Role of Core Number and Location in Targeted Magnetic Resonance Imaging-Ultrasound Fusion Prostate Biopsy.

The optimal method of magnetic resonance imaging (MRI)-ultrasound (US) fusion biopsy to adequately sample regions of interest (ROIs) remains unknown. We sought to determine the number and location of cores needed to adequately detect clinically significant prostate cancer (PCa). We identified patients undergoing MRI-US fusion prostate biopsy at our institution for known history or clinical suspicion of PCa. Multiparametric MRI studies were reviewed using Likert and Prostate Imaging Reporting and Data System (PI-RADS) v2 schema. Multiple targeted cores were taken from each ROI followed by 12-core systematic biopsy. In a distinct cohort of patients, lesions were targeted using a predetermined five-core template. We estimated cancers detected through sampling of five or fewer cores, assessed by core number and core location. We identified 744 patients with 581 lesions with PCa. Seventy-seven percent (279/361) of Gleason (G) ≥3+4 tumors and 72% (137/189) of G >3+4 tumors were detected on two-core sampling. Relative to all targeted cores, a two-core approach missed 16% of clinically significant cancers at first biopsy, 27% in prior negative, and 32% in active surveillance patients. Detection of G ≥3+4 cancers did not differ by core location. Sampling of two cores of ROIs misses nearly one-quarter of clinically significant PCa detected on additional sampling. PATIENT SUMMARY: We aimed to understand how the number of cores obtained from a suspicious area during prostate magnetic resonance imaging-ultrasound fusion biopsy affects cancer detection. We found that sampling of five cores missed substantially fewer cancers compared to two cores.

Opioid dependency is independently associated with inferior clinical outcomes after trauma.

INTRODUCTION: Increased use of opioids has led to higher rates of overdose and hospital admissions. Studies in trauma populations have focused on outcomes associated with acute intoxications rather than addiction. We hypothesize that clinical outcomes after injury would be inferior for opioid-dependent patients compared to opioid-naïve patients. METHODS: We identified all opioid-dependent adult patients admitted to an academic level I trauma center in 2016 with an Injury Severity Score (ISS) ≥ 5. Patients were further categorized by their pattern of opioid dependency into prescription abuse, illicit abuse, or chronic pain subgroups. Outcome measures included length of stay (LOS), major complications, mortality, non-home discharge, ventilator days, and readmissions. Regression models were adjusted for patient demographics, insurance, ISS, and comorbidities. RESULTS: Of the 1450 patients who met the inclusion criteria, 18% were opioid-dependent. Among opioid-dependent patients, 30%, 27%, and 43% were prescription abuse, illicit abuse, and chronic pain patients, respectively. Compared to opioid-naïve (non-users) patients, opioid-dependent patients had longer LOS, more ventilator days, more non-home discharges, and higher readmission rates. Subgroup analysis revealed significant differences among all cohorts when compared to non-users in LOS, non-home discharge, readmissions, and major complications. Opioid dependency was not associated with mortality. CONCLUSION: Opioid dependency was detected in 18% of trauma patients and was independently associated with inferior outcomes. The impact of opioid dependency affects each opioid subgroup differently with all cohorts demonstrating increased 30-day readmissions. Opioid dependent patients may be targeted for risk interventions to reduce LOS, non-home discharge, complications and readmissions.