Evidence map›Paper›PMID 37712097›Full record

ArticleOrthopaedic surgery2023

Risk Factors for Significant Intraoperative Blood Loss during Anterior Cervical Decompression and Fusion for Degenerative Cervical Diseases.

Hong Yuan, Yuanhang Zhao, Yin Hu, Zhonghua Liu, Yu Chen, Hongwei Wang, Hailong Yu, Liangbi Xiang

Open access · goldAbstract read
In one paragraph

Article in Orthopaedic surgery, 2023. 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
0.6field-weighted citation impact, top 29% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Predicting intraoperative blood loss using cervical vertebral bone quality scores in cervical corpectomy and fusion procedure.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 · 2026
    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

8 authors at 1 institution in 1 country.

Hong YuanDepartment of Orthopaedics, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.
Yuanhang ZhaoDepartment of Orthopaedics, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.
Yin HuDepartment of Orthopaedics, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.
Zhonghua LiuDepartment of Anesthesiology, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.
Yu ChenDepartment of Orthopaedics, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.
Hongwei WangDepartment of Orthopaedics, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.ORCID https://orcid.org/0000-0002-2367-3465
Hailong YuDepartment of Orthopaedics, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.
Liangbi XiangDepartment of Orthopaedics, General Hospital of Northern Theater Command of Chinese PLA, Shenyang, China.
General Hospital of Shenyang Military Region · CN

Funding

Applied Basic Research Project of Liaoning Province 2020JH2/10300157Applied Basic Research Project of Liaoning Province 2022JH2/101300024the Shenyang Science and Technology Project 22-321-33-35
6 · The paper itself

Abstract

objectivesAnterior cervical decompression and fusion (ACF) has become a widely accepted surgical treatment for degenerative cervical diseases, but occasionally, significant intraoperative blood loss (SIBL), which is defined as IBL of 500 mL or more, will occur. We aimed to investigate the independent risk factors for SIBL during ACF for degenerative cervical diseases.

methodsWe enrolled 1150 patients who underwent ACF for degenerative cervical diseases at our hospital between 2013 and 2019. The patients were divided into two groups: the SIBL group (n = 38) and the non-SIBL group (n = 1112). Demographic, surgical and radiographic data were recorded prospectively to investigate the independent risk factors for SIBL. For counting data, the chi-square test or Fisher's exact probability test was used. Student's t-test or the Mann-Whitney rank sum test was used for comparisons between groups of measurement data. Univariate analysis and multivariate logistic regression analysis were further used to analyze the significance of potential risk factors.

resultsThe incidence of SIBL during ACF was 3.3% (38/1150). A multivariate analysis revealed that female sex (odds ratio [OR], 6.285; 95% confidence interval [CI], 2.707-14.595; p < 0.001), corpectomy (OR, 3.872; 95% CI, 1.616-9.275; p = 0.002), duration of operation ≥150 min (OR, 8.899; 95% CI, 4.042-19.590; p < 0.001), C3 involvement (OR, 4.116; 95% CI, 1.808-9.369; p = 0.001) and ossification of posterior longitudinal ligament (OPLL) at the surgical level (OR, 6.007; 95% CI, 2.218-16.270; p < 0.001) were independent risk factors for SIBL. Patients with SIBL had more days of first-degree/intensive nursing (p = 0.003), longer length of stay (p = 0.003) and higher hospitalization costs (p = 0.023).

conclusionFemale sex, corpectomy, duration of operation, C3 involvement and OPLL at the surgical level were independent risk factors for SIBL during ACF. SIBL in ACF was associated with more days of first-degree/intensive nursing, longer length of stay and higher hospitalization costs.

Indexed as

Ossification of Posterior Longitudinal LigamentSpinal FusionBlood Loss, SurgicalCervical VertebraeDecompression, SurgicalFemaleHumansRetrospective StudiesRisk FactorsTreatment OutcomeAnterior cervical decompression and fusionRisk factorsSignificant intraoperative blood loss

Identifiers

PMID37712097
PMCPMC10622266
OpenAlexW4386758099

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.