Relationship of Para and Perirenal Fat and High-Density Lipoprotein and Its Function in Patients with Type 2 Diabetes Mellitus

Ke, Jing; Wang, Yan; Liu, Simo; Li, Kun; Xu, Yuechao; Yang, Longyan; Zhao, Dong

doi:10.1155/2021/9286492

Cited by 4 publications

(2 citation statements)

References 28 publications

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“…Numerous studies have shown that obesity indicators are associated with metabolic risk factors, while many studies have mainly focused on PRFT [ [23] , [24] , [25] ]. Ke J et al showed a negative correlation between PRFT and HDL-c [ 26 ], which was consistent with our findings. It's reported that dyslipidemia is one of the risk factors for renal dysfunction [ [27] , [28] , [29] ].…”

Section: Discussionsupporting

confidence: 93%

The association between obesity indicators and metabolic risk factors in type-2 diabetic patients

Xu,

Ren,

et al. 2023

Heliyon

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Section: Discussionsupporting

confidence: 93%

The association between obesity indicators and metabolic risk factors in type-2 diabetic patients

Xu,

Ren,

et al. 2023

Heliyon

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“…21 Ke et al found that PrFT was negatively correlated with the serum HDL-c level and positively correlated with cholesterol efflux capacity in T2DM. 22 In addition, several observational studies also revealed that increased PrFT was positively associated with increased WC and HOMA-IR. 8,23,24 The effects of VAT on metabolic dysfunctions and inflammation have been reported previously.…”

Section: Discussionmentioning

confidence: 99%

Perirenal Fat Thickness is Associated with Metabolic Dysfunction-Associated Fatty Liver Disease in Type 2 Diabetes Mellitus

Yang¹,

Li²,

Zhang³

et al. 2023

DMSO

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Objective Recent advances in perirenal adipose tissue (PAT) highlighted that PAT might involve in the pathogenesis of chronic inflammatory and dysfunctional metabolic diseases. This study assessed the association between perirenal fat thickness (PrFT) and metabolic dysfunction-associated fatty liver disease (MALFD) in type 2 diabetes mellitus (T2DM). Methods This study comprised 867 eligible participants with T2DM. Trained reviewers collected anthropometric and biochemical measurements. The diagnosis of MAFLD was based on the latest international expert consensus statement. PrFT and fatty liver were evaluated by computed tomography. The visceral fat area (VFA) and subcutaneous fat area (SFA) were measured by bioelectrical impedance analysis. The non-alcoholic fatty liver disease fibrosis score (NFS) and fibrosis-4 (FIB-4) index were used to assess progressive liver fibrosis in MAFLD. Results Overall, the prevalence of MAFLD was 62.3% in T2DM. The PrFT in the MAFLD group was statistically increased than in the non-MAFLD group ( P < 0.05). Correlation analysis showed that PrFT was significantly correlated with dysfunctional metabolic factors like body mass index, waist circumference, triglycerides, high-density lipoprotein cholesterol, systolic blood pressure, diastolic blood pressure, uric acid, and insulin resistance. Multiple regression analysis revealed that PrFT was positively correlated with NFS ( β =0.146, P <0.001) and FIB-4 ( β =0.082, P =0.025) in the MAFLD. In contrast, PrFT was negatively correlated with CT L-S ( β =−0.188, P <0.001). Furthermore, PrFT was also significantly associated with MAFLD independent of VFA and SFA, the OR (95% CI) was 1.279 (1.191–1.374). Meanwhile, PrFT also had a good identifying value for MAFLD as VFA. The area under the curve (95% CI) value of PrFT identifying MAFLD was 0.782 (0.751–0.812). The optimal cut-off value of PrFT was 12.6mm, with a sensitivity of 77.8% and specificity of 70.8%. Conclusion PrFT was independently associated with MAFLD, NFS, and FIB-4 and showed a similar identifying value for MAFLD as VFA, which suggested that PrFT can be used as an alternative index to VFA.

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Effects of perirenal fat thickness on postoperative renal dysfunction in patients who underwent robot‐assisted partial nephrectomy for renal tumours

Nishikawa,

Morizane,

Yamamoto

et al. 2024

Robotics Computer Surgery

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BackgroundDespite partial nephrectomy (PN) renal function preservation benefits, postoperative renal dysfunction may occur. Perirenal fat thickness (PFT) is associated with renal dysfunction such as diabetes; however, its role in renal tumour surgery is unclear. This study investigates the role of PFT in renal function after robot‐assisted partial nephrectomy (RAPN).MethodsPre‐operative factors for postoperative renal dysfunction were analysed in 156 patients undergoing RAPN with ≥1‐year follow‐up. PFT measured using computed tomography categorised patients with PFT >21.0 mm (median) as high‐PFT.ResultsTumour size, total R.E.N.A.L. nephrometry score and its N component, renal calyx opening, achievement of trifecta, and PFT were risk factors for renal dysfunction 1 year postoperatively. Age ≥75 years (p = 0.024), total RNS ≥7 (p = 0.036), and PFT >21.0 mm (p = 0.002) significantly correlated with postoperative renal dysfunction.ConclusionsCT‐measured PFT is a valuable predictor of postoperative renal dysfunction.

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Relationship of Para and Perirenal Fat and High-Density Lipoprotein and Its Function in Patients with Type 2 Diabetes Mellitus

Cited by 4 publications

References 28 publications

The association between obesity indicators and metabolic risk factors in type-2 diabetic patients

The association between obesity indicators and metabolic risk factors in type-2 diabetic patients

Perirenal Fat Thickness is Associated with Metabolic Dysfunction-Associated Fatty Liver Disease in Type 2 Diabetes Mellitus

Effects of perirenal fat thickness on postoperative renal dysfunction in patients who underwent robot‐assisted partial nephrectomy for renal tumours

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