196,060 research outputs found
U-shape association between hemoglobin A1c and late mortality in patients with heart failure after cardiac surgery
No full textHemoglobin A1c (HbA1c) levels are used as a measure of glycemic control, with greater levels indicating poorer control and a greater risk of death. However, recent studies have found a U-shaped association between the HbA1c levels and mortality in patients with heart failure, with the lowest risk of death associated with elevated HbA1c levels, usually 7percent. Cardiac surgery is frequently used to mitigate the signs and symptoms of heart failure. The purpose of the present study was to determine the association between HbA1c levels and late mortality in cardiac surgery patients with and without heart failure. Patients with and without New York Heart Association class III or IV heart failure were divided into quartiles according to the preoperative HbA1c level. Mortality was determined for each group and compared using chi-square tests and Cox modeling. Of the 311 patients with heart failure, 65 (21percent) were dead at follow-up compared to 57 of 669 patients (9percent) without heart failure (p 0.001). After adjusting for confounders, the patients without heart failure and with HbA1c ≤5.7percent had the lowest risk of death. In patients with preoperative heart failure, we found a U-shaped association between HbA1c levels and late mortality, with those patients with HbA1c levels of 5.8percent to 6.2percent having the lowest risk of death. HbA1c levels ≤5.7percent and ≥7.2percent were associated with statistically significant greater risks of death. In conclusion, we found in patients with heart failure that the lowest risk of death was associated with HbA1c levels of 5.8percent to 6.2percent. © 2013 Elsevier Inc. All rights reserved.Aguilar D, 2009, J AM COLL CARDIOL, V54, P422, DOI 10.1016-j.jacc.2009.04.049; Bilinska M, 2007, CORONARY ARTERY DIS, V18, P455, DOI 10.1097-MCA.0b013e3282a30676; Engoren M, 2008, J CARDIOTHORAC SURG, V3, DOI 10.1186-1749-8090-3-63; Eshaghian S, 2006, AM HEART J, V151; Gallagher AM, 2011, PLOS ONE, V6, DOI 10.1371-journal.pone.0028157; Guder G, 2009, CIRC-HEART FAIL, V2, P563, DOI 10.1161-CIRCHEARTFAILURE.108.825059; HARRELL FE, 1982, JAMA-J AM MED ASSOC, V247, P2543, DOI 10.1001-jama.247.18.2543; Nieto FJ, 1996, AM J EPIDEMIOL, V143, P1059; Pantalone KM, 2012, DIABETES OBES METAB, V14, P803, DOI 10.1111-j.1463-1326.2012.01604.x; Pencina MJ, 2004, STAT MED, V23, P2109, DOI 10.1002-sim.1802; Smooke S, 2005, AM HEART J, V149, P168, DOI 10.1016-j.ahj.2004.07.005; Tomova GS, 2012, AM J CARDIOL, V109, P1767, DOI 10.1016-j.amjcard.2012.02.0220
The independent effects of anemia and transfusion on mortality after coronary artery bypass
No full textBackground Both anemia and transfusions (Tx) are associated with mortality after cardiac operations. However, the relative contributions of anemia and Tx and their interaction on late mortality have not been determined. Methods 922 patients who underwent isolated coronary artery bypass grafting (CABG) were retrospectively studied. Anemia (A+) was defined as hemoglobin 12 g-dL for men and 11 g-dL for women. Patients who received (Tx+) and did not receive (Tx-) transfusions were compared; patient characteristics were controlled for by the use of Cox analysis and then by matching Tx+ to Tx- patients based on identical hemoglobin levels at admission and by propensity matching. Results 5.3percent of Tx- patients died, compared with 11percent of Tx+ patients (p = 0.001). The interaction of anemia and Tx was associated with a greater hazard of dying. In particular, A+Tx+ (anemic, received transfusion) patients had a threefold hazard of death (2.918, 95percent confidence interval = 1.512-5.633, p = 0.001) compared with A-Tx- (nonanemic, no transfusion) patients. A+Tx+ patients had twice the hazard of dying as did A+Tx- (anemic, no transfusion) (hazard ratio = 2.087, 95percent confidence interval = 1.004-4.336, p = 0.049). In populations matched by preoperative hemoglobin levels or by propensity scores, similar results were seen: a significant interaction between anemia and transfusion of red blood cells. A+Tx+ patients fared significantly worse than did the other three groups. Although there was no difference in mortality between A- patients who did or did not receive transfusions, A+T+ patients had triple the risk as A+T- patients, whereas A+Tx- patients had a similar risk of late mortality as A-Tx- patients. Conclusions The anemia-transfusion interaction was associated with an increased hazard of late mortality. © 2014 by The Society of Thoracic Surgeons Published by Elsevier Inc.Boening A, 2011, ANN THORAC SURG, V92, P805, DOI 10.1016-j.athoracsur.2011.02.076; Carson JL, 2012, ANN INTERN MED, V157, P49, DOI 10.7326-0003-4819-157-1-201206190-00429; Dardashti A, 2011, ACTA ANAESTH SCAND, V55, P952, DOI 10.1111-j.1399-6576.2011.02445.x; Engoren M, 2009, AM J CRIT CARE, V18, P124, DOI 10.4037-ajcc2009193; Engoren M, 2009, ANN THORAC SURG, V88, P95, DOI 10.1016-j.athoracsur.2009.04.047; Engoren M, 2008, J TRAUMA, V65, P1411, DOI 10.1097-TA.0b013e318157d9f9; Engoren M, 2014, ANN THORAC SURG, V97, P514, DOI 10.1016-j.athoracsur.2013.09.019; Engoren MC, 2002, ANN THORAC SURG, V74, P1180, DOI 10.1016-S0003-4975(02)03766-9; HARRELL FE, 1982, JAMA-J AM MED ASSOC, V247, P2543, DOI 10.1001-jama.247.18.2543; Johnston P, 2006, J ORTHOP TRAUMA, V20, P675, DOI 10.1097-01.bot.0000249435.25751.e8; Karkouti K, 2008, CIRCULATION, V117, P478, DOI 10.1161-CIRCULATIONAHA.107.718353; Karkouti K, 2012, ANESTHESIOLOGY, V117, P1175, DOI 10.1097-ALN.0b013e318271604e; Karski JM, 1999, CAN J ANAESTH, V46, P979; Koch CG, 2006, ANN THORAC SURG, V81, P1650, DOI 10.1016-j.athoracsur.2005.12.037; Kuduvalli M, 2005, EUR J CARDIO-THORAC, V27, P592, DOI 10.1016-j.ejcts.2005.01.030; Lambert N, 2003, AUTOIMMUN REV, V2, P133, DOI 10.1016-S1568-9972(02)00149-0; LEMESHOW S, 1988, STAT MED, V7, P759, DOI 10.1002-sim.4780070705; Nieto FJ, 1996, AM J EPIDEMIOL, V143, P1059; Pencina MJ, 2004, STAT MED, V23, P2109, DOI 10.1002-sim.1802; Ranucci M, 2012, ANN THORAC SURG, V94, P1134, DOI 10.1016-j.athoracsur.2012.04.042; Surgenor SD, 2009, ANESTH ANALG, V108, P1741, DOI 10.1213-ane.0b013e3181a2a696; Utter GH, 2007, VOX SANG, V93, P188, DOI 10.1111-j.1423-0410.2007.00954.x; Utter GH, 2006, TRANSFUSION, V46, P1863, DOI 10.1111-j.1537-2995.2006.00991.x; van Straten AHM, 2009, CIRCULATION, V120, P118, DOI 10.1161-CIRCULATIONAHA.109.85421635
Use of genetic programming, logistic regression, and artificial neural nets to predict readmission after coronary artery bypass surgery
No full textAs many as 14 percent of patients undergoing coronary artery bypass surgery are readmitted within 30 days. Readmission is usually the result of morbidity and may lead to death. The purpose of this study is to develop and compare statistical and genetic programming models to predict readmission. Patients were divided into separate Construction and Validation populations. Using 88 variables, logistic regression, genetic programs, and artificial neural nets were used to develop predictive models. Models were first constructed and tested on the Construction populations, then validated on the Validation population. Areas under the receiver operator characteristic curves (AU ROC) were used to compare the models. Two hundred and two patients (7.6 percent) in the 2,644 patient Construction group and 216 (8.0 percent) of the 2,711 patient Validation group were re-admitted within 30 days of CABG surgery. Logistic regression predicted readmission with AU ROC =.675 ±.021 in the Construction group. Genetic programs significantly improved the accuracy, AU ROC =.767 ±.001, p .001). Artificial neural nets were less accurate with AU ROC = 0.597 ±.001 in the Construction group. Predictive accuracy of all three techniques fell in the Validation group. However, the accuracy of genetic programming (AU ROC =.654 ±.001) was still trivially but statistically non-significantly better than that of the logistic regression (AU ROC =.644 ±.020, p =.61). Genetic programming and logistic regression provide alternative methods to predict readmission that are similarly accurate. © 2013 Springer Science+Business Media New York.Afessa B, 2005, INTENS CARE MED, V31, P1537, DOI 10.1007-s00134-005-2751-9; Biesheuvel CJ, 2004, J CLIN EPIDEMIOL, V57, P551, DOI 10.1016-j.jclinepi.2003.10.011; Efron B., 1993, INTRO BOOTSTRAP; Engoren M, 2008, GENET PROGRAM EVOL M, V9, P39, DOI 10.1007-s10710-007-9050-x; Engoren Milo, 2005, Chest, V127, P579, DOI 10.1378-chest.127.2.579; HANLEY JA, 1983, RADIOLOGY, V148, P839; Hannan EL, 2003, JAMA-J AM MED ASSOC, V290, P773, DOI 10.1001-jama.290.6.773; Hannan EL, 2011, JACC-CARDIOVASC INTE, V4, P569, DOI 10.1016-j.jcin.2011.01.010; Jacob C., 2001, ILLUSTRATING EVOLUTI; Kotini A, 2005, THEOR BIOL MED MODEL, V2, DOI 10.1186-1742-4682-2-37; Koza J., 1992, GENETIC PROGRAMMING; Lahey SJ, 1998, CIRCULATION S2, V98, pII35; Lee JL, 1980, CIRCULATION, V61, P508; Liu Y, 2004, P 8 IEEE S HIGH ASS, P54; McNally P, 2005, Ir Med J, V98, P240; Murphy BM, 2008, EUR J CARDIOV PREV R, V15, P210, DOI 10.1097-HJR.0b013e3282f2dc4e; Oxlad M, 2006, J PSYCHOSOM RES, V61, P775, DOI 10.1016-j.jpsychores.2006.09.008; Perez A, 2002, STAT MED, V21, P3885, DOI 10.1002-sim.1391; Scheier MF, 1999, ARCH INTERN MED, V159, P829, DOI 10.1001-archinte.159.8.829; Scott MJJ, 1998, 9 BRIT MACH VIS C, P304; Steuer J, 2002, ANN THORAC SURG, V73, P1380, DOI 10.1016-S0003-4975(02)03467-7; Stewart RD, 2000, ANN THORAC SURG, V70, P169, DOI 10.1016-S0003-4975(00)01386-2; Tully PJ, 2008, J BEHAV MED, V31, P281, DOI 10.1007-s10865-008-9153-8; Vaccarino V, 2003, J AM COLL CARDIOL, V41, P307, DOI 10.1016-S0735-1097(02)02698-0; Veltri RW, 2002, CLIN CHEM, V48, P1828; Zitser-Gurevich Y, 1999, MED CARE, V37, P625, DOI 10.1097-00005650-199907000-0000223
Hyperglycemia, hypoglycemia, and glycemic complexity are associated with worse outcomes after surgery
No full textPurpose: The purpose of this study was to determine if glycemic complexity, along with hypoglycemia and hyperglycemia, was associated with worse outcomes after cardiac surgery. Materials and methods: We conducted a retrospective analysis of 970 patients who had insulin infusions designed to keep blood glucose levels between 80 and 110 mg-dL. Glycemic complexity was calculated using jackknifed approximate entropy. Logistic regression was used to adjust for confounders. Results: A total of 495 patients (51percent) developed complications, and 32 patients (3.3percent) died. Along with older age, comorbidities, and complicated surgeries, any hypoglycemia (glucose 71 mg-dL) and the number of glucose values greater than 140 mg-dL were independent predictors of complications. Increased risk of mortality, after adjusting for other risk factors, was associated with older age, longer perfusion time, receiving intraoperative transfusions, and greater jackknifed approximate entropy of the glucose time series. Conclusion: We found that hypoglycemia (glucose 71 mg-dL) and hyperglycemia (glucose 140 mg-dL) were associated with increased risk of complications, whereas greater complexity of the glucose time series was associated with mortality. © 2014 Elsevier Inc.Amir J, 2011, CELL IMMUNOL, V272, P45, DOI 10.1016-j.cellimm.2011.09.008; Bagshaw SM, 2009, CRIT CARE, V13, DOI 10.1186-cc7921; Cochran WG, 1967, SAMPLING TECHNIQUES, P154; Cueni-Villoz N, 2011, CRIT CARE MED, V39, P2225, DOI 10.1097-CCM.0b013e31822572c9; D'Ancona G, 2011, EUR J CARDIO-THORAC, V40, P360, DOI 10.1016-j.ejcts.2010.11.065; Egi M, 2010, MAYO CLIN PROC, V85, P217, DOI 10.4065-mcp.2009.0394; Engoren M, 2009, J APPL PHYSIOL, V106, P766, DOI 10.1152-japplphysiol.90575.2008; Finfer S, 2009, NEW ENGL J MED, V360, P1283, DOI 10.1056-NEJMoa0810625; Finney SJ, 2003, JAMA-J AM MED ASSOC, V290, P2041, DOI 10.1001-jama.290.15.2041; Hermanides J, 2010, CRIT CARE MED, V38, P838, DOI 10.1097-CCM.0b013e3181cc4be9; Hermanides J, 2010, CRIT CARE MED, V38, P1430, DOI 10.1097-CCM.0b013e3181de562c; Hollingdal M, 2000, DIABETES, V49, P1334, DOI 10.2337-diabetes.49.8.1334; Kemeny SF, 2011, J BIOMECH, V44, P1927, DOI 10.1016-j.jbiomech.2011.04.026; Krinsley JS, 2004, MAYO CLIN PROC, V79, P992; Krinsley James Stephen, 2009, J Diabetes Sci Technol, V3, P1292; Lazar HL, 2009, ANN THORAC SURG, V87, P663, DOI 10.1016-j.athoracsur.2008.11.011; Li J, 2006, PHYS REV E, V73, DOI 10.1103-PhysRevE.73.052902; Mackenzie IMJ, 2011, INTENS CARE MED, V37, P435, DOI 10.1007-s00134-010-2103-2; Meyfroidt G, 2011, INTENS CARE MED, V37, P1151, DOI 10.1007-s00134-011-2159-7; Meyfroidt G, 2010, CRIT CARE MED, V38, P1021, DOI 10.1097-CCM.0b013e3181cf710e; Pappada SM, 2011, DIABETES TECHNOL THE, V13, P135, DOI 10.1089-dia.2010.0104; Pincus SM, 2008, J PSYCHIATR RES, V42, P337, DOI 10.1016-j.jpsychires.2007.01.001; Suh SW, 2007, GLIA, V55, P1280, DOI 10.1002-glia.20440; Van den Berghe G, 2006, NEW ENGL J MED, V354, P449, DOI 10.1056-NEJMoa052521; Van den Berghe G, 2001, NEW ENGL J MED, V345, P1359, DOI 10.1056-NEJMoa011300; Wang X, 2009, THESIS U VIRGINIA; Wessel N, 2000, PHYS REV E, V61, P733, DOI 10.1103-PhysRevE.61.7330
Ketorolac improves graft patency after coronary artery bypass grafting: A propensity-matched analysis
No full textBackground: The use of ketorolac, a potent cyclooxygenase-1 inhibitor, for analgesia after cardiac operations has been limited by concerns of increased cardiovascular events. However, a recent study found that its use after coronary artery bypass grafting was associated with improved survival. Methods: This was a retrospective study of patients who received coronary arteriograms for symptoms suggestive of recurrent ischemic heart disease. Patients who received postoperative ketorolac were matched with nonusers by propensity scores. Graft occlusion rates were compared, and their association with ketorolac use was compared using Cox proportional hazard modeling. Results: Although the rate of graft occlusion was similar in the two groups, in 184 of the 303 propensity-matched patients (61percent) who received ketorolac vs 202 of the 303 patients (67percent) who did not (p = 0.13), there was a longer time to angiographically proven occlusion in the patients who received ketorolac (2.80 ± 2.19 vs 2.04 ± 1.63 years; p 0.001). Cox modeling to control for the other variables and the longer time to angiography in the ketorolac group showed that ketorolac use was associated with nearly a halving of the hazard ratio (0.561; 95percent confidence interval, 0.454 to 0.692; p 0.001) for any graft occlusion. Conclusions: The use of ketorolac after coronary artery bypass grafting was associated with a lower rate of angiographically proven graft closure and suggests a mechanistic (improved graft patency) explanation for the previously reported survival benefit of ketorolac. © 2011 The Society of Thoracic Surgeons.Austin PC, 2009, COMMUN STAT-SIMUL C, V38, P1228, DOI 10.1080-03610910902859574; Austin PC, 2011, PHARM STAT, V10, P150, DOI 10.1002-pst.433; Baker CSR, 1999, ARTERIOSCL THROM VAS, V19, P646; Beattie WS, 1997, ANESTH ANALG, V84, P715, DOI 10.1097-00000539-199704000-00003; Bozzo J, 2001, J CARDIOVASC PHARM, V38, P183, DOI 10.1097-00005344-200108000-00003; Brambilla M, 2010, THROMB HAEMOSTASIS, V103, P516, DOI 10.1160-TH09-07-0470; Bunimov Natalia, 2008, Cardiovascular and Hematological Disorders - Drug Targets, V8, P268, DOI 10.2174-187152908786786250; CAMPEAU L, 1984, NEW ENGL J MED, V311, P1329, DOI 10.1056-NEJM198411223112101; Catella-Lawson F, 2001, NEW ENGL J MED, V345, P1809, DOI 10.1056-NEJMoa003199; DAVIES GC, 1980, CIRCULATION, V61, P808; Engoren M, 2001, ANESTH ANALG, V93, P859, DOI 10.1097-00000539-200110000-00011; Engoren MC, 2007, J CARDIOTHOR VASC AN, V21, P820, DOI 10.1053-j.jvca.2007.01.024; FDA U.S. Food and Drug Administration, COX 2 SEL INCL BEXTR; FitzGibbon GM, 1996, J AM COLL CARDIOL, V28, P616, DOI 10.1016-0735-1097(96)00206-9; FLURY BK, 1986, AM STAT, V40, P249, DOI 10.2307-2684560; GAVAGHAN TP, 1991, CIRCULATION, V83, P1526; GRANADOSSOTO V, 1995, EUR J PHARMACOL, V277, P281, DOI 10.1016-0014-2999(95)00123-3; Kalapatapu Venkat R, 2007, Vasc Endovascular Surg, V41, P402, DOI 10.1177-1538574407304506; Kimmel SE, 2002, PHARMACOEPIDEM DR S, V11, P113, DOI 10.1002-pds.670; LYTLE BW, 1985, J THORAC CARDIOV SUR, V89, P248; Mangano DT, 2002, NEW ENGL J MED, V347, P1309, DOI 10.1056-NEJMoa020798; Niemi TT, 2000, ACTA ANAESTH SCAND, V44, P69, DOI 10.1034-j.1399-6576.2000.440113.x; Nieto FJ, 1996, AM J EPIDEMIOL, V143, P1059; Nussmeier NA, 2005, NEW ENGL J MED, V352, P1081, DOI 10.1056-NEJMoa050330; Nuttall GA, 2008, ANESTHESIOLOGY, V108, P3; Ott E, 2003, J THORAC CARDIOV SUR, V125, P1481, DOI 10.1016-S0022-5223(3)00125-9; Ranucci M, 1999, Minerva Anestesiol, V65, P859; Sanioglu S, 2009, THORAC CARDIOV SURG, V57, P281, DOI 10.1055-s-0029-1185564; Shufflebarger JV, 1996, PLAST RECONSTR SURG, V98, P140, DOI 10.1097-00006534-199607000-00022; Stuart EA, 2008, STAT MED, V27, P2062, DOI 10.1002-sim.3207; Warner TD, 1999, P NATL ACAD SCI USA, V96, P7563, DOI 10.1073-pnas.96.13.7563; Yilmaz MB, 2005, THROMB RES, V115, P25, DOI 10.1016-j.thromres.2004.07.00454
Table_4_supplementary – Supplemental material for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review
No full textSupplemental material, Table_4_supplementary for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review by Elizabeth R. Eisenhauer, Alan R. Tait, Soo Young Rieh and Cynthia M. Arslanian-Engoren in Clinical Nursing Research</p
Table_3_supplementary – Supplemental material for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review
No full textSupplemental material, Table_3_supplementary for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review by Elizabeth R. Eisenhauer, Alan R. Tait, Soo Young Rieh and Cynthia M. Arslanian-Engoren in Clinical Nursing Research</p
Table_2_(7)_supplementary – Supplemental material for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review
No full textSupplemental material, Table_2_(7)_supplementary for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review by Elizabeth R. Eisenhauer, Alan R. Tait, Soo Young Rieh and Cynthia M. Arslanian-Engoren in Clinical Nursing Research</p
Table_1_(12)_Supplementary – Supplemental material for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review
No full textSupplemental material, Table_1_(12)_Supplementary for Participants’ Understanding of Informed Consent for Biobanking: A Systematic Review by Elizabeth R. Eisenhauer, Alan R. Tait, Soo Young Rieh and Cynthia M. Arslanian-Engoren in Clinical Nursing Research</p
The effect of acute kidney injury and discharge creatinine level on mortality following cardiac surgery
No full textOBJECTIVES:: Acute kidney injury after cardiac surgery is associated with increased operative and late mortality. The objective was to determine if short and long term mortality are systematically improved with completeness of postoperative acute kidney injury reversal or with amount of residual renal function. DESIGN:: Retrospective, single center study. SETTING:: Tertiary care hospital. PATIENTS:: One thousand five hundred and forty-three cardiac surgery patients divided into acute kidney injury groups based on Kidney Disease International Group Outcome criteria. MEASUREMENTS AND MAIN RESULTS:: Operative mortality was 3.1percent overall and was progressively worse with increasing acute kidney injury: none (0.8percent), minimal (1.6percent), Kidney Disease International Group Outcome stage 1 (4.3percent), stage 2 (17percent), and stage 3 (29percent). Similar to the operative outcomes, late outcomes were progressively worse with rising amounts of acute kidney injury. The risk of late death was related to amount of acute kidney injury and remaining renal function at discharge. CONCLUSIONS:: Acute kidney injury was associated with higher operative and late mortality. Lesser amounts of residual renal function were associated with increased late mortality. © 2014 by the Society of Critical Care Medicine and Lippincott Williams and Wilkins.Brown JR, 2008, ANN THORAC SURG, V86, P4, DOI 10.1016-j.athoracsur.2008.03.006; Brown JR, 2010, ANN THORAC SURG, V90, P1142, DOI 10.1016-j.athoracsur.2010.04.039; Chawla LS, 2011, KIDNEY INT, V79, P1361, DOI 10.1038-ki.2011.42; Coca SG, 2009, AM J KIDNEY DIS, V53, P961, DOI 10.1053-j.ajkd.2008.11.034; HARRELL FE, 1982, JAMA-J AM MED ASSOC, V247, P2543, DOI 10.1001-jama.247.18.2543; Hobson CE, 2009, CIRCULATION, V119, P2444, DOI 10.1161-CIRCULATIONAHA.108.800011; Howell NJ, 2012, EUR J CARDIO-THORAC, V41, pE38, DOI 10.1093-ejcts-ezr329; Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group, 2012, KIDNEY INT S, P1; Lassnigg A, 2004, J AM SOC NEPHROL, V15, P1597, DOI 10.1097-01.ASN.0000130340.93930.DD; Levey AS, 1999, ANN INTERN MED, V130, P461; Levin A, 2014, KIDNEY INT, V85, P49, DOI 10.1038-ki.2013.444; Mehta RH, 2010, AM J CARDIOL, V106, P1728, DOI 10.1016-j.amjcard.2010.07.045; Piccinni P, 2011, MINERVA ANESTESIOL, V77, P1072; Ricci Z, 2008, KIDNEY INT, V73, P538, DOI 10.1038-sj.ki.5002743; Roger VL, 2012, CIRCULATION, V125, pE2, DOI 10.1161-CIR.0b013e31823ac046; Tian JM, 2009, AM J KIDNEY DIS, V53, P974, DOI 10.1053-j.ajkd.2009.02.007; Tolpin DA, 2012, J THORAC CARDIOV SUR, V143, P682, DOI 10.1016-j.jtcvs.2011.09.04411
- …
