Albumin-corrected fructosamine predicts all-cause and non-CVD mortality among the very elderly aged ≥ 80 years without diabetes

The biological age model for evaluating the degree of aging in centenarians

BACKGROUND

Biological age (BA) has been used to assess individuals' aging conditions. However, few studies have evaluated BA models' applicability in centenarians.

METHODS

Important organ function examinations were performed in 1798 cases of the longevity population (80∼115 years old) in Hainan, China. Eighty indicators were selected that responded to nutritional status, cardiovascular function, liver and kidney function, bone metabolic function, endocrine system, hematological system, and immune system. BA models were constructed using multiple linear regression (MLR), principal component analysis (PCA), Klemera and Doubal method (KDM), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and light gradient boosting machine (lightGBM) methods. A tenfold crossover validated the efficacy of models.

RESULTS

A total of 1398 participants were enrolled, of whom centenarians accounted for 49.21%. Seven aging markers were obtained, including estimated glomerular filtration rate, albumin, pulse pressure, calf circumference, body surface area, fructosamine, and complement 4. Eight BA models were successfully constructed, namely MLR, PCA, KDM1, KDM2, RF, SVM, XGBoost and lightGBM, which had the worst R2 of 0.45 and the best R2 of 0.92. The best R2 for cross-validation was KDM2 (0.89), followed by PCA (0.62).

CONCLUSION

In this study, we successfully applied eight methods, including traditional methods and machine learning, to construct models of biological age, and the performance varied among the models.

Predictive value of different glycemic control markers in total hip or knee arthroplasty: A prospective study

OBJECTIVE

The optimal glycemic control marker before total hip or knee arthroplasty remains inconclusive. Hemoglobin A1c (HbA1c) is widely used, while fructosamine may be valuable for predicting periprosthetic joint infection (PJI). Fructosamine levels can be affected by serum albumin levels; albumin-corrected fructosamine (AlbF) can be calculated to overcome this issue. The objective of this study was to evaluate the predictive value of different markers for complications after primary total hip or knee arthroplasty.

METHODS

This prospective cohort study included 304 patients (mean age: 65 years [range, 16-85), mean follow-up: 32 months (range, 12-49)] who underwent primary total hip or knee arthroplasty between 2018 and 2021. Of them, 156 patients had diabetes. Mean HbA1c was 6.5% (range, 4.8%-13%), fructosamine 244 µmol/L (range, 98-566 µmol/L), and AlbF 632 (range, 238-2308). Patients who did and did not have diabetes were matched 1 : 1. Hemoglobin A1c 7% and fructosamine 292 µmol/L were used as cutoff. Complications were documented. Glycemic markers were compared using logistic regression analyses, with a special focus on PJI.

RESULTS

In the logistic regression analyses, HbA1c was strongly associated with total complications [adjusted odds ratio (OR): 3.61; 95% CI, 1.65-7.91, P = .001], while fructosamine was associated with PJI (adjusted OR: 13.68; 95% CI, 1.39-134.89, P = .025). Albumin-corrected fructosamine did not show any additional benefits.

CONCLUSION

Preoperative assessment before total hip or knee arthroplasty must not focus on a single marker; HbA1c is a good predictor of total complications, while fructosamine is a better predictor of PJI. To the best of our knowledge, in its first orthopedic study, AlbF did not show any advantages.

LEVEL OF EVIDENCE

Level II, Prognostic Study.

An Assessment of the Utility of Serum Fructosamine in the Diagnosis and Monitoring of Diabetes Mellitus

BACKGROUND

Fructosamine (FA) has gained importance as a new biomarker for hyperglycemia in the past decade and may be of indispensable use in certain conditions where hemoglobin A1c (HbA1c) falls short of utility such as disorders of red blood cells, patients with rapid glycemic excursions requiring more short-term monitoring, pregnancy, chronic kidney disease, etc. Methods: The present study was a hospital-based observational cross-sectional study conducted in the Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Nagpur, India. Serum HbA1c, FA, albumin-corrected fructosamine (AlbF), total protein-corrected FA (PrF), hemoglobin (Hb), and hematocrit (Hct) were estimated in 32 controls (Group I) and 32 cases of diabetes mellitus (DM) (Group II). The clinical data and lab results were presented as mean±SD/±standard error (SE) of the mean. Student's t-test and ANOVA were used to compare various parameters between the groups. Pearson correlation analysis was performed to assess the correlation between different diagnostic parameters. The receiver operating characteristic (ROC) curve was plotted to assess the diagnostic significance and cut-off value for FA, AlbF, and PrF.

RESULTS

The controls and cases were matched for age and gender distribution. Serum HbA1c (p<0.0001), serum FA (p<0.0001), fasting blood sugar (p=0.001), postprandial blood sugar (p<0.0001), random blood sugar (p=0.001), hematocrit (p=0.002), AlbF (p<0.0001), and PrF (p<0.0001) were found to be significantly higher in known diabetic subjects compared to controls. The case group was further subdivided into pre-diabetic and diabetic groups. On correlation analysis of HbA1c with various parameters, a moderate correlation of HbA1c was noted with FA (r=0.522, p<0.0001) and AlbF (r=0.375, p=0.002) in all subjects. Additionally, a moderate correlation of FA (r=0.479, p=0.033), AlbF (r=0.444, p=0.050), and PrF (r=0.441, p=0.065) with HbA1c was also found in subjects with diabetic range glycemia. No such correlation was noted in the pre-diabetic group. No significant correlation was noted between FA and its corrected values in any range of glycemia. None of the parameters assessing glycemia were found to be significantly affected by hemoglobin status. On ROC curve analysis, HbA1c was found to be the best parameter (area under the curve (AUC) =83%, p<0.0001) followed by AlbF (AUC= 80.5%, p<0.0001) and uncorrected FA (AUC=80.5%, p<0.0001) to diagnose DM.

CONCLUSION

Serum FA should be considered a valid diagnostic biomarker and of indispensable use in special populations where HbA1c falls short of utility such as patients with red blood cell disorders or those showing rapid glycemic excursions such as those on corticosteroid therapy or insulin therapy, etc. It exhibits additional advantages over HbA1c with respect to lower reagent cost and easy automation on any conventional laboratory instruments based on simple colorimetry.