The progression of long-term diabetes complications has led to a decreased quality of life. Our objective was to evaluate the adverse outcomes associated with diabetes based on a patient’s clinical profile by utilizing a multistate modeling approach.

This was a retrospective study of diabetes patients seen in primary care practices from 2013 to 2017. We implemented a five-state model to examine the progression of patients transitioning from one complication to having multiple complications. Our model incorporated high dimensional covariates from multisource data to investigate the possible effects of different types of factors that are associated with the progression of diabetes.

The cohort consisted of 10,596 patients diagnosed with diabetes and no previous complications associated with the disease. Most of the patients in our study were female, White, and had type 2 diabetes. During our study period, 5928 did not develop complications, 3323 developed microvascular complications, 1313 developed macrovascular complications, and 1129 developed both micro- and macrovascular complications. From our model, we determined that patients had a 0.1334 [0.1284, .1386] rate of developing a microvascular complication compared to 0.0508 [0.0479, .0540] rate of developing a macrovascular complication. The area deprivation index score we incorporated as a proxy for socioeconomic information indicated that patients who reside in more disadvantaged areas have a higher rate of developing a complication compared to those who reside in least disadvantaged areas.

Our work demonstrates how a multistate modeling framework is a comprehensive approach to analyzing the progression of long-term complications associated with diabetes.

Associations have been found between five-factor model (FFM) personality traits and risk of developing specific predementia syndromes such as subjective cognitive decline (SCD) and mild cognitive impairment (MCI). The aims of this study were to: 1) Compare baseline FFM traits between participants who transitioned from healthy cognition or SCD to amnestic MCI (aMCI) versus non-amnestic MCI (naMCI); and 2) Determine the relationship between FFM traits and risk of transition between predementia cognitive states.

Participants were 562 older adults from the Einstein Aging Study, 378 of which had at least one follow-up assessment. Baseline data collected included levels of FFM personality traits, anxiety and depressive symptoms, medical history, performance on a cognitive battery, and demographics. Follow-up cognitive diagnoses were also recorded.

Mann–Whitney U tests revealed no differences in baseline levels of FFM personality traits between participants who developed aMCI compared to those who developed naMCI. A four-state multistate Markov model revealed that higher levels of conscientiousness were protective against developing SCD while higher levels of neuroticism resulted in an increased risk of developing SCD. Further, higher levels of extraversion were protective against developing naMCI.

FFM personality traits may be useful in improving predictions of who is at greatest risk for developing specific predementia syndromes. Information on these personality traits could enrich clinical trials by permitting trials to target individuals who are at greatest risk for developing specific forms of cognitive impairment. These results should be replicated in future studies with larger sample sizes and younger participants.