Pre-operative screening: Criteria for referring to anaesthetists

Nurses assess patients pre-operatively using screening questionnaires and locally-developed protocols. Our objectives were to determine which questions might identify patients who should be seen by an anaesthetist before the day of surgery. A review of the literature and a preliminary questionnaire to establish questions to be tested was followed by a modified, two-round Delphi questionnaire to determine the level of agreement by anaesthetists. There was agreement for referring patients who gave a positive response to questions that query: restricted exercise tolerance; previous anaesthetic problems; family history of anaesthetic problem; pathology affecting neck movement; angina; arrhythmia; heart failure; asthma; epilepsy; insulin-dependent diabetes mellitus; liver disease and unspecified kidney disease. There was equivocal agreement on questions that report a myocardial infarction over one year ago, cerebrovascular accident, non insulin-dependent diabetes mellitus and thyroid disease. Nurses should use these criteria during pre-operative assessment to decide the timing of evaluation by an anaesthetist

Validation of a pre-anaesthetic screening questionnaire

We developed a screening questionnaire to be used by nurses to decide which patients should see an anaesthetist for further evaluation before the day of surgery. Our objective was to measure the accuracy of responses to the questionnaire. Agreement between questionnaire responses and the anaesthetist's assessment was assessed. For questions with a prevalence of 5 to 95%, the Kappa coefficient was used; percentage agreement was used for all other questions. Criterion validity was excellent/good for all questions with a prevalence between 5 and 95%, except for the question 'Do you have kidney disease?' For questions with prevalence < 5%, all demonstrated adequate criterion validity except the questions 'Has anyone in your family had a problem following an anaesthetic?' and 'If you have been put to sleep for an operation were there any anaesthetic problems?' Therefore, it is reasonable for nurses to use this questionnaire to determine which patients an anaesthetist should see before the day of surgery

Interobserver reliability between a nurse and anaesthetist of tests used for predicting difficult tracheal intubation

We examined the interobserver reliability, between a nurse and anaesthetist, of five tests used to predict difficult tracheal intubation: mouth opening; thyromental distance; head and neck movement; mandibular luxation; and assessment of oropharyngeal view. For each test, an anaesthetic nurse and a specialist registrar anaesthetist were trained to use a standard method of examination. Most of the tests had either good or very good reliability. Assessment of mouth opening demonstrated only moderate reliability and assessment of oropharyngeal view demonstrated poor reliability. The interobserver reliability estimates between a nurse and an anaesthetist are similar to those previously demonstrated between two anaesthetists

The relationship between patient data and pooled clinical management decisions

A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. Ina previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P <0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics with the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient data may have utility supporting clinicians' preoperative decisions.G. L. Ludbrook, E. J. O'loughlin, C. Grant, T B. Corcora