Evidence map›Paper›PMID 36200336›Full record

ArticleInternational wound journal2023

A nomogram for accurately predicting the surgical site infection following transforaminal lumbar interbody fusion in type 2 diabetes patients, based on glycemic variability.

Hang Liu, Wei Zhang, Qiang Hu, Lei Liu, Zhiyang Xie, Yuzhu Xu, Genyang Jing, Yuntao Wang

Open access · goldAbstract read
In one paragraph

Article in International wound journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Development of a risk scoring system for surgical site infection after lumbar surgery using Dixon MRI and clinical parameters.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025
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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

8 authors at 2 institutions in 1 country.

Hang LiuDepartment of Orthopedics, The 904th Hospital of PLA Joint Logistic Support Force, Wuxi, China.ORCID https://orcid.org/0000-0003-3699-9314
Wei ZhangDepartment of Spinal Surgery, The Affiliated Zhongda Hospital of Southeast University, Nanjing, China.
Qiang HuDepartment of Spinal Surgery, The Affiliated Zhongda Hospital of Southeast University, Nanjing, China.
Lei LiuDepartment of Spinal Surgery, The Affiliated Zhongda Hospital of Southeast University, Nanjing, China.
Zhiyang XieDepartment of Spinal Surgery, The Affiliated Zhongda Hospital of Southeast University, Nanjing, China.
Yuzhu XuDepartment of Spinal Surgery, The Affiliated Zhongda Hospital of Southeast University, Nanjing, China.
Genyang JingDepartment of Orthopedics, The 904th Hospital of PLA Joint Logistic Support Force, Wuxi, China.
Yuntao WangDepartment of Spinal Surgery, The Affiliated Zhongda Hospital of Southeast University, Nanjing, China.
Zhongda Hospital Southeast University · CN81th Hospital of PLA · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surgical site infection (SSI) is a common and serious complication of transforaminal lumbar interbody fusion (TLIF), and the occurrence of SSI usually leads to prolonged hospitalisation, increased medical costs, poor prognosis, and even death. The objectives of this study were to compare the incidence of SSI in patients with type 2 diabetes, investigate the correlation between perioperative glycemic variability and postoperative SSI, and develop a nomogram model to predict the risk of SSI. This study retrospectively analysed 339 patients with type 2 diabetes who underwent TLIF in the spinal surgery department of the Affiliated Zhongda Hospital of Southeast University from January 2018 to September 2021. The medical records of all patients were collected, and postoperative infection cases were determined according to the diagnostic criteria of surgical site infection. The risk factors for postoperative SSI were analysed by univariate and multivariate logistic regression. And Nomogram prediction model was established and validated. The nomogram incorporated seven independent predictors. Preoperative FPG-CV was the most important independent risk predictor of SSI, followed by preoperative MFBG, duration of drain placement, postoperative FPG-CV, preoperative blood glucose control scheme, duration of diabetes >5 years, and the number of fused vertebrae ≥2. The nomogram showed good diagnostic accuracy for the SS of both the training cohort and the validation cohort (AUC = 0.915 and AUC = 0.890). The calibration curves for the two cohorts both showed optimal agreement between nomogram prediction and actual observation. In conclusion, preoperative and postoperative glycemic variability is closely related to the occurrence of SSI. We developed and validated a nomogram to accurately predict the risk of SSI after TLIF surgery. It's helpful for spinal surgeons to formulate reasonable treatment plans and prevention strategies for type 2 diabetes patients.

Indexed as

Diabetes Mellitus, Type 2Spinal FusionHumansLumbar VertebraeNomogramsRetrospective StudiesSurgical Wound Infectiondiabetes mellitusglycemic variabilitylumbar fusionnomogramsurgical site infection

Identifiers

PMID36200336
PMCPMC10031251
OpenAlexW4302288013

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.