Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients
Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this populat...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Pinar, Ugo [verfasserIn] Mageau, Arthur [verfasserIn] Renard, Yohann [verfasserIn] Rod, Xavier [verfasserIn] Lebacle, Cédric [verfasserIn] Barrou, Benoit [verfasserIn] Zaidan, Mohamad [verfasserIn] Irani, Jacques [verfasserIn] Bessede, Thomas [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
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| Übergeordnetes Werk: |
Enthalten in: International urology and nephrology - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969, 53(2021), 12 vom: 18. Sept., Seite 2469-2475 |
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| Übergeordnetes Werk: |
volume:53 ; year:2021 ; number:12 ; day:18 ; month:09 ; pages:2469-2475 |
| Links: |
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| DOI / URN: |
10.1007/s11255-021-02995-4 |
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| Katalog-ID: |
SPR045602034 |
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| 245 | 1 | 0 | |a Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients |
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| 520 | |a Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. | ||
| 650 | 4 | |a Body mass index |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Obesity |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Kidney transplantation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Adipose tissue |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Delayed graft function |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Mageau, Arthur |e verfasserin |4 aut | |
| 700 | 1 | |a Renard, Yohann |e verfasserin |4 aut | |
| 700 | 1 | |a Rod, Xavier |e verfasserin |4 aut | |
| 700 | 1 | |a Lebacle, Cédric |e verfasserin |4 aut | |
| 700 | 1 | |a Barrou, Benoit |e verfasserin |4 aut | |
| 700 | 1 | |a Zaidan, Mohamad |e verfasserin |4 aut | |
| 700 | 1 | |a Irani, Jacques |e verfasserin |4 aut | |
| 700 | 1 | |a Bessede, Thomas |e verfasserin |4 aut | |
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10.1007/s11255-021-02995-4 doi (DE-627)SPR045602034 (SPR)s11255-021-02995-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.88 bkl Pinar, Ugo verfasserin aut Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. Body mass index (dpeaa)DE-He213 Obesity (dpeaa)DE-He213 Kidney transplantation (dpeaa)DE-He213 Adipose tissue (dpeaa)DE-He213 Delayed graft function (dpeaa)DE-He213 Mageau, Arthur verfasserin aut Renard, Yohann verfasserin aut Rod, Xavier verfasserin aut Lebacle, Cédric verfasserin aut Barrou, Benoit verfasserin aut Zaidan, Mohamad verfasserin aut Irani, Jacques verfasserin aut Bessede, Thomas verfasserin aut Enthalten in International urology and nephrology Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 53(2021), 12 vom: 18. Sept., Seite 2469-2475 (DE-627)320529134 (DE-600)2015547-5 1573-2584 nnns volume:53 year:2021 number:12 day:18 month:09 pages:2469-2475 https://dx.doi.org/10.1007/s11255-021-02995-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.88 ASE AR 53 2021 12 18 09 2469-2475 |
| spelling |
10.1007/s11255-021-02995-4 doi (DE-627)SPR045602034 (SPR)s11255-021-02995-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.88 bkl Pinar, Ugo verfasserin aut Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. Body mass index (dpeaa)DE-He213 Obesity (dpeaa)DE-He213 Kidney transplantation (dpeaa)DE-He213 Adipose tissue (dpeaa)DE-He213 Delayed graft function (dpeaa)DE-He213 Mageau, Arthur verfasserin aut Renard, Yohann verfasserin aut Rod, Xavier verfasserin aut Lebacle, Cédric verfasserin aut Barrou, Benoit verfasserin aut Zaidan, Mohamad verfasserin aut Irani, Jacques verfasserin aut Bessede, Thomas verfasserin aut Enthalten in International urology and nephrology Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 53(2021), 12 vom: 18. Sept., Seite 2469-2475 (DE-627)320529134 (DE-600)2015547-5 1573-2584 nnns volume:53 year:2021 number:12 day:18 month:09 pages:2469-2475 https://dx.doi.org/10.1007/s11255-021-02995-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.88 ASE AR 53 2021 12 18 09 2469-2475 |
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10.1007/s11255-021-02995-4 doi (DE-627)SPR045602034 (SPR)s11255-021-02995-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.88 bkl Pinar, Ugo verfasserin aut Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. Body mass index (dpeaa)DE-He213 Obesity (dpeaa)DE-He213 Kidney transplantation (dpeaa)DE-He213 Adipose tissue (dpeaa)DE-He213 Delayed graft function (dpeaa)DE-He213 Mageau, Arthur verfasserin aut Renard, Yohann verfasserin aut Rod, Xavier verfasserin aut Lebacle, Cédric verfasserin aut Barrou, Benoit verfasserin aut Zaidan, Mohamad verfasserin aut Irani, Jacques verfasserin aut Bessede, Thomas verfasserin aut Enthalten in International urology and nephrology Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 53(2021), 12 vom: 18. Sept., Seite 2469-2475 (DE-627)320529134 (DE-600)2015547-5 1573-2584 nnns volume:53 year:2021 number:12 day:18 month:09 pages:2469-2475 https://dx.doi.org/10.1007/s11255-021-02995-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.88 ASE AR 53 2021 12 18 09 2469-2475 |
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10.1007/s11255-021-02995-4 doi (DE-627)SPR045602034 (SPR)s11255-021-02995-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.88 bkl Pinar, Ugo verfasserin aut Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. Body mass index (dpeaa)DE-He213 Obesity (dpeaa)DE-He213 Kidney transplantation (dpeaa)DE-He213 Adipose tissue (dpeaa)DE-He213 Delayed graft function (dpeaa)DE-He213 Mageau, Arthur verfasserin aut Renard, Yohann verfasserin aut Rod, Xavier verfasserin aut Lebacle, Cédric verfasserin aut Barrou, Benoit verfasserin aut Zaidan, Mohamad verfasserin aut Irani, Jacques verfasserin aut Bessede, Thomas verfasserin aut Enthalten in International urology and nephrology Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 53(2021), 12 vom: 18. Sept., Seite 2469-2475 (DE-627)320529134 (DE-600)2015547-5 1573-2584 nnns volume:53 year:2021 number:12 day:18 month:09 pages:2469-2475 https://dx.doi.org/10.1007/s11255-021-02995-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.88 ASE AR 53 2021 12 18 09 2469-2475 |
| allfieldsSound |
10.1007/s11255-021-02995-4 doi (DE-627)SPR045602034 (SPR)s11255-021-02995-4-e DE-627 ger DE-627 rakwb eng 610 ASE 44.88 bkl Pinar, Ugo verfasserin aut Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. Body mass index (dpeaa)DE-He213 Obesity (dpeaa)DE-He213 Kidney transplantation (dpeaa)DE-He213 Adipose tissue (dpeaa)DE-He213 Delayed graft function (dpeaa)DE-He213 Mageau, Arthur verfasserin aut Renard, Yohann verfasserin aut Rod, Xavier verfasserin aut Lebacle, Cédric verfasserin aut Barrou, Benoit verfasserin aut Zaidan, Mohamad verfasserin aut Irani, Jacques verfasserin aut Bessede, Thomas verfasserin aut Enthalten in International urology and nephrology Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 53(2021), 12 vom: 18. Sept., Seite 2469-2475 (DE-627)320529134 (DE-600)2015547-5 1573-2584 nnns volume:53 year:2021 number:12 day:18 month:09 pages:2469-2475 https://dx.doi.org/10.1007/s11255-021-02995-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.88 ASE AR 53 2021 12 18 09 2469-2475 |
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Enthalten in International urology and nephrology 53(2021), 12 vom: 18. Sept., Seite 2469-2475 volume:53 year:2021 number:12 day:18 month:09 pages:2469-2475 |
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Body mass index Obesity Kidney transplantation Adipose tissue Delayed graft function |
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Pinar, Ugo @@aut@@ Mageau, Arthur @@aut@@ Renard, Yohann @@aut@@ Rod, Xavier @@aut@@ Lebacle, Cédric @@aut@@ Barrou, Benoit @@aut@@ Zaidan, Mohamad @@aut@@ Irani, Jacques @@aut@@ Bessede, Thomas @@aut@@ |
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We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. 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Pinar, Ugo |
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Pinar, Ugo ddc 610 bkl 44.88 misc Body mass index misc Obesity misc Kidney transplantation misc Adipose tissue misc Delayed graft function Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients |
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610 ASE 44.88 bkl Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients Body mass index (dpeaa)DE-He213 Obesity (dpeaa)DE-He213 Kidney transplantation (dpeaa)DE-He213 Adipose tissue (dpeaa)DE-He213 Delayed graft function (dpeaa)DE-He213 |
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Pinar, Ugo Mageau, Arthur Renard, Yohann Rod, Xavier Lebacle, Cédric Barrou, Benoit Zaidan, Mohamad Irani, Jacques Bessede, Thomas |
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pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients |
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Pre-transplant morphometry by computed tomography scan and post-transplant dialysis risk in overweight or obese kidney transplant recipients |
| abstract |
Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. © The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
| abstractGer |
Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. © The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
| abstract_unstemmed |
Purpose Adipose distribution and sarcopenia could better assess kidney transplantation outcomes than body mass index (BMI) and have been poorly evaluated among obese and overweight recipients. We aimed to evaluate morphometric radiologic markers to predict post-operative dialysis within this population. Methods We conducted a retrospective study including patients with a BMI > 25 kg/$ m^{2} $ undergoing kidney transplantation during 5 years. Subcutaneous adipose tissue surface (SAT), visceral adipose tissue surface (VAT), and psoas surface were measured on CT scans sections. A model predictive of post-transplantation dialysis was elaborated through a multivariable logistic regression and was compared to a model including only BMI. Results Overall, 248 patients were included whom mean (SD) BMI and age were, respectively, 29.7 kg/m2 (3.6) and 56 years (12.7). Of them, 83 (33.5%) needed dialysis: 14 (5.7%) for primary kidney failure and 69 (27.8%) for delayed kidney function. On multivariable analysis, SAT, VAT and deceased donor were significantly associated with post-operative dialysis (respectively, OR [95%CI]:1.6 [1.1–2.6], 1.6[1.1–2.6], and 7.5 [1.6–56]). The area under the curve of this predictive model was 0.70 versus 0.64 for a BMI-based model. Conclusion High VAT and SAT were associated with post-transplantation dialysis. A predictive model based on these morphometrics could provide a better appreciation of graft recovery after transplantation among obese and overweight recipients. External validation is needed. © The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
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|
| score |
7.401101 |