Evidence map›Paper›PMID 36009095›Full record

ArticleBrain sciences2022

Higher Plasma Fibrinogen Level at Admission Is Associated with Post-Stroke Depression at Discharge.

Juehua Zhu, Li Wang, Han Shao, Xiang Tang, Lulu Zhang, Yun Zhou, Yongjun Jiang, Qi Fang, Xiuying Cai

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 25% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. 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

9 authors at 2 institutions in 1 country.

Juehua ZhuDepartment of Neurology, The First Affiliated Hospital of SooChow University, Suzhou 215006, China.ORCID 0000-0002-5174-6887
Li WangDepartment of Neurology, Zhangjianggang Fifith People's Hospital, Suzhou 215600, China.
Han ShaoDepartment of Neurology, The First Affiliated Hospital of SooChow University, Suzhou 215006, China.
Xiang TangDepartment of Neurology, The First Affiliated Hospital of SooChow University, Suzhou 215006, China.
Lulu ZhangDepartment of Neurology, The First Affiliated Hospital of SooChow University, Suzhou 215006, China.
Yun ZhouDepartment of Neurology, The First Affiliated Hospital of SooChow University, Suzhou 215006, China.
Yongjun JiangDepartment of Neurology, The Second Affiliated Hospital of Guangzhou Medical University, 250 Changgang East Road, Guangzhou 510260, China.
Qi FangDepartment of Neurology, The First Affiliated Hospital of SooChow University, Suzhou 215006, China.
Xiuying CaiDepartment of Neurology, The First Affiliated Hospital of SooChow University, Suzhou 215006, China.ORCID 0000-0002-3496-3281
Soochow University · CNSecond Affiliated Hospital of Guangzhou Medical University · CN

Funding

National Natural Science Foundation of China 82071300National Natural Science Foundation of China 8271282
6 · The paper itself

Abstract

Background: Post-stroke depression (PSD) is a common complication of stroke, which seriously affects the functional outcome of patients. Systemic low-grade inflammation associated with PSD has been shown to occur at several months to years, however, whether these inflammatory markers predicted PSD at an acute stage of stroke is controversial. Method: A total of 625 patients with acute ischemic stroke (219 female, 35.40%) were included in this study. PSD was diagnosed using the 17-item Hamilton depression scale (HAMD) at 7 days following discharge (7−14 days after stroke onset). Multivariable logistic regression analysis was applied to build a prediction model for PSD at discharge. Discrimination and calibration of the model were assessed by C-index, calibration plot. Internal validation was conducted using bootstrapping validation. Results: At discharge of hospitalization, 95 patients (15.20%) were diagnosed with PSD. Multivariable logistic regression suggested that female gender (OR = 2.043, 95% CI = 1.287−3.245, p = 0.002), baseline NIHSS (OR = 1.108, 95% CI = 1.055−1.165, p < 0.001) and fibrinogen (OR = 1.388, 95% CI = 1.129−1.706, p = 0.002) were independent predictors for PSD at discharge. The cut-off of the fibrinogen plasma level was 3.08 g/L. These predictors were included in the nomogram. The model displayed good discrimination, with a C-index of 0.730 (95% CI = 0.683−0.777) and good calibration. Conclusion: Female gender, baseline stroke severity and a higher level of fibrinogen were independently associated with PSD at discharge. A nomogram based on these three predictors can be used to provide an individual, visual prediction of the risk probability of PSD.

Indexed as

fibrinogengenderinflammationpost-stroke depression

Identifiers

PMID36009095
PMCPMC9405685
OpenAlexW4289705098

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.