Post-discharge Follow-up of Standardized Management for Patients with Post-stroke Cognitive Impairment.
Bibliographic record
Abstract
Context: Severe cases of stroke can lead to cognitive impairment or even dementia. The most critical factor related to cognitive impairment after strokes is patients' lack of understanding about or attention to their conditions. Strengthening standardized management post-stroke has become a common goal for clinical workers and patients. Objective: The study intended to explore, during post-discharge follow-up, the effectiveness of standardized management of patients with post-stroke cognitive impairment, which could provide guidance for patients and doctors to improve patients' follow-up plans. Design: The research team conducted a randomized controlled trial. Setting: The study took place at Huangshi Central Hospital, an Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, in Huangshi, Hubei, China. Participants: Participants were 112 patients with post-stroke cognitive impairment at the hospital between February 2021 and March 2023. Intervention: The research team randomly divided the participants into two groups, using a random-number-table method: (1) a control group with 56 participants who received routine management and (2) an intervention group with 56 participants who received standardized management. Outcome Measures: At baseline and 6 months postintervention, the research team measured participants': (1) cognitive function using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), (2) quality of life (QoL) using the World Health Organization Quality of Life-Bref (WHOQOL-BREF) questionnaire, and (3) self-efficacy using the General Self-Efficacy Scale (GSES). At one and 6 months postintervention, the team analyzed participants' medication adherence using the Morisky Medication Adherence Scale (MMAS-8). Results: At baseline, no significant difference (P > .05) existed between the groups in the scores: (1) for cognitive function on the MMSE or MoCA, (2) for the physiological, psychological, social, and environmental domains and the total score on the WHOQOL-BREF, or (3) for self-efficacy on the GSES scores. At 6 months postintervention, the intervention group's scores were significantly higher than those of the control group: (1) on the MMSE and MoCA (both P < .001), (2) on the four domains and total score on the WHOQOL-BREF (all P < .001), and (3) on the GSES (P < .001). At one month and six months postintervention, the intervention group's score for medication adherence on the MMAS-8 was significantly higher than those of the control group (both P < .001). Conclusions: Standardized management for patients with post-stroke cognitive impairment provided beneficial outcomes in improving their cognitive function, QoL, self-efficacy, and medication adherence, and the research team highly recommends it for wide application in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".