Use of Dental Practices for the Identification of Adults With Undiagnosed Type 2 Diabetes Mellitus or Nondiabetic Hyperglycemia: Protocol for a Systematic Review

Systematic investigation of Radix Salviae for treating diabetic peripheral neuropathy disease based on network Pharmacology

BACKGROUND

Diabetic peripheral neuropathy (DPN) is a debilitating complication of diabetes mellitus with limited available treatment options. Radix Salviae, a traditional Chinese herb, has shown promise in treating DPN, but its therapeutic mech-anisms have not been systematically investigated.

AIM

Radix Salviae (Danshen in pinin), a traditional Chinese medicine (TCM), is widely used to treat DPN in China. However, the mechanism through which Radix Salviae treats DPN remains unclear. Therefore, we aimed to explore the mechanism of action of Radix Salviae against DPN using network pharmacology.

METHODS

The active ingredients and target genes of Radix Salviae were screened using the TCM pharmacology database and analysis platform. The genes associated with DPN were obtained from the Gene Cards and OMIM databases, a drug-com-position-target-disease network was constructed, and a protein-protein inter-action network was subsequently constructed to screen the main targets. Gene Ontology (GO) functional annotation and pathway enrichment analysis were performed via the Kyoto Encyclopedia of Genes and Genomes (KEGG) using Bioconductor.

RESULTS

A total of 56 effective components, 108 targets and 4581 DPN-related target genes of Radix Salviae were screened. Intervention with Radix Salviae for DPN mainly involved 81 target genes. The top 30 major targets were selected for enrichment analysis of GO and KEGG pathways.

CONCLUSION

These results suggested that Radix Salviae could treat DPN by regulating the AGE-RAGE signaling pathway and the PI3K-Akt signaling pathway. Therefore, Danshen may affect DPN by regulating inflammation and apoptosis.

Factors Associated with Self-Report of Type 2 Diabetes Mellitus in Adults Seeking Dental Care in a Developing Country

The aims of the present study were to identify the prevalence and risk indicators of type 2 diabetes mellitus (T2DM) in urban-based Mexican adults seeking care in a university-based triage/intake dental clinic, and to develop a predictive model. A cross-sectional study was conducted on 3354 medical/dental records of adults who sought care at the triage/intake dental clinics of a public university. The dependent variable was self-report of a previous diagnosis of T2DM made by a physician. Several socio-demographic and socioeconomic covariates were included, as well as others related to oral and general health. A multivariate binary logistic regression model was generated. We subsequently calculated well-known statistical measures employed to evaluate discrimination (classification) using an (adjusted) multivariate logistic regression model (goodness-of-fit test). The average age of patients was 42.5 ± 16.1 years old and the majority were female (64.1%). The prevalence of T2DM was 10.7% (95%CI = 9.7−11.8). In the final multivariate model, the variables associated (p < 0.05) with the presence of T2DM were older age (40 to 59 years old, OR = 2.00; 60 to 95 years old, OR = 2.78), having any type of health insurance (OR = 2.33), having high blood pressure (OR = 1.70), being obese (OR = 1.41), and having a functional dentition (OR = 0.68). Although the global fit of the model and the calibration tests were adequate, the sensitivity (0.0%) and positive predictive (0.0%) values were not. The specificity (100%) and negative predictive (89.3%) values, as well as the correctly classified (89.3%) value, were adequate. The area under the ROC curve, close to 0.70, was modest. In conclusion, a prevalence of T2DM of 10.7% in this sample of Mexican adults seeking dental care was similar to national figures. Clinical (blood pressure, BMI and functional dentition), demographic (age), and socioeconomic (health insurance) variables were found to be associated with T2DM. The dental setting could be appropriate for implementing preventive actions focused on identifying and helping to reduce the burden of T2DM in the population.

Use of dental practices for the identification of adults with undiagnosed type 2 diabetes mellitus or non-diabetic hyperglycaemia: a systematic review

AIM

Type 2 diabetes is a growing global challenge. Evidence exists demonstrating the use of primary care (non-hospital based) dental practices to identify, through risk assessments, those who may be at increased risk of type 2 diabetes or who may already unknowingly have the condition. This review aimed to synthesize evidence associated with the use of primary care dental services for the identification of undiagnosed non-diabetic hyperglycaemia or type 2 diabetes in adults, with particular focus on the pick-up rate of new cases.

METHOD

Electronic databases were searched for studies reporting the identification of non-diabetic hyperglycaemia/type 2 diabetes in primary care dental settings. Returned articles were screened and two independent reviewers completed the data-extraction process. A descriptive synthesis of the included articles was undertaken due to the heterogeneity of the literature returned.

RESULTS

Nine studies were identified, the majority of which utilized a two-stage risk-assessment process with risk score followed by a point-of-care capillary blood test. The main barriers cited were cost, lack of adequate insurance cover and people having previously been tested elsewhere. The pick-up rate of new cases of type 2 diabetes and non-diabetic hyperglycaemia varied greatly between studies, ranging from 1.7% to 24% for type 2 diabetes and from 23% to 45% for non-diabetic hyperglycaemia, where reported.

CONCLUSION

This review demonstrates that although it appears there may be benefit in using the dental workforce to identify undiagnosed cases of non-diabetic hyperglycaemia and type 2 diabetes, further high-quality research in the field is required assessing both the clinical and cost effectiveness of such practice. (Prospero Registration ID: PROSPERO 2018 CRD42018098750).