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Record W2059713152 · doi:10.1186/1471-244x-13-164

Predictors of early post ischemic stroke apathy and depression: a cross-sectional study

2013· article· en· W2059713152 on OpenAlexaboutno aff
Songran Yang, Ping Hua, Xin-yuan Shang, Rong Hu, Xiao-en Mo, Xiaoping Pan

Bibliographic record

VenueBMC Psychiatry · 2013
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsApathyHamdDepression (economics)Stroke (engine)Montreal Cognitive AssessmentLogistic regressionRating scaleDementiaPsychologyPsychiatryMedicineMini–Mental State ExaminationPhysical therapyClinical psychologyInternal medicineCognitionAnxietyDiseaseDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Apathy and depression are important neuropsychiatric disorders that can occur after a stroke but the etiology and risk factors are not well understood. The purpose of this study was to identify risk factors for apathy and depression following a stroke. METHODS: Patients with an acute stroke who met the inclusion criteria were recruited from our hospital, and general information was recorded from patient charts. The Apathy Evaluation Scale, Clinician Version (AES-C) was used to evaluate these patients within 2 weeks after the stroke. The Montreal Cognitive Assessment (MoCA), mini-mental state examination (MMSE), Hamilton Depression Scale (HAMD), Mattis Dementia Rating Scale Initiation/Perseveration subset (MDRS I/P), Frontal Assessment Battery (FAB) and Stroop Color-Word Association Test were employed to evaluate emotion, cognitive function and executive function. The patients were divided into two groups: the apathy group and the non-apathy group. We also divided the patients into two groups based on whether or not they had post-stroke depression. The clinical characteristics and scores on the MoCA, MMSE, HAMD and MDRS I/P were compared between the apathy and non-apathy groups as well as between patients with and without depression. Logistic regression analysis was performed to identify risk factors for apathy and depression following a stroke. RESULTS: A total of 75 patients with acute stroke were recruited. Of these, 25 (33.3%) developed apathy and 12 (16%) developed depression. Multivariate logistic regression analysis indicated that a history of cerebrovascular disease (OR: 6.45, 95% CI: 1.48-28.05, P = 0.013), low HbA1c (OR: 0.31, 95% CI: 0.12-0.81, P = 0.017) and a low MDRS I/P score (OR: 0.84, 95% CI: 0.74, 0.96, P = 0.010) were risk factors for post-stroke apathy. Additionally, multivariate logistic regression indicated that a low MDRS I/P (OR: 0.85, 95% CI: 0.75, 0.97, P = 0.015) was associated with post-stroke depression. CONCLUSIONS: Three risk factors for post-stroke apathy were identified as a history of cerebrovascular disease, low HbA1c and lower MDRS I/P scores. A low MDRS I/P score was also identified as a risk factor for post-stroke depression. These results may be useful to clinicians in recognizing and treating apathy and depression in patients after a stroke.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.280
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2013
Admission routes1
Has abstractyes

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