{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T15:16:20Z","timestamp":1790954180153,"version":"4.1.0"},"reference-count":34,"publisher":"Journal of Neurosurgery Publishing Group (JNSPG)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JNS"],"published-print":{"date-parts":[[2015,1]]},"abstract":"<jats:sec>\n                    <jats:title>OBJECT<\/jats:title>\n                    <jats:p>Neurosurgeons are frequently the primary physicians measuring pain relief in patients with trigeminal neuralgia (TN). Unfortunately, the measurement of pain can be complex. The Brief Pain Inventory\u2013Facial (BPI-Facial) is a reliable and validated multidimensional tool that consists of 18 questions. It measures 3 domains of pain: 1) pain intensity (worst and average pain intensity), 2) interference with general activities of daily living (ADL), and 3) face-specific pain interference. The objective of this paper is to determine the patient-reported minimum clinically important difference (MCID) using the BPI-Facial.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>The authors conducted a retrospective study of 234 patients with TN seen in a single neurosurgeon's office. Patients completed baseline and 1-month follow-up BPI-Facial questionnaires. The MCID was calculated using an anchor-based approach in which the defined anchor was the 7-point patient global impression of change (PGIC). Two statistical methods were employed: mean change score and optimal cutoff point.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Using the mean change score method, the investigators calculated the MCID for the 3 domains of the BPIFacial: 44% and 30% improvement in pain intensity at its worst and average, respectively, 54% improvement in interference with general ADL, and 63% improvement in interference with facial ADL. Using the optimal cutoff point method, they also calculated the MCID for the 3 domains of the BPI-Facial: 57% and 28% improvement in pain intensity at its worst and average, respectively, 75% improvement in interference with general ADL, and 62% improvement in interference with facial ADL.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>The BPI-Facial is a multidimensional pain scale that measures 3 domains of pain. Although 2 statistical methods were used to calculate the MCID, the optimal cutoff point method was the superior one because it used data from the majority of subjects included in this study. A 57% improvement in pain intensity at its worst and a 28% improvement in pain intensity at its average were the MCIDs for patients with facial pain. A greater improvement was needed to achieve the MCID for interference with general and facial ADL. A 75% improvement in interference with general ADL and a 62% improvement in interference with facial ADL were needed to achieve an MCID. While pain intensity is easier to measure, pain's interference with ADL may be more important for patient outcomes when designing or evaluating interventions in the field of TN. The BPI-Facial is a useful instrument to measure changes in multidimensional aspects of pain in patients with TN.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3171\/2014.8.jns132547","type":"journal-article","created":{"date-parts":[[2014,10,31]],"date-time":"2014-10-31T10:03:24Z","timestamp":1414749804000},"page":"180-190","source":"Crossref","is-referenced-by-count":38,"title":["Brief Pain Inventory\u2013Facial minimum clinically important difference"],"prefix":"10.3171","volume":"122","author":[{"given":"Sukhmeet K.","family":"Sandhu","sequence":"first","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Casey H.","family":"Halpern","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Venus","family":"Vakhshori","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keyvan","family":"Mirsaeedi-Farahani","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John T.","family":"Farrar","sequence":"additional","affiliation":[{"name":"Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John Y. 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