Role of Alberta Stroke Programme Early Computed Tomography Score (PC- ASPECT) in Predicting Functional Outcome of Patients with Posterior Circulation Stroke - A Prospective Observational Study
Bibliographic record
Abstract
Objective: 1) To investigate the unfavourable outcome predictors of posterior circulation stroke. 2) To compare the PC-ASPECTS with respect to functional outcome prediction using Modified Rankin Scale and NIHSS (National institute of health stroke scale) 3) To identify the optimal cut-off point for the PC-ASPECTS for predicting favourable and unfavourable functional outcomes. Sample Size: Favourable functional outcome prediction in posterior circulation acute ischemic stroke has been observed in 64% from the previous study. Considering the 95% level of confidence interval (Z=1.96) with 10% precision (d=0.1) the minimum requiredsample size is - = ( ) ( -) () = (.) (.) ( -.) (.) = . Therefore, the minimum required sample for the study is 89.Article considered for the sample size calculation: "Predicting functional outcomes of posterior circulation acute ischemic stroke in first 36 h of stroke onset" by Sheng-Feng Lin.Statistical Analysis Plan: All the qualitative parameters like sex, complaints, risk factors, etc, represented with frequencies and percentages.Quantitative parameters like Age, NIHSS score, PC Aspect score, etc., represented with Mean with standard deviation.To find the association between qualitative factors we used Chi-Square test for measure of association.To find the relation between NIHSS, MRS, PC Aspects scores we used Pearson's correlation.To compare mean difference we used unpaired t-test.P value less than 0.05 considered as significance.Data entered in Ms. Excel and Analyzed by using SPSS 19.0v.Conclusions and Results: 1) It was observed that 50 (55.6%)patients were in the age group of 60 years and above followed by 35 (38.9%) in the age group of 46-60 years.2) Males were affected more i.e. 72 (80%) compared to the female patients 18 (20%).3) Most observed co-morbid condition was diabetes in 56(62.2%)patients followed by hypertension in 55(61.1%)patients and smoking in 44(48.9%)patients.4) Among the study participants 44(48.9%)were smokers.5) It was observed that the symptoms of headache were present among 62 (68.9%) patients followed by weakness in 57 (63.3%), altered consciousness in 52 (57.8%) and vomiting in 46 (51.1%).6) Most of the patients were having score 2 according to Modified Rankin scale after 4 weeks follow up.Score 2 seen in 34 (37.8%)patients followed by score 1 in 27(30%), score 3 in 18 (20%), score 4 in 9(10%) and score 5 in 2 (2.2%) patients.7) In our study the mean age is 63.3 years, NIHHS score is 10, PC-ASPECT is 7.2 and modified Rankin scale score is 2. 8) The correlation of PC-ASPECT, NIHHS and modified Rankin score was observed.9) The mean NIHHS is 17.43 for PC-ASPECT score <7 score, mean NIHHS is 7.81 for PC-ASPECT score >7 and above.10) The mean modified rank in score is 3.52 for PC-ASPECT score <7, mean modified rank in score is 1.75 for PC-ASPECT score >7.11) So our conclusion is that patients with low value of PC-ASPECT score (<7), present with higher value of NIHSS score and have higher value of Modified Rankin scoreunfavourable outcome.And the patients with high value of PC-ASPECT score (>7), present with lower value of NIHSS score and low value of Modified Rankin score-favourable outcome.Inference: The present study concludes that the PC-ASPECTS and baseline NIHSS help physicians to predict an unfavourable outcome, both individually and in combination.In addition to the effect of aging, gender, co-morbidity like hypertension, diabetes, addiction factors like smoking a PC-ASPECTS of 7 was the strongest predictor of unfavorable outcomes in our univariate and multivariate models.The functional outcomes were assessed at day 30 according to the Modified Rankin Scale (MRS), a standardized functional outcome assessment tool.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".