Evidence map›Paper›PMID 36225784›Full record

ArticleFrontiers in public health2022

Tree-based, two-stage risk factor analysis for postoperative sepsis based on Sepsis-3 criteria in elderly patients: A retrospective cohort study.

Xiaorong Peng, Chaojin Chen, Jingjing Chen, Yanlin Wang, Duo Yang, Chuzhou Ma, Zifeng Liu, Shaoli Zhou, Ziqing Hei

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 7 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

9 authors at 4 institutions in 1 country.

Xiaorong PengDepartment of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Chaojin ChenDepartment of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Jingjing ChenBig Data and Artificial Intelligence Center, The Third Hospital of Sun Yat-sen University, Guangzhou, China.
Yanlin WangDepartment of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Duo YangDepartment of Anesthesiology, Jieyang People's Hospital, Jieyang, China.
Chuzhou MaDepartment of Anesthesiology, Shantou Central Hospital, Shantou, China.
Zifeng LiuBig Data and Artificial Intelligence Center, The Third Hospital of Sun Yat-sen University, Guangzhou, China.
Shaoli ZhouDepartment of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Ziqing HeiDepartment of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Third Affiliated Hospital of Sun Yat-sen University · CNSun Yat-sen University · CNPeople 's Hospital of Jilin Province · CNShantou Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis remains the leading cause of postoperative death in elderly patients and is defined as organ dysfunction with proven or suspected infection according to Sepsis-3 criteria. To better avoid potential non-linear associations between the risk factors, we firstly used a tree-based analytic methods to explore the putative risk factors of geriatric sepsis based on the criteria in the study. Methods: Data of 7,302 surgical patients aged ≥ 65 years at the Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were collected. An analytic method that combined tree-based analysis with the method of Mantel-Haenszel and logistic regression was adopted to assess the association between 17 putative risk factors and postoperative sepsis defined by the Sepsis-3 guideline by controlling 16 potential confounding factors. Results: Among the 16 potential covariates, six major confounders were statistically identified by the tree-based model, including cerebrovascular diseases, preoperative infusion of red blood cells, pneumonia, age ≥ 75, malignant tumor and diabetes. Our analysis indicated that emergency surgery increases the risk of postoperative sepsis in elderly patients by more than six times. The type of surgery is also a crucial risk factor for sepsis, particularly transplantation and neurosurgery. Other risk factors were duration of surgery > 120 min, administration of steroids, hypoalbuminemia, elevated creatinine, blood urea nitrogen, hematocrit, platelets, glucose, white blood cell count, abnormal neutrophil-to-lymphocyte ratio and elevated hsCRP-to-albumin ratio. Conclusions: Our study uses an effective method to explore some risk factors for postoperative sepsis in elderly by adjusting many potential confounders and it can provide information for intervention design.

Indexed as

C-Reactive ProteinSepsisAgedCreatinineFactor Analysis, StatisticalGlucoseHumansPostoperative ComplicationsRetrospective StudiesRisk FactorsC-Reactive ProteinCreatinineGlucoseclassification and regression treeelderlyrisk factorssepsistree-based analysis

Identifiers

PMID36225784
PMCPMC9550002
OpenAlexW4297201642

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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.