Deans' stroke musings: A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Tuesday, July 7, 2020

A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients

What fucking useless crapola! PREDICTIONS? Your mentors and senior researchers need to be fired.

A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients

Xiang Li^1,2,

Fusang Wang^1,2,

Zhihong Zhao³,

Chao Sun^1,2,

Jun Liao¹,

Xuemei Li³,

Chaoping Huang⁴,

Linda Nyame^1,2,

Zheng Zhao^1,2,

Xiaohan Zheng^1,2,

Junshan Zhou⁵,

Ming Li⁶^* and

Jianjun Zou^1,2^*

¹School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
²Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
³Department of Neurology, The First Affiliated Hospital (People's Hospital of Hunan Province), Hunan Normal University, Changsha, China
⁴Department of Neurology, Changsha Central Hospital, Changsha, China
⁵Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
⁶College of Life Science and Technology, China Pharmaceutical University, Nanjing, China

Background and Purpose: Accurate prediction of functional outcomes after stroke would provide evidence for reasonable post stroke management(Not cure?). This study aimed to develop and validate a nomogram for individualized prediction of 1-year unfavorable outcomes in Chinese acute ischemic stroke (AIS) patients.

Methods: We gathered AIS patients at the National Advanced Stroke Center of Nanjing First Hospital (China) between August 2014 and May 2017 within 12 h of symptom onset. The outcome measure was 1-year unfavorable outcomes (modified Rankin Scale 3–6). The patients were randomly stratified into the training (66.7%) and testing (33.3%) sets. With the training data, pre-established predictors were entered into a logistic regression model to generate the nomogram. Predictive performance of the nomogram model was evaluated in the testing data by calculating the area under the receiver operating characteristic curve (AUC-ROC), Brier score, and a calibration plot.

Results: A total of 807 patients were included into this study, and 262 (32.5%) of them had unfavorable outcomes. Systolic blood pressure, Creatinine, Age, National Institutes of Health Stroke Scale (NIHSS) score on admission, and fasting blood glucose were significantly associated with unfavorable outcomes and entered into the SCANO nomogram. The AUC-ROC of the SCANO nomogram in the testing set was 0.781 (Brier score: 0.166; calibration slope: 0.936; calibration intercept: 0.060).

Conclusions: The SCANO nomogram is developed and validated in Chinese AIS patients to firstly predict 1-year unfavorable outcomes, which is simple and convenient for the management(Not cure?) of stroke patients.

Introduction

Acute ischemic stroke (AIS) continues to be an important cause of morbidity and mortality worldwide, which can bring heavy economic burden for patients and their families (1, 2). Consequently, clinicians will be faced with a great challenge regarding unfavorable outcomes in these patients. Better identification of AIS patients with unfavorable outcomes could be useful to develop preventive strategies and reduce the risk of morbidity and mortality after stroke.

Some prognostic scores (3–5) and several nomograms (6–8) have identified some demographic and clinical characteristics to predict 3-month clinical outcomes for AIS patients. However, model for predicting 1-year unfavorable outcomes in AIS patients was not found. On the one hand, most of the functional improvements tend to be achieved during the first 3 months after stroke. Although the patients with AIS recover rapidly during the first few weeks, there are some additional recovery between 3 and 6 months (9, 10). On the other hand, between 3 and 12 months, one in six patients with AIS deteriorate in functional outcomes (11). Therefore, the models for predicting 3-month outcomes may be limited because these models could not be suitable for all patients. Furthermore, as the strongest predictors of 3-month unfavorable outcomes (3, 6, 12–14), the correlation of National Institutes of Health Stroke Scale (NIHSS) score with the outcomes varies with the time passed from the onset of cerebral ischemia (15). This also affects the predictive performance when these models were used to predict 1-year outcomes. As a result, these prognostic scores and nomograms cannot be extrapolated to predict 1-year unfavorable outcomes, and it is meaningful to establish a model to predict 1-year unfavorable outcomes.

Therefore, the present research aimed to develop and validate a nomogram by using a limited number of easily available variables to predict 1-year unfavorable outcomes for Chinese AIS patients.