Evidence map›Paper›PMID 39375618›Full record

ArticleBMC gastroenterology2024

Nucleated red blood cell distribution in critically ill patients with acute pancreatitis: a retrospective cohort study.

Huan-Qin Liu, Guan-Qun Wang, Cheng-Shuang Zhang, Xia Wang, Ji-Kui Shi, Feng Qu, Hang Ruan

Abstract read
In one paragraph

Article in BMC gastroenterology, 2024. 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

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

3 citing papers in PubMed.

  1. Nucleated Red Blood Cells for Predicting Mortality in Intensive Care Unit Patients With Sepsis.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Article
  2. Article
  3. 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

7 authors.

Huan-Qin LiuDepartment of Critical-care Medicine, Jining NO.1 People's Hospital, Jining, 272000, Shandong Province, China.
Guan-Qun WangDepartment of Critical-care Medicine, Jining NO.1 People's Hospital, Jining, 272000, Shandong Province, China.
Cheng-Shuang ZhangDepartment of Critical-care Medicine, Jining NO.1 People's Hospital, Jining, 272000, Shandong Province, China.
Xia WangDepartment of Critical-care Medicine, Jining NO.1 People's Hospital, Jining, 272000, Shandong Province, China.
Ji-Kui ShiDepartment of Critical-care Medicine, Jining NO.1 People's Hospital, Jining, 272000, Shandong Province, China. sjkjnrmyy@126.com.
Feng QuDepartment of Critical-care Medicine, Jining NO.1 People's Hospital, Jining, 272000, Shandong Province, China. rmyyzzeq@163.com.
Hang RuanDepartment of Critical-care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei Province, China.

Funding

Medical and Health Science and Technology Development Project of Shandong Province 202319010449
6 · The paper itself

Abstract

objectivesThis study examined the potential association between nucleated red blood cell (NRBC) levels and mortality in critically ill patients with acute pancreatitis (AP) in the intensive care unit, due to limited existing research on this correlation.

methodsThis retrospective cohort study utilized data from the MIMIC-IV v2.0 and MIMIC-III v1.4 databases to investigate the potential relationship between NRBC levels and patient outcomes. The study employed restricted cubic splines (RCS) regression analysis to explore non-linear associations. The impact of NRBC on prognosis was assessed using a generalized linear model (GLM) with a logit link, adjusted for potential confounders. Furthermore, four machine learning models, including Gradient Boosting Classifier (GBC), Random Forest, Gaussian Naive Bayes, and Decision Tree Classifier model, were constructed using NRBC data to generate risk scores and evaluate the potential of NRBC in predicting patient prognosis.

resultsA total of 354 patients were enrolled in the study, with 162 (45.8%) individuals aged 60 years or older and 204 (57.6%) males. RCS regression analysis demonstrated a non-linear relationship between NRBC levels and 90-day mortality. Receiver Operating Characteristic (ROC) analysis identified a 1.7% NRBC cutoff to distinguish survivor from non-survivor patients for 90-day mortality, yielding an Area Under the Curve (AUC) of 0.599, with a sensitivity of 0.475 and specificity of 0.711. Elevated NRBC levels were associated with increased risks of 90-day mortality in both unadjusted and adjusted models (all Odds Ratios > 1, P < 0.05). Assessment of various machine learning models with nine variables, including NRBC, Sex, Age, Simplified Acute Physiology Score II, Acute Physiology Score III, Congestive Heart Failure, Vasopressin, Norepinephrine, and Mean Arterial Pressure, indicated that the GBC model displayed the highest predictive accuracy for 90-day mortality, with an AUC of 0.982 (95% CI 0.970-0.994). Post hoc power analysis showed a statistical power of 0.880 in the study.

conclusionsElevated levels of NRBC are linked to an increased mortality risk in critically ill patients with AP, suggesting its potential for predicting mortality.

Indexed as

Critical IllnessErythroblastsMachine LearningPancreatitisAdultAgedFemaleHumansIntensive Care UnitsMaleMiddle AgedPrognosisRetrospective StudiesROC CurveAcute PancreatitisCohort studyCritical careNucleated red blood cellRisk factors

Identifiers

PMID39375618
PMCPMC11460230

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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.