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Gupta MICA (Perioperative MI or Cardiac Arrest) Risk Calculator

  • Age
  • Functional Status
  • ASA Class
  • Serum Creatinine (most recent, mg/dL)
  • Procedure Category
  • Gupta Myocardial Infarction or Cardiac Arrest (MICA) Risk Model: Explanation and Clinical Context
    The Gupta MICA model estimates the probability of perioperative myocardial infarction or cardiac arrest within 30 days after non-cardiac surgery. It uses five preoperative predictors readily available at assessment: age (continuous), functional status (independent/partially dependent/totally dependent), American Society of Anesthesiologists (ASA) class (I–V), elevated serum creatinine >1.5 mg/dL (binary), and the planned procedure category (21 groups). The model is logistic, with the intercept and coefficients derived from the American College of Surgeons NSQIP dataset; the output is an absolute risk (%) that can be used to inform consent, postoperative monitoring plans, and shared decision-making.

    Clinical Significance & Interpretation
    As a probability model, MICA complements the stepwise perioperative evaluation recommended by professional societies. Many clinicians treat estimates <1% as “low risk” and ≥1% as “elevated,” aligning with guideline thresholds for major adverse cardiovascular events. Risk is sensitive to procedural category and global illness burden (ASA), and rises with functional dependence and renal dysfunction. Because calibration can drift across settings and eras, consider local validation and the use of perioperative biomarkers (e.g., natriuretic peptides, troponin) when available. Use MICA as one input, alongside urgency, hemodynamics, and multidisciplinary judgment, rather than a sole decision rule.

    Reference:
    Gupta PK, et al. Development and Validation of a Risk Calculator for Prediction of Cardiac Risk After Surgery. Circulation. 2011;124:381–387. doi:10.1161/CIRCULATIONAHA.110.015701.
    A summary of variables and clinical usage appears in later reviews and specialty validations; the procedure-category and coefficient set used here follows transparent community implementations reproducing the original logistic equation (e.g., OmniCalculator) and matches the five-variable specification reported in external discussions. Percentile context for MICA risk distribution is available from Evidencio.

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