Paper›PMID 37393302›Full record

ArticleBMC surgery2023

Development of a nomogram for the prediction of complicated appendicitis during pregnancy.

Xiaosong Zheng, Xiaojun He

Abstract read
In one paragraph

Article in BMC surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

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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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Nomogram for predicting opioid-induced nausea and vomiting for cancer pain patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    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

2 authors.

Xiaosong ZhengDepartment of General Surgery, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, NO.745 Wuluo Road, Hongshan District, Wuhan City, Hubei Province, 430070, P.R. China.
Xiaojun HeDepartment of General Surgery, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, NO.745 Wuluo Road, Hongshan District, Wuhan City, Hubei Province, 430070, P.R. China. hexjdoctor@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComplicated appendicitis during pregnancy directly affects the clinical prognosis of both mother and fetus. However, accurate identification of complicated appendicitis in pregnancy is fraught with various challenges. The purpose of this study was to identify the risk factors and to develop a useful nomogram to predict complicated appendicitis during pregnancy.

methodsThis retrospective study involved pregnant women who underwent appendectomy at the Maternal and Child Health Hospital of Hubei Provincial from May 2016 to May 2022 and who ultimately had histopathological confirmed acute appendicitis. Univariate and multivariate logistic regression were applied to analyze clinical parameters and imaging features as a way to identify risk factors. Then, nomogram and scoring systems predicting complicated appendicitis in pregnancy were constructed and evaluated. Finally, the potential non-linear association between risk factors and complicated appendicitis was analyzed using restricted cubic splines.

resultsThree indicators were finally identified for the construction of the nomogram: gestational weeks, C-reactive protein (CRP), and neutrophil percentage (NEUT%). To improve the clinical utility, the gestational weeks were divided into three periods (first trimesters, second trimesters, and third trimesters), while the optimal cut-offs for CRP level and NEUT% were found to be 34.82 mg/L and 85.35%, respectively. Multivariate regression analysis showed that third trimesters (P = 0.013, OR = 16.81), CRP level ≥ 34.82 mg/L (P = 0.007, OR = 6.24) and NEUT% ≥85.35% (P = 0.011, OR = 18.05) were independent risk factors for complicated appendicitis. The area under the ROC curve (AUC) of the nomogram predicting complicated appendicitis in pregnancy was 0.872 (95% CI: 0.803-0.942). In addition, the model was shown to have excellent predictive performance by plotting calibration plots, Decision Curve Analysis (DCA), and clinical impact curves. When the optimal cut-off point of the scoring system was set at 12, the corresponding AUC, sensitivity, specificity, Positive Likelihood Ratio (PLR), Negative Likelihood Ratio (NLR), Positive Predictive Value (PPV), and Negative Predictive Value (NPV) values were AUC: 0.869(95% CI: 0.799-0.939),100%, 58.60%, 2.41, 0, 42%, and 100%, respectively. The restricted cubic splines revealed a linear relationship between these predictors and complicated appendicitis during pregnancy.

conclusionsThe nomogram utilizes a minimum number of variables to develop an optimal predictive model. Using this model, the risk of developing complicated appendicitis in individual patients can be determined so that reasonable treatment choices can be made.

Indexed as

AppendicitisNomogramsAppendectomyChildC-Reactive ProteinFemaleHumansPregnancyRetrospective StudiesC-Reactive ProteinComplicated appendicitisNomogramPregnancy

Identifiers

PMID37393302
PMCPMC10315032

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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.