Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy

Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. Al...
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Autor*in:	Hajian, Simin [verfasserIn] Ghoreifi, Alireza Cen, Steven Yong Varghese, Bino Lei, Xiaomeng Hwang, Darryl Tran, Khoa Tejura, Tapas Whang, Gilbert Djaladat, Hooman Duddalwar, Vinay

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Incisional hernia Nephrectomy Sarcopenia Abdominal visceral fat Abdominal subcutaneous fat

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: Skeletal radiology - Berlin : Springer, 1976, 52(2023), 12 vom: 30. Mai, Seite 2469-2477
Übergeordnetes Werk:	volume:52 ; year:2023 ; number:12 ; day:30 ; month:05 ; pages:2469-2477

Links:	Volltext

DOI / URN:	10.1007/s00256-023-04371-y

Katalog-ID:	SPR053429338

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245	1	0	\|a Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy
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520			\|a Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy.
650		4	\|a Incisional hernia \|7 (dpeaa)DE-He213
650		4	\|a Nephrectomy \|7 (dpeaa)DE-He213
650		4	\|a Sarcopenia \|7 (dpeaa)DE-He213
650		4	\|a Abdominal visceral fat \|7 (dpeaa)DE-He213
650		4	\|a Abdominal subcutaneous fat \|7 (dpeaa)DE-He213
700	1		\|a Ghoreifi, Alireza \|4 aut
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700	1		\|a Hwang, Darryl \|4 aut
700	1		\|a Tran, Khoa \|4 aut
700	1		\|a Tejura, Tapas \|4 aut
700	1		\|a Whang, Gilbert \|4 aut
700	1		\|a Djaladat, Hooman \|4 aut
700	1		\|a Duddalwar, Vinay \|4 aut
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allfields	10.1007/s00256-023-04371-y doi (DE-627)SPR053429338 (SPR)s00256-023-04371-y-e DE-627 ger DE-627 rakwb eng Hajian, Simin verfasserin aut Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. Incisional hernia (dpeaa)DE-He213 Nephrectomy (dpeaa)DE-He213 Sarcopenia (dpeaa)DE-He213 Abdominal visceral fat (dpeaa)DE-He213 Abdominal subcutaneous fat (dpeaa)DE-He213 Ghoreifi, Alireza aut Cen, Steven Yong aut Varghese, Bino aut Lei, Xiaomeng aut Hwang, Darryl aut Tran, Khoa aut Tejura, Tapas aut Whang, Gilbert aut Djaladat, Hooman aut Duddalwar, Vinay aut Enthalten in Skeletal radiology Berlin : Springer, 1976 52(2023), 12 vom: 30. Mai, Seite 2469-2477 (DE-627)254236855 (DE-600)1461957-X 1432-2161 nnns volume:52 year:2023 number:12 day:30 month:05 pages:2469-2477 https://dx.doi.org/10.1007/s00256-023-04371-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_267 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 AR 52 2023 12 30 05 2469-2477
spelling	10.1007/s00256-023-04371-y doi (DE-627)SPR053429338 (SPR)s00256-023-04371-y-e DE-627 ger DE-627 rakwb eng Hajian, Simin verfasserin aut Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. Incisional hernia (dpeaa)DE-He213 Nephrectomy (dpeaa)DE-He213 Sarcopenia (dpeaa)DE-He213 Abdominal visceral fat (dpeaa)DE-He213 Abdominal subcutaneous fat (dpeaa)DE-He213 Ghoreifi, Alireza aut Cen, Steven Yong aut Varghese, Bino aut Lei, Xiaomeng aut Hwang, Darryl aut Tran, Khoa aut Tejura, Tapas aut Whang, Gilbert aut Djaladat, Hooman aut Duddalwar, Vinay aut Enthalten in Skeletal radiology Berlin : Springer, 1976 52(2023), 12 vom: 30. Mai, Seite 2469-2477 (DE-627)254236855 (DE-600)1461957-X 1432-2161 nnns volume:52 year:2023 number:12 day:30 month:05 pages:2469-2477 https://dx.doi.org/10.1007/s00256-023-04371-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_267 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 AR 52 2023 12 30 05 2469-2477
allfields_unstemmed	10.1007/s00256-023-04371-y doi (DE-627)SPR053429338 (SPR)s00256-023-04371-y-e DE-627 ger DE-627 rakwb eng Hajian, Simin verfasserin aut Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. Incisional hernia (dpeaa)DE-He213 Nephrectomy (dpeaa)DE-He213 Sarcopenia (dpeaa)DE-He213 Abdominal visceral fat (dpeaa)DE-He213 Abdominal subcutaneous fat (dpeaa)DE-He213 Ghoreifi, Alireza aut Cen, Steven Yong aut Varghese, Bino aut Lei, Xiaomeng aut Hwang, Darryl aut Tran, Khoa aut Tejura, Tapas aut Whang, Gilbert aut Djaladat, Hooman aut Duddalwar, Vinay aut Enthalten in Skeletal radiology Berlin : Springer, 1976 52(2023), 12 vom: 30. Mai, Seite 2469-2477 (DE-627)254236855 (DE-600)1461957-X 1432-2161 nnns volume:52 year:2023 number:12 day:30 month:05 pages:2469-2477 https://dx.doi.org/10.1007/s00256-023-04371-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_267 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 AR 52 2023 12 30 05 2469-2477
allfieldsGer	10.1007/s00256-023-04371-y doi (DE-627)SPR053429338 (SPR)s00256-023-04371-y-e DE-627 ger DE-627 rakwb eng Hajian, Simin verfasserin aut Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. Incisional hernia (dpeaa)DE-He213 Nephrectomy (dpeaa)DE-He213 Sarcopenia (dpeaa)DE-He213 Abdominal visceral fat (dpeaa)DE-He213 Abdominal subcutaneous fat (dpeaa)DE-He213 Ghoreifi, Alireza aut Cen, Steven Yong aut Varghese, Bino aut Lei, Xiaomeng aut Hwang, Darryl aut Tran, Khoa aut Tejura, Tapas aut Whang, Gilbert aut Djaladat, Hooman aut Duddalwar, Vinay aut Enthalten in Skeletal radiology Berlin : Springer, 1976 52(2023), 12 vom: 30. Mai, Seite 2469-2477 (DE-627)254236855 (DE-600)1461957-X 1432-2161 nnns volume:52 year:2023 number:12 day:30 month:05 pages:2469-2477 https://dx.doi.org/10.1007/s00256-023-04371-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_267 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 AR 52 2023 12 30 05 2469-2477
allfieldsSound	10.1007/s00256-023-04371-y doi (DE-627)SPR053429338 (SPR)s00256-023-04371-y-e DE-627 ger DE-627 rakwb eng Hajian, Simin verfasserin aut Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. Incisional hernia (dpeaa)DE-He213 Nephrectomy (dpeaa)DE-He213 Sarcopenia (dpeaa)DE-He213 Abdominal visceral fat (dpeaa)DE-He213 Abdominal subcutaneous fat (dpeaa)DE-He213 Ghoreifi, Alireza aut Cen, Steven Yong aut Varghese, Bino aut Lei, Xiaomeng aut Hwang, Darryl aut Tran, Khoa aut Tejura, Tapas aut Whang, Gilbert aut Djaladat, Hooman aut Duddalwar, Vinay aut Enthalten in Skeletal radiology Berlin : Springer, 1976 52(2023), 12 vom: 30. Mai, Seite 2469-2477 (DE-627)254236855 (DE-600)1461957-X 1432-2161 nnns volume:52 year:2023 number:12 day:30 month:05 pages:2469-2477 https://dx.doi.org/10.1007/s00256-023-04371-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_267 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 AR 52 2023 12 30 05 2469-2477
language	English
source	Enthalten in Skeletal radiology 52(2023), 12 vom: 30. Mai, Seite 2469-2477 volume:52 year:2023 number:12 day:30 month:05 pages:2469-2477
sourceStr	Enthalten in Skeletal radiology 52(2023), 12 vom: 30. Mai, Seite 2469-2477 volume:52 year:2023 number:12 day:30 month:05 pages:2469-2477
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Incisional hernia Nephrectomy Sarcopenia Abdominal visceral fat Abdominal subcutaneous fat
isfreeaccess_bool	true
container_title	Skeletal radiology
authorswithroles_txt_mv	Hajian, Simin @@aut@@ Ghoreifi, Alireza @@aut@@ Cen, Steven Yong @@aut@@ Varghese, Bino @@aut@@ Lei, Xiaomeng @@aut@@ Hwang, Darryl @@aut@@ Tran, Khoa @@aut@@ Tejura, Tapas @@aut@@ Whang, Gilbert @@aut@@ Djaladat, Hooman @@aut@@ Duddalwar, Vinay @@aut@@
publishDateDaySort_date	2023-05-30T00:00:00Z
hierarchy_top_id	254236855
id	SPR053429338
language_de	englisch
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Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. 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author	Hajian, Simin
spellingShingle	Hajian, Simin misc Incisional hernia misc Nephrectomy misc Sarcopenia misc Abdominal visceral fat misc Abdominal subcutaneous fat Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy
authorStr	Hajian, Simin
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topic_title	Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy Incisional hernia (dpeaa)DE-He213 Nephrectomy (dpeaa)DE-He213 Sarcopenia (dpeaa)DE-He213 Abdominal visceral fat (dpeaa)DE-He213 Abdominal subcutaneous fat (dpeaa)DE-He213
topic	misc Incisional hernia misc Nephrectomy misc Sarcopenia misc Abdominal visceral fat misc Abdominal subcutaneous fat
topic_unstemmed	misc Incisional hernia misc Nephrectomy misc Sarcopenia misc Abdominal visceral fat misc Abdominal subcutaneous fat
topic_browse	misc Incisional hernia misc Nephrectomy misc Sarcopenia misc Abdominal visceral fat misc Abdominal subcutaneous fat
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy
ctrlnum	(DE-627)SPR053429338 (SPR)s00256-023-04371-y-e
title_full	Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy
author_sort	Hajian, Simin
journal	Skeletal radiology
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container_start_page	2469
author_browse	Hajian, Simin Ghoreifi, Alireza Cen, Steven Yong Varghese, Bino Lei, Xiaomeng Hwang, Darryl Tran, Khoa Tejura, Tapas Whang, Gilbert Djaladat, Hooman Duddalwar, Vinay
container_volume	52
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author-letter	Hajian, Simin
doi_str_mv	10.1007/s00256-023-04371-y
title_sort	sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy
title_auth	Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy
abstract	Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. © The Author(s) 2023
abstractGer	Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. © The Author(s) 2023
abstract_unstemmed	Objective To assess the effect of body muscle and fat metrics on the development of radiologic incisional hernia (IH) following robotic nephrectomy. Materials and Methods We retrospectively reviewed the records of patients who underwent robotic nephrectomy for kidney tumors between 2011 and 2017. All pre- and postoperative CTs were re-reviewed by experienced radiologists for detection of radiologic IH and calculation of the following metrics using Synapse 3D software: cross-sectional psoas muscle mass at the level of L3 and L4 as well as subcutaneous and visceral fat areas. Sarcopenia was defined as psoas muscle index below the lowest quartile. Cox proportional hazard model was constructed to examine the association between muscle and fat metrics and the risk of developing radiologic IH. Results A total of 236 patients with a median (IQR) age of 64 (54–70) years were included in this study. In a median (IQR) follow-up of 23 (14–38) months, 62 (26%) patients developed radiologic IH. On Cox proportional hazard model, we were unable to detect an association between sarcopenia and risk of IH development. In terms of subcutaneous fat change from pre-op, both lower and higher values were associated with IH development (HR (95% CI) 2.1 (1.2–3.4), p = 0.01 and 2.4 (1.4–4.1), p < 0.01 for < Q1 and ≥ Q3, respectively). Similar trend was found for visceral fat area changes from pre-op with a HR of 2.8 for < Q1 and 1.8 for ≥ Q3. Conclusion Both excessive body fat gain and loss are associated with development of radiologic IH in patients undergoing robotic nephrectomy. © The Author(s) 2023
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container_issue	12
title_short	Sarcopenia and body fat change as risk factors for radiologic incisional hernia following robotic nephrectomy
url	https://dx.doi.org/10.1007/s00256-023-04371-y
remote_bool	true
author2	Ghoreifi, Alireza Cen, Steven Yong Varghese, Bino Lei, Xiaomeng Hwang, Darryl Tran, Khoa Tejura, Tapas Whang, Gilbert Djaladat, Hooman Duddalwar, Vinay
author2Str	Ghoreifi, Alireza Cen, Steven Yong Varghese, Bino Lei, Xiaomeng Hwang, Darryl Tran, Khoa Tejura, Tapas Whang, Gilbert Djaladat, Hooman Duddalwar, Vinay
ppnlink	254236855
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isOA_txt	true
hochschulschrift_bool	false
doi_str	10.1007/s00256-023-04371-y
up_date	2024-07-03T19:28:14.087Z
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