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Saccade Tasks: A Noninvasive Approach for Predicting Postoperative Delirium in Elderly Arthroplasty Patients
Meng Kang, Xuan Lai, Junru Wu, Xiang Qian, Li‐Wen Chen, Xiang Li, J.Z. Su, Zhe Ma et al.. Anesthesiology, 2025-12-04
Topic: Risk, prevention and care in population studies
The incidence of POD was 8.2% (26 of 316). The MMSE and MoCA scales, serum neurofilament light chain levels, and five saccadic parameters values (reaction time, primary saccade error, saccadic gains in pro-saccades; peak velocity in anti-saccades and memory-guided saccades) differed significantly ( P < 0.05) between POD and non-POD participants. The logistic regression classifier model revealed higher predictive accuracy when using saccadic parameters (area under the receiver operating characteristic curve [AUROC], 0.81; 95% CI, 0.70 to 0.92) than when using MMSE and MoCA scores (AUROC, 0.64; 95% CI, 0.53 to 0.76) or neurofilament light chain levels (AUROC, 0.61; 95% CI, 0.50 to 0.72). The multilayer perceptron machine learning classifier model further increased the accuracy (AUROC, 0.89; 95% CI, 0.82 to 0.94) by using saccadic parameters to predict POD occurrence. Saccadic parameters exhibited higher accuracy in predicting the occurrence of POD than MMSE and MoCA scores and molecular test results. Therefore, saccadic parameters may serve as a complementary behavioral biomarker for predicting the occurrence of POD in elderly arthroplasty patients.
Key findings
- The incidence of POD was 8.2% (26 of 316).
- The MMSE and MoCA scales, serum neurofilament light chain levels, and five saccadic parameters values (reaction time, primary saccade error, saccadic gains in pro-saccades; peak velocity in anti-saccades and memory-guided saccades) differed significantly ( P < 0.05) between POD and non-POD participants.
- The logistic regression classifier model revealed higher predictive accuracy when using saccadic parameters (area under the receiver operating characteristic curve [AUROC], 0.81; 95% CI, 0.70 to 0.92) than when using MMSE and MoCA scores (AUROC, 0.64; 95% CI, 0.53 to 0.76) or neurofilament light chain levels (AUROC, 0.61; 95% CI, 0.50 to 0.72).
- The multilayer perceptron machine learning classifier model further increased the accuracy (AUROC, 0.89; 95% CI, 0.82 to 0.94) by using saccadic parameters to predict POD occurrence.
- Saccadic parameters exhibited higher accuracy in predicting the occurrence of POD than MMSE and MoCA scores and molecular test results.
Why it matters
This study found that saccadic eye movement parameters predicted postoperative delirium in elderly arthroplasty patients more accurately than MMSE and MoCA scores or neurofilament light chain levels. It suggests saccadic parameters may serve as a complementary behavioural biomarker for predicting postoperative delirium.
Study details
- Participants316
- Effect size8.2%
- Evidence strengthLow
How this study scored 45/100
Published in a peer-reviewed journal. Scored zero for study design and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Anesthesiology) |
| Journal's citation record | 3 / 4 | Anesthesiology: journal h-index 368 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 2 / 4 | 316 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 3 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 2.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Yongzheng Han: h-index 15 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Peking University: institution h-index 1,098 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41344677) |
| Free to read | 2 / 2 | Free to read |
| Total | 45 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1097/aln.0000000000005875
- PubMed: 41344677
- Original source →
- Free full text: Anesthesiology →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Kang, M., Lai, X., Wu, J., Qian, X., Chen, L., Li, X., et al. (2025). Saccade Tasks: A Noninvasive Approach for Predicting Postoperative Delirium in Elderly Arthroplasty Patients. Anesthesiology. https://doi.org/10.1097/aln.0000000000005875
Vancouver
Kang M, Lai X, Wu J, Qian X, Chen L, Li X, et al. Saccade Tasks: A Noninvasive Approach for Predicting Postoperative Delirium in Elderly Arthroplasty Patients. Anesthesiology. 2025. doi:10.1097/aln.0000000000005875. PMID: 41344677.
BibTeX
@article{kang2025-41344677,
author = {Kang, Meng and Lai, Xuan and Wu, Junru and Qian, Xiang and Chen, Li‐Wen and Li, Xiang and Su, J.Z. and Ma, Zhe and others},
title = {{Saccade Tasks: A Noninvasive Approach for Predicting Postoperative Delirium in Elderly Arthroplasty Patients}},
journal = {Anesthesiology},
year = {2025},
doi = {10.1097/aln.0000000000005875},
pmid = {41344677},
url = {https://doi.org/10.1097/aln.0000000000005875}
}
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