• In vivo · Jan 2001

    Prediction of accelerated Ca-induced Ca release rate by clinical findings in malignant hyperthermia susceptible subjects.

    • M Kawamoto, K Mukaida, Y Maehara, and O Yuge.
    • Department of Anesthesiology and Critical Care, Hiroshima University Faculty of Medicine, Kasumi 1-2-3, Minami-ku, Hiroshima 734-8551. anekawa@hiroshima-u.ac.jp
    • In Vivo. 2001 Jan 1;15(1):45-8.

    BackgroundAn abnormally accelerated Ca-induced Ca release (CICR) rate is known to be correlated with malignant hyperthermia susceptibility (MHS).ObjectiveTo analyze significant clinical findings concerning CICR rate and develop a computer program for its prediction in human MHS.Patients And MethodUsing data from 146 subjects who had received a muscle biopsy for the determination of CICR rate, because of their anesthesia-related MHS history, we analyzed 23 different clinical features. There were 71 subjects with an abnormally accelerated CICR rate and 75 with a normal rate. Accelerated CICR rate was used as the objective variable whilst clinical findings and ages were used as independent variables and control variables, respectively. A multiple logistic regression model was employed for the analyses and the most suitable formulae for prediction were determined for use in the development of a computer program.ResultsThe following 8 clinical findings were determined to be the most significant: the presence of muscle rigidity, the most serious PaCO2 reading (mmHg), peak body temperature (degree C), body temperature rate of increase over 15 minutes (degree C/15 minutes), most serious arterial pH reading, administration of dantrolene, improvement of acidosis with dantrolene, and time elapsed to peak body temperature after administration of anesthetics (minutes). By ranking the subject ages into 14 groups, we were able to minimize the prediction error rate with each corresponding formula. The computer program developed for prediction whilst consisted of these formulae yielded a sensitivity of 80% and a specificity of 86%.ConclusionThis method of prediction may contribute to the accurate prediction of CICR rate at the bedside. For clinical convenience, we will distribute the computer program upon request.

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