Relationship between serum creatinine to cystatin C ratio and subclinical atherosclerosis in patients with type 2 diabetes

Hashimoto, Yoshitaka; Takahashi, Fuyuko; Okamura, Tomio; Osaka, Takafumi; Okada, Hiroshi; Senmaru, Takafumi; Majima, Susumu; Ushigome, Emi; Nakanishi, Naoko; Asano, Mai; Hamaguchi, Masahide; Yamazaki, Masahiro; Fukui, Michiaki

doi:10.1136/bmjdrc-2022-002910

Cited by 11 publications

(8 citation statements)

References 50 publications

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“…In this study, the percentage of SCAS in the T2DM population was 38.46%, lower than the 43.68% reported by Hashimoto et al in a Japanese T2DM population (22), which might be related to the region and sample size. Multiple studies have demonstrated an association between the TyG index and the incidence of CVD, coronary artery stenosis, stroke, and AS (23,24).…”

Section: Discussioncontrasting

confidence: 85%

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Tusongtuoheti,

Shu,

Huang

et al. 2024

Front. Endocrinol.

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BackgroundCardiovascular disease (CVD) has emerged as a global public health concern. Identifying and preventing subclinical atherosclerosis (SCAS), an early indicator of CVD, is critical for improving cardiovascular outcomes. This study aimed to construct interpretable machine learning models for predicting SCAS risk in type 2 diabetes mellitus (T2DM) patients.MethodsThis study included 3084 T2DM individuals who received health care at Zhenhai Lianhua Hospital, Ningbo, China, from January 2018 to December 2022. The least absolute shrinkage and selection operator combined with random forest-recursive feature elimination were used to screen for characteristic variables. Linear discriminant analysis, logistic regression, Naive Bayes, random forest, support vector machine, and extreme gradient boosting were employed in constructing risk prediction models for SCAS in T2DM patients. The area under the receiver operating characteristic curve (AUC) was employed to assess the predictive capacity of the model through 10-fold cross-validation. Additionally, the SHapley Additive exPlanations were utilized to interpret the best-performing model.ResultsThe percentage of SCAS was 38.46% (n=1186) in the study population. Fourteen variables, including age, white blood cell count, and basophil count, were identified as independent risk factors for SCAS. Nine predictors, including age, albumin, and total protein, were screened for the construction of risk prediction models. After validation, the random forest model exhibited the best clinical predictive value in the training set with an AUC of 0.729 (95% CI: 0.709-0.749), and it also demonstrated good predictive value in the internal validation set [AUC: 0.715 (95% CI: 0.688-0.742)]. The model interpretation revealed that age, albumin, total protein, total cholesterol, and serum creatinine were the top five variables contributing to the prediction model.ConclusionThe construction of SCAS risk models based on the Chinese T2DM population contributes to its early prevention and intervention, which would reduce the incidence of adverse cardiovascular prognostic events.

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Section: Discussioncontrasting

confidence: 85%

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Tusongtuoheti,

Shu,

Huang

et al. 2024

Front. Endocrinol.

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“…However, the complexity of sarcopenia assessment likely makes the formal screening for sarcopenia highly underutilized. The SI is a readily available biomarker of skeletal muscle mass that has been validated in several populations including critically ill 6 , older adults 32 , lung and kidney transplant recipients 7 , diabetic 33 and cancer patients 34 . Moreover, SI was found to be a prognostic factor for short- and long-term survival and complications among cancer patients 35 .…”

Section: Discussionmentioning

confidence: 99%

Alterations in Sarcopenia Index are Associated with Inflammation, Gut and Oral Microbiota among Heart Failure, Left Ventricular Assist Device and Heart Transplant Patients

Yuzefpolskaya,

Bohn,

Ladanyi

et al. 2023

Preprint

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Background: Sarcopenia, characterized by loss of muscle mass and function, is prevalent in heart failure (HF) and associated with poor outcomes. We investigated alterations in sarcopenia index (SI), a surrogate marker of skeletal muscle mass, in HF, left ventricular assist device (LVAD) and heart transplant (HT) and assessed its relationship with inflammation and digestive tract (gut and oral) microbiota. Methods: We enrolled 460 HF, LVAD and HT patients. Repeated measures pre and post procedures were obtained in a subset of LVAD and HT patients. Sarcopenia index (serum Creatinine/Cystatin C) and inflammatory biomarkers (C-reactive protein, interleukin-6, tumor necrosis factor-alpha) were measured in 271 and 622 blood samples, respectively. Gut and saliva microbiota were assessed via 16S rRNA sequencing among 335 stool and 341 saliva samples. Multivariable regression models were used to assess the relationship between SI and i) New York Heart Association class; ii) pre- vs. post-LVAD or HT; iii) biomarkers of inflammation and microbial diversity. Results: Median (interquartile range) ln-SI was -0.13(-0.32,0.05). Ln-SI decreased across worsening HF class, further declined within the 1-month after LVAD and HT and rebounded over time to the levels of symptomatic HF. Ln-SI demonstrated an inverse correlation with inflammation (r=-0.28, p<0.0001), and a positive correlation with gut (r=0.26, p<0.0001) and oral microbial diversity (r=0.24, p<0.0001). Presence of the gut taxa Roseburia inulinivorans was associated with increased SI. Conclusions: SI levels decreased in symptomatic HF and remained decreased long-term after LVAD and HT. SI levels covaried with inflammation, gut and oral microbiota in a similar fashion.

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“…Creatinine is generated in proportion to muscle mass; however, cystatin C levels are not affected by it [ 23 ]. Therefore, the serum creatinine to cystatin C ratio can be used to evaluate muscle mass in several diseases [ 24 - 26 ]. Similar to the results of the previous study, this study also showed a significant correlation between the serum creatinine to cystatin C ratio and muscle mass in patients with COPD [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Low Skeletal Muscle Mass and Clinical Outcomes in Chronic Obstructive Pulmonary Disease

Choi,

Park,

Cho

et al. 2023

Tuberc Respir Dis

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Background: In patients with chronic obstructive pulmonary disease (COPD), decreased muscle mass is a frequently encountered comorbidity in clinical practice. However, the evaluation of muscle mass in patients with COPD in real-world practice is rare.Methods: We retrospectively reviewed the electronic medical records of all patients with COPD who underwent bioelectrical impedance analysis at least once between January 2011 and December 2021 in three hospitals. Then, we analyzed the performance rate of muscle mass measurement in the patients and the correlation between muscle mass, clinical parameters, and COPD prognosis.Results: Among the 24,502 patients with COPD, only 270 (1.1%) underwent muscle mass measurements. The total skeletal muscle mass index was significantly correlated with albumin, alanine transaminase, and creatinine to cystatin C ratio in patients with COPD (r=0.1614, p=0.011; r=0.2112, p=0.001; and r=0.3671, p=0.001, respectively). Acute exacerbation of COPD (AE COPD) was significantly correlated with muscle mass, especially the truncal skeletal muscle mass index (TSMI) in males (r=–0.196, p=0.007). In the multivariate analysis, TSMI and cystatin C were significant risk factors for AE COPD (hazard ratio, 0.200 [95% confidence interval, CI, 0.048 to 0.838] and 4.990 [95% CI, 1.070 to 23.278], respectively).Conclusion: Low muscle mass negatively affects the clinical outcomes in patients with COPD. Despite its clinical significance, muscle mass measurement is performed in a small proportion of patients with COPD. Therefore, protocols and guidelines for the screening of sarcopenia in patients with COPD should be established.

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Relationship between serum creatinine to cystatin C ratio and subclinical atherosclerosis in patients with type 2 diabetes

Cited by 11 publications

References 50 publications

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Predicting the risk of subclinical atherosclerosis based on interpretable machine models in a Chinese T2DM population

Alterations in Sarcopenia Index are Associated with Inflammation, Gut and Oral Microbiota among Heart Failure, Left Ventricular Assist Device and Heart Transplant Patients

Low Skeletal Muscle Mass and Clinical Outcomes in Chronic Obstructive Pulmonary Disease

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