Perioperative Breast Analgesia: a Systematic Review of the Evidence for Perioperative Analgesic Medications.

PURPOSE OF REVIEW: Breast surgery is common and may result in significant acute as well as chronic pain. A wide range of pharmacologic interventions is available including opioids, non-steroidal anti-inflammatory drugs (NSAIDs), N-methyl-D-aspartate (NMDA) receptor antagonists, anticonvulsants, and other non-opioids with analgesic properties. We present a review of the evidence for these pharmacologic interventions. A literature search of the MEDLINE database was performed via PubMed with combined terms related to breast surgery, anesthesia, and analgesia. Articles were limited to randomized controlled trial (RCT) design, adult patients undergoing elective surgery on the breast (not including biopsy), and pharmacologic interventions only. Article titles and abstracts were screened, and risk of bias assessments were performed. RECENT FINDINGS: The search strategy initially captured 7254 articles of which 60 articles met the full inclusion criteria. Articles were organized according to intervention: 6 opioid agonists, 14 NSAIDs and acetaminophen, 4 alpha-2 agonists, 7 NMDA receptor antagonists, 6 local anesthetics, 7 steroids, 15 anticonvulsants (one of which also discussed an NMDA antagonist), 1 antiarrhythmic, and 2 serotonin reuptake inhibitors (one of which also studied an anticonvulsant). A wide variety of medications is effective for perioperative breast analgesia, but results vary by agent and dose. The most efficacious are likely NSAIDs and anticonvulsants. Some agents may also decrease the incidence of chronic postoperative pain, including flurbiprofen, gabapentin, venlafaxine, and memantine. While many individual agents are well studied, optimal combinations of analgesic medications remain unclear.

Distinguishing grade I meningioma from higher grade meningiomas without biopsy.

BACKGROUND: Many meningiomas are identified by imaging and followed, with an assumption that they are WHO Grade I tumors. The purpose of our investigation is to find clinical or imaging predictors of WHO Grade II/III tumors to distinguish them from Grade I meningiomas. METHODS: Patients with a pathologic diagnosis of meningioma from 2002-2009 were included if they had pre-operative MRI studies and pathology for review. A Neuro-Pathologist reviewed and classified all tumors by WHO 2007. All Brain MRI imaging was reviewed by a Neuro-radiologist. Pathology and Radiology reviews were blinded from each other and clinical course. Recursive partitioning was used to create predictive models for identifying meningioma grades. RESULTS: Factors significantly correlating with a diagnosis of WHO Grade II-III tumors in univariate analysis: prior CVA (p = 0.005), CABG (p = 0.010), paresis (p = 0.008), vascularity index = 4/4: (p = 0.009), convexity vs other (p = 0.014), metabolic syndrome (p = 0.025), non-skull base (p = 0.041) and non-postmenopausal female (p = 0.045). Recursive partitioning analysis identified four categories: 1. prior CVA, 2. vascular index (vi) = 4 (no CVA), 3. premenopausal or male, vi < 4, no CVA. 4. Postmenopausal, vi < 4, no CVA with corresponding rates of 73, 54, 35 and 10% of being Grade II-III meningiomas. CONCLUSIONS: Meningioma patients with prior CVA and those grade 4/4 vascularity are the most likely to have WHO Grade II-III tumors while post-menopausal women without these features are the most likely to have Grade I meningiomas. Further study of the associations of clinical and imaging factors with grade and clinical behavior are needed to better predict behavior of these tumors without biopsy.