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Revised Cardiac Risk Index

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create these risk calculators. This tool includes adjusted ORs for different surgical sites, with inguinal hernia as the reference group. Target complications were defined as cardiac arrest (defined as "chaotic cardiac rhythm requiring initiation of basic or advanced life support") or MI (defined as ≥1 of the following: documented electrocardiographic findings of MI, ST elevation of ≥1 mm in >1 contiguous leads, new left bundle-branch block, new Q-wave in ≥2 contiguous leads, or troponin >3 times normal in setting of suspected ischemia).
64:). In 1999, Lee et al. published a cardiac risk index derived from 2893 patients and validated in 1422 patients aged ≥ 50 undergoing major noncardiac surgery, which became known as the Revised Cardiac Risk Index (RCRI). Lee identified six independent variables that predicted an increased risk for cardiac complications. A patient's risk for perioperative cardiac complications increased with number of variables that were present. 265:
Fleisher, L. A.; Beckman, J. A.; Brown, K. A.; Calkins, H.; Chaikof, E.; Fleischmann, K. E.; Freeman, W. K.; Froehlich, J. B.; Kasper, E. K.; Kersten, J. R.; Riegel, B.; Robb, J. F.; Smith Jr, S. C.; Jacobs, A. K.; Adams, C. D.; Anderson, J. L.; Antman, E. M.; Buller, C. E.; Creager, M. A.; Ettinger,
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surgeries, that claimed to supersede the RCRI in predictive performance. Unlike the RCRI, the CCoR mines the history of medical encounters to identify subtle comorbidity signatures that increase the risk of cardiac events, and was claimed to reliably assess "low-risk" patients, e.g., ones with none
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2014 ACC/AHA Perioperative Guidelines stated that two newer tools have been created by the American College of Surgeons, which prospectively collected data on operations performed in more than 252 participating hospitals in the United States. Data on more than 1 million operations have been used to
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analysis are incorporated into the risk index. Ideally, the accuracy and validity of the risk index is then tested in a separate cohort (the "validation cohort"). In 1977 Goldman, et al., developed the first cardiac risk index, which included nine variables associated with an increased risk of
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S. M.; Faxon, D. P.; Fuster, V.; Halperin, J. L.; Hiratzka, L. F.; Hunt, S. A.; Lytle, B. W.; Nishimura, R.; Ornato, J. P.; Page, R. L.; Riegel, B. (2007). "ACC/AHA 2007 Guidelines on Perioperative Cardiovascular Evaluation and Care for Noncardiac Surgery: Executive Summary".
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Goldman, L.; Caldera, D. L.; Nussbaum, S. R.; Southwick, F. S.; Krogstad, D.; Murray, B.; Burke, D. S.; O'Malley, T. A.; Goroll, A. H.; Caplan, C. H.; Nolan, J.; Carabello, B.; Slater, E. E. (1977). "Multifactorial Index of Cardiac Risk in Noncardiac Surgical Procedures".
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Compared with the Original Cardiac Risk Index, the RCRI was easier to use and more accurate. The RCRI was used widely in clinical practice, research, and was incorporated in a modified form into the 2007 preoperative cardiac risk evaluation guideline from the
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Lee, T. H.; Marcantonio, E. R.; Mangione, C. M.; Thomas, E. J.; Polanczyk, C. A.; Cook, E. F.; Sugarbaker, D. J.; Donaldson, M. C.; Poss, R.; Ho, K. K.; Ludwig, L. E.; Pedan, A.; Goldman, L. (1999).
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Fleisher, Lee A.; Fleischmann, Kirsten E.; Auerbach, Andrew D.; Barnason, Susan A.; Beckman, Joshua A.; Bozkurt, Biykem; Davila-Roman, Victor G.; Gerhard-Herman, Marie D.; Holly, Thomas A. (2014).
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complications. The RCRI and similar clinical prediction tools are derived by looking for an association between preoperative variables (e.g., patient's age, type of
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In 2022, Onishchenko et al. published the Cardiac Comorbidity Risk (CCoR) score for assessing the risk of major adverse cardiac events (MACE) after hip and knee
344:"Cardiac Comorbidity Risk Score: Zero‐Burden Machine Learning to Improve Prediction of Postoperative Major Adverse Cardiac Events in Hip and Knee Arthroplasty" 165: 124: 303:"2014 ACC/AHA Guideline on Perioperative Cardiovascular Evaluation and Management of Patients Undergoing Noncardiac Surgery" 223:"Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery" 120: 342:
Onishchenko, Dmytro; Rubin, Daniel S.; van Horne, James R.; Ward, R. Parker; Chattopadhyay, Ishanu (2022-08-02).
222: 407: 131:. The surgery-specific risk (#6 on the above list) is included separately in the algorithm. Criterion #4, 51:
of surgical patients (the "derivation cohort"). Variables that have independent predictive value in a
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0 predictors = 3.9%, 1 predictor = 6.0%, 2 predictors = 10.1%, ≥3 predictors = 15% (Duceppe 2017)
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Risk for cardiac death, nonfatal myocardial infarction, and nonfatal cardiac arrest:
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6. Undergoing suprainguinal vascular, intraperitoneal, or intrathoracic surgery
319: 302: 279: 242: 127:. The ACC/AHA guidelines use the 5 clinical RCRI criteria in their screening 359: 139:
use was also changed to any diagnosis of diabetes in the ACC/AHA algorithm.
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3. History of cerebrovascular disease (stroke or transient ischemic attack)
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Medical tool for measuring risk of perioperative cardiac complications
47:, or laboratory data) and the risk for cardiac complications in a 29: 56:
perioperative cardiac complications. This became known as the
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4. History of diabetes requiring preoperative insulin use
307:Journal of the American College of Cardiology 268:Journal of the American College of Cardiology 8: 367: 348:Journal of the American Heart Association 318: 241: 166:ASA physical status classification system 66: 177: 84:2. History of congestive heart failure 79:1. History of ischemic heart disease 7: 156:of the risk factors that RCRI uses. 14: 22:Revised Cardiac Risk Index (RCRI) 188:New England Journal of Medicine 125:American College of Cardiology 1: 24:is a tool used to estimate a 200:10.1056/NEJM197710202971601 99:5. Chronic kidney disease 58:Original Cardiac Risk Index 424: 320:10.1016/j.jacc.2014.07.944 280:10.1016/j.jacc.2007.09.001 243:10.1161/01.CIR.100.10.1043 121:American Heart Association 72:Revised Cardiac Risk Index 360:10.1161/JAHA.121.023745 60:(or alternatively the 53:logistic regression 274:(17): 1707–1732. 236:(10): 1043–1049. 116: 115: 415: 382: 381: 371: 339: 333: 332: 322: 313:(22): e77–e137. 298: 292: 291: 262: 256: 255: 245: 227: 218: 212: 211: 182: 67: 423: 422: 418: 417: 416: 414: 413: 412: 388: 387: 386: 385: 354:(15): e023745. 341: 340: 336: 300: 299: 295: 264: 263: 259: 225: 220: 219: 215: 194:(16): 845–850. 184: 183: 179: 174: 162: 149: 74: 19: 17: 12: 11: 5: 421: 419: 411: 410: 408:Patient safety 405: 400: 390: 389: 384: 383: 334: 293: 257: 213: 176: 175: 173: 170: 169: 168: 161: 158: 148: 145: 114: 113: 106: 105: 101: 100: 96: 95: 91: 90: 86: 85: 81: 80: 76: 75: 70: 15: 13: 10: 9: 6: 4: 3: 2: 420: 409: 406: 404: 401: 399: 396: 395: 393: 379: 375: 370: 365: 361: 357: 353: 349: 345: 338: 335: 330: 326: 321: 316: 312: 308: 304: 297: 294: 289: 285: 281: 277: 273: 269: 261: 258: 253: 249: 244: 239: 235: 231: 224: 217: 214: 209: 205: 201: 197: 193: 189: 181: 178: 171: 167: 164: 163: 159: 157: 154: 146: 144: 140: 138: 134: 130: 126: 122: 112: 108: 107: 103: 102: 98: 97: 93: 92: 88: 87: 83: 82: 78: 77: 73: 69: 68: 65: 63: 62:Goldman Index 59: 54: 50: 46: 42: 38: 35: 34:perioperative 31: 27: 23: 351: 347: 337: 310: 306: 296: 271: 267: 260: 233: 229: 216: 191: 187: 180: 153:arthroplasty 150: 147:Alternatives 141: 117: 110: 71: 61: 57: 21: 18: 230:Circulation 43:, comorbid 398:Anesthesia 392:Categories 172:References 129:algorithm 45:diagnoses 378:35904198 329:25091544 288:17950159 252:10477528 160:See also 133:diabetes 403:Surgery 369:9375497 137:insulin 41:surgery 37:cardiac 26:patient 376:  366:  327:  286:  250:  208:904659 206:  49:cohort 226:(PDF) 135:with 374:PMID 325:PMID 284:PMID 248:PMID 204:PMID 123:and 30:risk 20:The 364:PMC 356:doi 315:doi 276:doi 238:doi 234:100 196:doi 192:297 32:of 28:'s 394:: 372:. 362:. 352:11 350:. 346:. 323:. 311:64 309:. 305:. 282:. 272:50 270:. 246:. 232:. 228:. 202:. 190:. 380:. 358:: 331:. 317:: 290:. 278:: 254:. 240:: 210:. 198::

Index

patient
risk
perioperative
cardiac
surgery
diagnoses
cohort
logistic regression
American Heart Association
American College of Cardiology
algorithm
diabetes
insulin
arthroplasty
ASA physical status classification system
doi
10.1056/NEJM197710202971601
PMID
904659
"Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery"
doi
10.1161/01.CIR.100.10.1043
PMID
10477528
doi
10.1016/j.jacc.2007.09.001
PMID
17950159
"2014 ACC/AHA Guideline on Perioperative Cardiovascular Evaluation and Management of Patients Undergoing Noncardiac Surgery"
doi

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