Prognostic Value of The Leuko-Glycemic Index in Acute Myocardial Infarction; a Systematic Review and Meta-Analysis.

Introduction: In recent years, studies have provided evidence on the prognostic value of the leuko-glycemic index (LGI) in acute myocardial infarction (MI), but there is a lack of consensus. In addition, various reported cut-offs for LGI have raised concern regarding its clinical applicability. So, to conclude, through this systematic review and meta-analysis, we aimed to investigate all available evidence on the prognostic value of LGI in acute MI. Methods: Two independent researchers summarized records available in the four main databases of Medline (Via PubMed), Embase, Scopus, and Web of Science until 15 Sep 2022. Articles studying the prognostic value of the LGI in acute MI were included. Finally, sensitivity, specificity, prognostic odds ratio, and the area under the curve (AUC) for LGI were analyzed and reported. Results: Eleven articles were included (3701 patients, 72.1% male). Based on the analyses, AUC, sensitivity, and specificity for LGI in prediction of mortality following acute MI were 0.77 (95% CI: 0.73 to 0.80), 0.75 (95% CI: 0.62 to 0.84), and 0.66 (95% CI: 0.51 to 0.78), respectively. Positive and negative post-test probability of LGI in prediction of mortality were 21% and 5%, respectively. AUC, sensitivity, and specificity for LGI in prediction of major cardiac complications after acute MI were 0.81 (95% CI: 0.77 to 0.84), 0.84 (95% CI: 0.70 to 0.92), and 0.64 (95% CI: 0.49 to 0.84), respectively. Also, the Positive and negative post-test probability of LGI in this regard were 59% and 13%, respectively. Conclusion: Although the results demonstrated that the LGI could predict mortality and acute cardiac complication after MI, the low post-test probability of LGI in risk stratification of patients raises questions regarding its applicability. Nevertheless, as most of the available studies have been conducted in the Latino/Hispanic population, further evidence is warranted to generalize the validity of this tool to other racial populations.

Prognostic Value of CRASH and IMPACT Models for Predicting Mortality and Unfavorable Outcome in Traumatic Brain Injury; a Systematic Review and Meta-Analysis.

Introduction: The Corticosteroid Randomization After Significant Head injury (CRASH) and the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) are two prognostic models frequently used in predicting the outcome of patients with traumatic brain injury. There are ongoing debates about which of the two models has a better prognostic value. This study aims to compare the CRASH and IMPACT in predicting mortality and unfavorable outcome of patients with traumatic brain injury. Method: We performed a literature search using Medline (via PubMed), Embase, Scopus, and Web of Science databases until August 17, 2022. After two independent researchers screened the articles, we included all the original articles comparing the prognostic value of IMPACT and CRASH models in patients with traumatic brain injury. The outcomes evaluated were mortality and unfavorable outcome. The data of the included articles were analyzed using STATA 17.0 statistical program, and we reported an odds ratio (OR) with a 95% confidence interval (95% CI) for comparison. Results: We included the data from 16 studies. The analysis showed that the areas under the curve of the IMPACT core model and CRASH basic model do not differ in predicting the mortality of patients (OR=0.99; p=0.905) and their six-month unfavorable outcome (OR=1.01; p=0.719). Additionally, the CRASH CT model showed no difference from the IMPACT extended (OR=0.98; p=0.507) and IMPACT Lab (OR=1.00; p=0.298) models in predicting the mortality of patients with traumatic brain injury. We also observed similar findings in the six-month unfavorable outcome, showing that the CRASH CT model does not differ from the IMPACT extended (OR=1.00; p=0.990) and IMPACT Lab (OR=1.00; p=0.570) in predicting the unfavorable outcome in head trauma patients. Conclusion: Low to very low level of evidence shows that IMPACT and CRASH models have similar values in predicting mortality and unfavorable outcome in patients with traumatic brain injury. Since the discriminative power of the IMPACT Core and CRASH basic models is not different from the IMPACT extended, IMPACT Lab, and CRASH CT models, it may be possible to only use the core and basic models in examining the prognosis of patients with traumatic injuries to the brain.

Can metformin use reduce the risk of stroke in diabetic patients? A systematic review and meta-analysis.

BACKGROUND AND AIM: Stroke and cardiovascular diseases are major causes of death and disability, especially among diabetic patients. Some studies have shown that metformin has been effective in preventing cardiovascular diseases. In this study, we aim to evaluate the effect of metformin on stroke in type 2 diabetic patients. METHODS: A comprehensive search was conducted in Medline, Embase, Scopus, and Web of Science databases from their inception till 1st July 2022. Randomized clinical trials (RCT) and cohort studies were included. Two independent researchers screened the records, extracted the data, and assessed the risk of bias and certainty of evidence. Findings were reported as risk ratio (RR) and 95% confidence interval (CI). All statistical analyses were performed using the STATA 17.0 software package. RESULTS: Analysis of 21 included studies with 1,392,809 patients demonstrated that metformin monotherapy was effective in reducing stroke risk in both RCTs (RR = 0.66, 95% CI: 0.50, 0.87 p = 0.004) and cohort studies (RR = 0.67, 95% CI: 0.55, 0.81, p < 0.0001). However, combined administration of metformin with other antihyperglycemic agents had no significant effect on stroke risk reduction in either the RCTs (RR = 0.92, 95% CI: 0.69, 1.22 p = 0.558) or the cohort studies (RR = 0.79, 95% CI: 0.59, 1.06, p = 0.122). CONCLUSION: Low to moderate level of evidence in RCTs showed that metformin monotherapy could reduce stroke risk in type 2 diabetic patients. However, the preventive effect of metformin in stroke was not observed in patients who received a combination of metformin plus other hypoglycemic agents.

Canadian C-spine Rule versus NEXUS in Screening of Clinically Important Traumatic Cervical Spine Injuries; a systematic review and meta-analysis.

Introduction: The Canadian C-spine Rule (CCR) and the National Emergency X-Radiography Utilization Study (NEXUS) are two criteria designed to rule-out clinically important traumatic cervical Spinal Cord Injury (SCI). In this systematic review and meta-analysis, we reviewed the articles comparing the performance of these two models. Methods: Search was done in Medline, Embase, Scopus and Web of Science until June 2022. Observational studies with direct comparison of CCR and NEXUS criteria in detection of clinically important cervical SCI were included. Two independent reviewers screened the relevant articles and summarized the data. Certainty of evidence was assessed based on QUADAS-2. Data were recorded as true positive, true negative, false positive, and false negative. Then, using "diagma" package and applying weighted random effect model, area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, negative likelihood ratio, positive likelihood ratio, and diagnostic odds ratio (DOR) were calculated with 95% confidence interval (95% CI). Results: We included 5 studies with direct comparison. Area under the ROC curve of NEXUS in screening of patients with clinically important cervical SCI was 0.708 (95% CI: 0.647 to 0.762). Pooled sensitivity and specificity of NEXUS criteria in screening of patients with clinically important cervical SCI were 0.899 (95% CI: 0.845 to 0.936) and 0.398 (95% CI: 0.315 to 0.488). The positive and negative likelihood ratios of NEXUS were 1.494 (95% CI: 1.146 to 1.949) and 0.254 (95% CI: 1.155 to 1.414), respectively. Diagnostic odds ratio of NEXUS was 5.894 (95% CI: 3.372 to 10.305). Furthermore, area under the ROC curve of CCR in screening of clinically important cervical SCI was 0.793 (95% CI: 0.657 to 0.884). Meta-analysis results showed that pooled sensitivity of CCR criteria in screening of patients with clinically important cervical SCI was 0.987 (95% CI: 0.957 to 0.996) and specificity was 0.167 (95% CI: 0.073 to 0.336). The positive and negative likelihood ratios of CCR were 1.184 (95% CI: 0.837 to 1.675) and 0.081 (95% CI: 0.021 to 0.308), respectively. Diagnostic odds ratio of CCR was 14.647 (95% CI: 3.678 to 58.336). Conclusion: Based on studies, both CCR and NEXUS were sensitive rules that have the potential to reduce unnecessary imaging in cervical spine trauma patients. However, the low specificity and false-positive results of both of these tools indicate that many people will continue to undergo unnecessary imaging after screening of cervical SCI using these tools. In this meta-analysis, CCR appeared to have better screening accuracy.