Influence of family follow up grading nursing on patients with Parkinson’s disease at home
Bibliographic record
Abstract
Abstract Objective:To observe the influence of family follow up grading nursing on motor and non motor symptoms,mental status and quality of life in patients with Parkinson’s disease at home.Methods:A total of 160 patients with Parkinson’s disease were randomly divided into routine group and intervention group,80 cases in each group.The patients in routine nursing group were given routine nursing,and the patients in intervention group were given family followup grading nursing.The motor symptoms,non motor symptoms,social activities,activities of daily living and quality of life of patients in the two groups were compared before and after the intervention 6 months.Meanwhile,the compliance and nursing service satisfaction of the two groups were investigated.Results:The Montreal Cognitive Assessment(MoCA) score was significantly higher than that before intervention,Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),social function(Functional Activities Questionnaire,FAQ),Scales for Outcomes in Parkinson’s DiseaseNight Sleep(SCOPANS) and Scales for Outcomes in Parkinson’s DiseaseDaytime Sleep(SCOPADS) scores were significantly lower than those before intervention(P＜0.05).After intervention,the MoCA score of intervention group was higher than that of conventional group,and the scores of FAQ,HAMD,HAMA,SCOPADS and SCOPANS were lower than those of conventional group(P＜0.05).The modified Ashworth scale,Unified Parkinson s Disease Rating Scale（UPDRSⅢ),39item Parkinson’s Disease Questionnaire(PDQ39) scores were significantly lower than those before intervention, the balance and gait assessment scale(FGA),Modified Barthel Index(MBI) scores were significantly higher than those before intervention(P＜0.05).After intervention,the scores of Ashworth,UPDRSⅢ and PDQ39 in the intervention group were significantly lower than those in the conventional group,FGA,MBI scores was significantly higher than that in the conventional group(P＜0.05).After intervention,the compliance rate and nursing satisfaction rate in intervention group were significantly higher than those of the conventional group(P＜0.05).Conclusions:The application of family followup grading nursing in home care of patients with Parkinson disease could significantly improve the negative psychological,motor and non motor symptoms,improve the social function and activities of daily living,improve the overall quality of life.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".