Abstract 17: Association Between Pre-stroke Depression and Patient Reported Outcomes After Acute Ischemic Stroke
Bibliographic record
Abstract
Background: Post-stroke depression has been shown to have a negative impact on patients’ quality of life but data regarding the relationship between pre-stroke depression and post-stroke outcomes are lacking. Methods: Patient reported outcome measures (PROMS) were prospectively collected (January 2014 – December 2014) as a part of PROSPER, a PCORI-funded study designed by researchers and stroke survivors to evaluate the effectiveness of therapies post-stroke. PROMS evaluated in the study included modified Rankin Scale (mRS) assessed at discharge, 3 months and 6 months post-discharge. EuroQual-5D-3L (EQ-5D-3L), EuroQual Visual Analog Scale (EQ-VAS), Patient Health Questionnaire-2 (PHQ-2), Stroke Impact Scale-16 (SIS-16), and Fatigue Severity Scale (FSS) were assessed at 3 months and 6 months post-discharge. Pre-stroke depression was identified from patient medical history. Validated dichotomized endpoints were used to create regression models to examine association of pre-stroke depression with PROMS. Results: Of 1,617 enrolled patients at 60 hospitals, 185 (11.4%) had pre-stroke depression. Patients with documented pre-stroke depression were more likely to be white, female and have a higher prevalence of cardiovascular risk factors than those without pre-stroke depression. While both cohorts had similar stroke severity and functional status at discharge, patients with pre-stroke depression had significantly worse PROMS at 3 months and 6 months post-discharge. Pre-stroke depression was associated with 56% higher odds of functional decline between 3 months and 6 months post-discharge with greater negative impact of stroke on patient’s health and life, and with increased likelihood of reporting severe fatigue during stroke recovery (Table 1). Conclusions: Pre-stroke depression is associated with worse patient reported outcomes and greater odds of functional decline after ischemic stroke discharge. Strategies to more effectively manage comorbid depression and improve outcomes in these patients are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".