Method: Nine case-based scenarios have been developed involving preoperative patients with isolated orthopaedic traumas. Cases were established and marked with a baseline score by a treating anaesthetist and orthopaedic traumatic surgeons. The anaesthetists present and residents were asked to assign an ASA score for each case. Missing from the reference and inter-rater chord was then analyzed via Kappa fleiss and Cohen Kappa weighted and unweighted. Another approach to concordance (useful when there are only two advisors and the scale is continuous) is to calculate the differences between the observations of the two advisors. The average of these differences is called Bias and the reference interval (average ± 1.96 × standard deviation) is called the compliance limit. The limitations of the agreement provide an overview of how random variations can influence evaluations. There are several operational definitions of “inter-rated reliability” that reflect different views on what a reliable agreement between advisors is.  There are three operational definitions of agreements: therefore, the common probability of an agreement will remain high, even in the absence of an “intrinsic” agreement between the advisers. A useful interrater reliability coefficient (a) is expected to be close to 0 if there is no “intrinsic” agreement and (b) increased if the “intrinsic” agreement rate improves. Most probability-adjusted match coefficients achieve the first objective.
However, the second objective is not achieved by many well-known measures that correct the odds.  If the number of categories used is small (z.B 2 or 3), the probability of 2 raters agreeing by mere coincidence increases considerably. This is because the two advisors must limit themselves to the limited number of options available, which affects the overall agreement rate, not necessarily their propensity to enter into an “intrinsic” agreement (an agreement is considered “intrinsic” if not due to chance). Key measures of results: the correspondence between rates is expressed with intra-ccal correlation coefficients (CCIs) and corresponding confidence intervals of 95% (CN). The difference between advisors is reported with 95% of CN. The baseline demography, University of Los Angeles of California (UCLA), and Harris hip questionnaires were completed by all participants. Subsequent extensions of the approach included versions that could deal with “under-credits” and ordinal scales.  These extensions converge with the intra-class correlation family (ICC), which allows us to estimate reliability for each level of measurement, from the notion (kappa) to the ordinal (or ICC) at the interval (ICC or ordinal kappa) and the ratio (ICC). There are also variations that may consider the agreement by the evaluators on a number of points (for example.B.
two people agree on the rates of depression for all points of the same semi-structured interview for a case?) as well as cases of raters x (for example. B how do two or more evaluators agree on whether 30 cases have a diagnosis of depression, yes/no a nominal variable).