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10.1093/ndt/gfu200 http://scihub22266oqcxt.onion/10.1093/ndt/gfu200 C4200038!4200038 !24920842     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=24920842 &cmd=llinks): Failed to open stream: HTTP request failed! 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A new clinical multivariable model that predicts postoperative acute kidney injury: impact of endogenous ouabain |pdf=|usr=}}{{24920842 }} gab.com Text A new clinical multivariable model that predicts postoperative acute kidney injury: impact of endogenous ouabain JO: Nephrol Dial Transplant http://www.kidney.de/pget.php?&tw=1&pmid=24920842 #FOAvip BACKGROUND: Acute kidney injury (AKI) is an important complication of cardiac surgery. Recently, elevated levels of endogenous ouabain (EO), an adrenal stress hormone with haemodynamic and renal effects, have been associated with worse renal outcome after cardiac surgery. Our aim was to develop and evaluate a new risk model of AKI using simple preoperative clinical parameters and to investigate the utility of EO. METHODS: The primary outcome was AKI according to Acute Kidney Injury Network stage II or III. We selected the Northern New England Cardiovascular Disease Study Group (NNECDSG) as a reference model. We built a new internal predictive risk model considering common clinical variables (CLIN-RISK), compared this model with the NNECDSG model and determined whether the addition of preoperative plasma EO improved prediction of AKI. RESULTS: All models were tested on >800 patients admitted for elective cardiac surgery in our hospital. Seventy-nine patients developed AKI (9.9%). Preoperative EO levels were strongly associated with the incidence of AKI and clinical complication (total ICU stay and in-hospital mortality). The NNECDSG model was confirmed as a good predictor of AKI (AUC 0.74, comparable to the NNECDSG reference population). Our CLIN-RISK model had improved predictive power for AKI (AUC 0.79, CI 95% 0.73-0.84). Furthermore, addition of preoperative EO levels to both clinical models improved AUC to 0.79 and to 0.83, respectively (?AUC +0.05 and +0.04, respectively, P < 0.01). CONCLUSION: In a population where the predictive power of the NNECDSG model was confirmed, CLIN-RISK was more powerful. Both clinical models were further improved by the addition of preoperative plasma EO levels. These new models provide improved predictability of the relative risk for the development of AKI following cardiac surgery and suggest that EO is a marker for renal vascular injury. Twit Text FOAVip A new clinical multivariable model that predicts postoperative acute kidney injury: impact of endogenous ouabain ????Nephrol Dial Transplant http://www.kidney.de/pget.php?&tw=1&pmid=24920842 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24920842 #FOAvip English Wikipedia <ref>{{Cite pmid|24920842 }}</ref> A new clinical multivariable model that predicts postoperative acute kidney injury: impact of endogenous ouabain #MMPMID24920842 Simonini M ; Lanzani C ; Bignami E ; Casamassima N ; Frati E ; Meroni R ; Messaggio E ; Alfieri O ; Hamlyn J ; Body SC ; Collard CD ; Zangrillo A ; Manunta P Nephrol Dial Transplant 2014[Sep]; 29 (9 ): 1696-701 PMID24920842 show ga BACKGROUND: Acute kidney injury (AKI) is an important complication of cardiac surgery. Recently, elevated levels of endogenous ouabain (EO), an adrenal stress hormone with haemodynamic and renal effects, have been associated with worse renal outcome after cardiac surgery. Our aim was to develop and evaluate a new risk model of AKI using simple preoperative clinical parameters and to investigate the utility of EO. METHODS: The primary outcome was AKI according to Acute Kidney Injury Network stage II or III. We selected the Northern New England Cardiovascular Disease Study Group (NNECDSG) as a reference model. We built a new internal predictive risk model considering common clinical variables (CLIN-RISK), compared this model with the NNECDSG model and determined whether the addition of preoperative plasma EO improved prediction of AKI. RESULTS: All models were tested on >800 patients admitted for elective cardiac surgery in our hospital. Seventy-nine patients developed AKI (9.9%). Preoperative EO levels were strongly associated with the incidence of AKI and clinical complication (total ICU stay and in-hospital mortality). The NNECDSG model was confirmed as a good predictor of AKI (AUC 0.74, comparable to the NNECDSG reference population). Our CLIN-RISK model had improved predictive power for AKI (AUC 0.79, CI 95% 0.73-0.84). Furthermore, addition of preoperative EO levels to both clinical models improved AUC to 0.79 and to 0.83, respectively (?AUC +0.05 and +0.04, respectively, P < 0.01). CONCLUSION: In a population where the predictive power of the NNECDSG model was confirmed, CLIN-RISK was more powerful. Both clinical models were further improved by the addition of preoperative plasma EO levels. These new models provide improved predictability of the relative risk for the development of AKI following cardiac surgery and suggest that EO is a marker for renal vascular injury. |*Decision Support Techniques [MESH] |Acute Kidney Injury/*blood/*epidemiology [MESH] |Aged [MESH] |Area Under Curve [MESH] |Biomarkers/blood [MESH] |Cardiac Surgical Procedures/*adverse effects [MESH] |Female [MESH] |Humans [MESH] |Logistic Models [MESH] |Male [MESH] |Middle Aged [MESH] |Models, Theoretical [MESH] |Ouabain/*blood [MESH] |Prognosis [MESH] |Risk Assessment [MESH]A new clinical multivariable model that predicts postoperative acute k(epmc).pdf DeepDyve Pubget Overpricing