serum leptin, neuron specific enolase and s-100b in relation to post-stroke depression in a prospective nested case-control study

serum leptin, neuron specific enolase and s-100b in relation to post-stroke depression in a prospective nested case-control study

;Mei-ying ZHAO;Run-qing WANG;Wei LIU;Jie ZHAO;Juan LV;Jiang-tao LI
frontiers in neurorobotics 2015 Vol. 40 pp. 226-230
181
zhao2015medicalserum

Abstract

Objective To investigate the relationship between the serum levels of leptin, neuron-specific enolase (NSE) and S-100B in patients of stroke and the incidence of post-stroke depression (PSD). Methods The clinical data of 121 cases of acute ischemic stroke, admitted to Zhengzhou Central Hospital affiliated to Zhengzhou University from Jun. 2010 to Dec. 2012, were retrospectively analyzed. After six months of follow-up 42 patients were diagnosed as suffering from PSD (Hamilton Depression Scale score ≥8). Another 42 participants with available matching data on onset time, age, gender and lesions of brain were selected. The serum samples were collected from all patients at time of discharge, and the concentrations of serum leptin, NSE and S-100B were analyzed by enzyme-linked immunosorbent assay (ELISA) kit. Correlation and efficiency of diagnosing PSD among them was validated by receptor operator curve (ROC). Results The concentration of serum leptin, NSE, and S-100B in PSD group (25.84±13.80, 2.59±1.48 and 25.03±8.24μg/L, respectively) was higher than that in the control group (8.67±6.17, 2.27±1.84 and 22.40±6.84μg/L, respectively). No obvious correlation was found between serum leptin and the NSE and S-100B in PSD patients. Based on the ROC curve, the area under the curve of serum leptin in PSD patients was 0.935 (95%CI 0.885-0.984), and the optimal cutoff value of serum leptin level was 16.17μg/L, which was an indicator for predicting of PSD with 81.0% sensitivity and 90.1% specificity. Conclusion Elevation of serum leptin level at admission was found to be associated with PSD, and it may act as a new marker for predicting the occurrence of PSD. DOI: 10.11855/j.issn.0577-7402.2015.03.11

Keywords

Citation

ID: 188986
Ref Key: zhao2015medicalserum
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
188986
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet