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Flaminia Coluzzi,1 Francesca Bifulco,2 Arturo Cuomo,2 Mario Dauri,3 Claudio Leonardi,4 Rita Maria Melotti,5 Silvia Natoli,3 Patrizia Romualdi,6 Gennaro Savoia,7 Antonio Corcione8 1Department of Medical and Surgical Sciences and Biotechnologies, Unit of Anaesthesia, Intensive Care and Pain Medicine, Sapienza University of Rome, Polo Pontino, Latina, 2National Cancer Institute “G Pascale” Foundation, Unit of Anaesthesia, Intensive Care and Pain Medicine, Naples, 3Department of Clinical Science and Translational Medicine, Tor Vergata University of Rome, 4Addiction Disease Department, Local Health Unit (ASL) Rome 2, Rome, 5Department of Medical and Surgical Sciences, 6Department of Pharmacy and Biotechnology, Alma Mater Studiorum University of Bologna, Bologna, 7Department Anesthesia, Fatebenefratelli Hospital, Naples, 8Unit of Anaesthesia and Intensive Care, Dei Colli Hospital, V. Monaldi, Naples, Italy Abstract: The increasing number of opioid users among chronic pain patients, and opioid abusers among the general population, makes perioperative pain management challenging for health care professionals. Anesthesiologists, surgeons, and nurses should be familiar with some pharmacological phenomena which are typical of opioid users and abusers, such as tolerance, physical dependence, hyperalgesia, and addiction. Inadequate pain management is very common in these patients, due to common prejudices and fears. The target of preoperative evaluation is to identify comorbidities and risk factors and recognize signs and symptoms of opioid abuse and opioid withdrawal. Clinicians are encouraged to plan perioperative pain medications and to refer these patients to psychiatrists and addiction specialists for their evaluation. The aim of this review was to give practical suggestions for perioperative management of surgical opioid-tolerant patients, together with schemes of opioid conversion for chronic pain patients assuming oral or transdermal opioids, and patients under maintenance programs with methadone, buprenorphine, or naltrexone. Keywords: opioids, postoperative pain, addiction, abusers, buprenorphine, methadone

Boaz Gedaliahu Samolsky Dekel,1–3 Marco Palma,4 Maria Cristina Sorella,1–3 Alberto Gori,3 Alessio Vasarri,3 Rita Maria Melotti1–3 1Department of Medicine and Surgery Sciences, University of Bologna, 2Department of Emergency-Urgency, Bologna’s University Teaching Hospital, Policlinic S. Orsola-Malpighi, 3University of Bologna, Post Graduate School of Anaesthesia and Intensive Care, 4Collegio Superiore, Istituto di Studi Superiori – ISS, University of Bologna, Bologna, Italy Objectives: Variable prevalence and treatment of breakthrough pain (BTP) in different clinical contexts are partially due to the lack of reliable/validated diagnostic tools with prognostic capability. We report the statistical basis and performance analysis of a novel BTP scoring system based on the naïve Bayes classifier (NBC) approach and an 11-item IQ-BTP validated questionnaire. This system aims at classifying potential BTP presence in three likelihood classes: “High,” “Intermediate,” and “Low.”Methods: Out of a training set of n=120 mixed chronic pain patients, predictors associated with the BTP likelihood variables (Pearson’s χ2 and/or Fisher’s exact test) were employed for the NBC planning. Adjusting the binary classification to a three–likelihood classes case enabled the building of a scoring algorithm and to retrieve the score of each predictor’s answer options and the Patient’s Global Score (PGS). The latter medians were used to establish the NBC thresholds, needed to evaluate the scoring system performance (leave-one-out cross-validation).Results: Medians of PGS in the “High,” “Intermediate,” and “Low” likelihood classes were 3.44, 1.53, and −2.84, respectively. Leading predictors for the model (based on score differences) were flair frequency (∆S=1.31), duration (∆S=5.25), and predictability (∆S=1.17). Percentages of correct classification were 63.6% for the “High” and of 100.0% for either the “Intermediate” and “Low” likelihood classes; overall accuracy of the scoring system was 90.9%.Conclusion: The NBC-based BTP scoring system showed satisfactory performance in classifying potential BTP in three likelihood classes. The reliability, flexibility, and simplicity of this statistical approach may have significant relevance for BTP epidemiology and management. These results need further impact studies to generalize our findings. Keywords: naïve Bayes classifier, breakthrough pain, multiclass scoring-system