BACKGROUND: Outcomes after kidney transplantation (KTx) remain limited by delayed graft function (DGF) and acute rejection. Non-invasive biomarkers may help identify patients at increased risk for these events. We examined the association between the systemic immune-inflammation index (SII), a novel inflammatory biomarker, and outcomes after KTx and evaluated its ability to predict post-transplant prognosis. PATIENTS AND METHODS: Adult patients who underwent primary KTx at our institution between 2016-2019 were included. SII was calculated from pre-transplant complete blood counts as the ratio of the neutrophil count to the lymphocyte count multiplied by the platelet count. The cutoff between high and low SII was determined by maximizing the area under the curve. Multivariable logistic and Cox regression were used to identify factors associated with DGF and patient, rejection-free, and graft survival respectively. RESULTS: Overall, 378 KTx recipients were included; 224 (59.3%) had high SII. On unadjusted analysis, high SII was associated with reduced odds of DGF, and improved patient and rejection-free survival. After adjustment, high SII was independently associated with improved patient survival alone. Multivariable models incorporating SII performed well for the prediction of DGF (c-statistic=0.755) and patient survival (c-statistic=0.786), though rejection-free survival was more difficult to predict (c-statistic=0.635). CONCLUSION: SII demonstrated limited utility as an independent predictor of outcomes after KTx. However, in combination with other clinically relevant parameters, SII is a useful predictor of post-KTx prognosis. Validation of this novel inflammatory biomarker in a multi-institutional study is needed to further elucidate its practical applications in transplantation. Copyright
BACKGROUND: Outcomes after kidney transplantation (KTx) remain limited by delayed graft function (DGF) and acute rejection. Non-invasive biomarkers may help identify patients at increased risk for these events. We examined the association between the systemic immune-inflammation index (SII), a novel inflammatory biomarker, and outcomes after KTx and evaluated its ability to predict post-transplant prognosis. PATIENTS AND METHODS: Adult patients who underwent primary KTx at our institution between 2016-2019 were included. SII was calculated from pre-transplant complete blood counts as the ratio of the neutrophil count to the lymphocyte count multiplied by the platelet count. The cutoff between high and low SII was determined by maximizing the area under the curve. Multivariable logistic and Cox regression were used to identify factors associated with DGF and patient, rejection-free, and graft survival respectively. RESULTS: Overall, 378 KTx recipients were included; 224 (59.3%) had high SII. On unadjusted analysis, high SII was associated with reduced odds of DGF, and improved patient and rejection-free survival. After adjustment, high SII was independently associated with improved patient survival alone. Multivariable models incorporating SII performed well for the prediction of DGF (c-statistic=0.755) and patient survival (c-statistic=0.786), though rejection-free survival was more difficult to predict (c-statistic=0.635). CONCLUSION: SII demonstrated limited utility as an independent predictor of outcomes after KTx. However, in combination with other clinically relevant parameters, SII is a useful predictor of post-KTx prognosis. Validation of this novel inflammatory biomarker in a multi-institutional study is needed to further elucidate its practical applications in transplantation. Copyright
Authors: Robert R Redfield; Joseph R Scalea; Tiffany J Zens; Brenda Muth; Dixon B Kaufman; Arjang Djamali; Brad C Astor; Maha Mohamed Journal: Transpl Int Date: 2015-10-26 Impact factor: 3.782
Authors: Florian W R Vondran; Kai Timrott; Sonja Kollrich; Ann-Kristin Steinhoff; Alexander Kaltenborn; Harald Schrem; Juergen Klempnauer; Frank Lehner; Reinhard Schwinzer Journal: Clin Transplant Date: 2014-07-22 Impact factor: 2.863
Authors: Piotr Hogendorf; Anna Suska; Aleksander Skulimowski; Joanna Rut; Monika Grochowska; Aleksandra Wencel; Filip Dziwisz; Michał Nowicki; Dariusz Szymański; Grażyna Poznańska; Adam Durczyński; Janusz Strzelczyk Journal: Pol Przegl Chir Date: 2018-04-30
Authors: A Hart; J M Smith; M A Skeans; S K Gustafson; A R Wilk; S Castro; J Foutz; J L Wainright; J J Snyder; B L Kasiske; A K Israni Journal: Am J Transplant Date: 2020-01 Impact factor: 8.086
Authors: Diamantis I Tsilimigras; Dimitrios Moris; Rittal Mehta; Anghela Z Paredes; Kota Sahara; Alfredo Guglielmi; Luca Aldrighetti; Matthew Weiss; Todd W Bauer; Sorin Alexandrescu; George A Poultsides; Shishir K Maithel; Hugo P Marques; Guillaume Martel; Carlo Pulitano; Feng Shen; Olivier Soubrane; Bas G Koerkamp; Itaru Endo; Timothy M Pawlik Journal: HPB (Oxford) Date: 2020-04-04 Impact factor: 3.647