Development and validation of a nomogram predictive model for cerebral small vessel disease: a comprehensive retrospective analysis

Background

Cerebral small vessel disease (CSVD) is a significant contributor to stroke, intracerebral hemorrhages, and vascular dementia, particularly in the elderly. Early diagnosis remains challenging. This study aimed to develop and validate a novel nomogram for the early diagnosis of cerebral small vessel disease (CSVD). We focused on integrating cerebrovascular risk factors and blood biochemical markers to identify individuals at high risk of CSVD, thus enabling early intervention.

Methods

In a retrospective study conducted at the neurology department of the Affiliated Hospital of Hebei University from January 2020 to June 2022, 587 patients were enrolled. The patients were randomly divided into a training set (70%, n = 412) and a validation set (30%, n = 175). The nomogram was developed using multivariable logistic regression analysis, with variables selected through the Least Absolute Shrinkage and Selection Operator (LASSO) technique. The performance of the nomogram was evaluated based on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analysis (DCA).

Results

Out of 88 analyzed biomarkers, 32 showed significant differences between the CSVD and non-CSVD groups. The LASSO regression identified 12 significant indicators, with nine being independent clinical predictors of CSVD. The AUC-ROC values of the nomogram were 0.849 (95% CI: 0.821-0.894) in the training set and 0.863 (95% CI: 0.810-0.917) in the validation set, indicating excellent discriminative ability. Calibration plots demonstrated good agreement between predicted and observed probabilities in both sets. DCA showed that the nomogram had significant clinical utility.

Conclusions

The study successfully developed a nomogram predictive model for CSVD, incorporating nine clinical predictive factors. This model offers a valuable tool for early identification and risk assessment of CSVD, potentially enhancing clinical decision-making and patient outcomes.

Changes in blood biochemical markers before, during, and after a 2-day ultramarathon

We studied changes in blood markers of 18 nonprofessional, middle-aged runners of a 2-day, 130 km ultramarathon. Blood was sampled at baseline, after the goals on the first and second day, and at three time points (1, 3, and 5/6 days) after the race. Blood indices showed three patterns. First pattern indices showed essentially no changes after the two goals and after the race, including red blood cell indices, gamma-glutamyl transferase, and tumor necrosis factor-α. Second pattern markers, including the majority of indices, were elevated during the race (and also after the race for some parameters) and then returned to baseline afterward, including hemolysis/red blood cell destruction markers (indirect bilirubin) and an iron reservoir index (ferritin), muscle damage parameters (uric acid, creatine kinase, lactate dehydrogenase, and aspartate aminotransferase), renal function markers (creatinine and blood urea nitrogen), liver injury index (alanine aminotransferase), lipid metabolism indices (free fatty acid), reactive oxygen species and inflammation parameters (white blood cells, interleukin-6, and C-reactive protein), and energy production and catecholamines (adrenaline, noradrenaline, and dopamine). Third pattern index of a lipid metabolism marker – triglyceride – decreased during the race periods and started returning to baseline from then onward. Some hormonal markers such as insulin, leptin, and adiponectin showed unique patterns. These findings appeared informative for nonprofessional athletes to know about an optimal physical activity level, duration, and total exercise for elevating physical performance and monitoring physical/mental conditioning as well as for prevention of overtraining and physical injuries.

Characterization of blood biochemical markers during aging in the Grey Mouse Lemur (Microcebus murinus): impact of gender and season

BACKGROUND

Hematologic and biochemical data are needed to characterize the health status of animal populations over time to determine the habitat quality and captivity conditions. Blood components and the chemical entities that they transport change predominantly with sex and age. The aim of this study was to utilize blood chemistry monitoring to establish the reference levels in a small prosimian primate, the Grey Mouse Lemur (Microcebus murinus).

METHOD

In the captive colony, mouse lemurs may live 10-12 years, and three age groups for both males and females were studied: young (1-3 years), middle-aged (4-5 years) and old (6-10 years). Blood biochemical markers were measured using the VetScan Comprehensive Diagnostic Profile. Because many life history traits of this primate are highly dependent on the photoperiod (body mass and reproduction), the effect of season was also assessed.

RESULTS

The main effect of age was observed in blood markers of renal functions such as creatinine, which was higher among females. Additionally, blood urea nitrogen significantly increased with age and is potentially linked to chronic renal insufficiency, which has been described in captive mouse lemurs. The results demonstrated significant effects related to season, especially in blood protein levels and glucose rates; these effects were observed regardless of gender or age and were likely due to seasonal variations in food intake, which is very marked in this species.

CONCLUSION

These results were highly similar with those obtained in other primate species and can serve as references for future research of the Grey Mouse Lemur.