English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The allocation of hypoglycaemic symptoms to autonomic or neuroglycopenic groups tends to occur on an a priori basis. In view of the practical need for clear symptom markers of hypoglycaemia more scientific approaches must be pursued. Substantial evidence is presented from two large scale studies we performed which support a three factor model of hypoglycaemic symptomatology, based on the statistical associations discovered among symptoms reported by diabetic patients. Study 1 involved 295 insulin-treated out-patients and found that 11 key hypoglycaemic symptoms segregated into three clear factors: autonomic (sweating, palpitation, shaking and hunger) neuroglycopenic (confusion, drowsiness, odd behaviour, speech difficulty and incoordination), and malaise (nausea and headache). The three factors were validated on a separate group of 303 insulin-treated diabetic out-patients. Confirmatory factor analyses showed that the three factor model was the optimal model for explaining symptom covariance in each group. A multi-sample confirmatory factor analysis tested the rigorous assumptions that the relative loadings of symptoms on factors across groups were equal, and that the residual variance for each symptom was identical across groups. These assumptions were successful, indicating that the three factor model was replicated in detail across these two large samples. It is suggested that the results indicate valid groupings of symptoms that may be used in future research and in clinical practice.

Partitioning the symptoms of hypoglycaemia using multi-sample confirmatory factor analysis