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1.
Eur J Emerg Med ; 31(1): 18-28, 2024 Feb 01.
Article in English | MEDLINE | ID: mdl-37650732

ABSTRACT

BACKGROUND AND IMPORTANCE: Ultrasound-guided femoral nerve block (FNB) could be used as part of a multimodal preoperative pain management for patients with hip fracture. Evidence of the effects of its early implementation in the emergency room as an immediate alternative to intravenous morphine titration is sparse. OBJECTIVE: To investigate the effect of an early ultrasound-guided FNB performed by emergency physicians on preoperative opioid consumption, compared to standard pain management. DESIGN, SETTING, AND PARTICIPANTS: This open randomized controlled trial was conducted in the Emergency Department of a French hospital with patients with neck or trochanteric femoral fracture who had a pain score ≥7 out of 10 points at triage. INTERVENTION: Patients were randomized to receive an initial analgesia with an early ultrasound-guided FNB or with standard pain management. The continuation of pain treatment followed standardized pain control guidelines until hospital discharge in both groups. OUTCOME MEASURE AND ANALYSIS: The primary outcome was preoperative opioid consumption truncated 48h after triage time, and converted in morphine milligram intravenous equivalents (MME). Secondary outcomes were time to pain relief, time for regaining walk, opioid consumption and occurrence of opioid and FNB adverse effects during the hospital stay. Exploratory outcomes included ease and duration of the procedure. MAIN RESULTS: We randomized 35 patients: 17 to standard pain management and 18 to ultrasound-guided FNB, among whom 30 patients completed the protocol. The median of preoperative opioid consumption was reduced by 60% in the ultrasound-guided FNB group compared to standard group [6 MME (3-9) vs. 15 MME (11-18)], with a consumption difference of 9 MME (95% CI: 3-14, P  < 0.001). Throughout hospital stay, opioid consumption was reduced by 56% in the ultrasound-guided FNB group compared to standard group, with a consumption difference of 11.5 MME (95% CI: 0.5-22).Times to pain relief and for regaining walk did not differ between groups. Opioid adverse events occurrence were reduced by 40% (95% CI: 5.1-74.9) in the ultrasound-guided FNB group compared to standard group. No adverse effects of FNB have been detected. CONCLUSION: Early ultrasound-guided FNB resulted in reducing preoperative opioid consumption, without delaying time to pain relief.


Subject(s)
Analgesics, Opioid , Nerve Block , Humans , Analgesics, Opioid/therapeutic use , Nerve Block/adverse effects , Nerve Block/methods , Femoral Nerve , Pain, Postoperative/drug therapy , Pain, Postoperative/etiology , Morphine/therapeutic use , Ultrasonography, Interventional
2.
Int J Clin Pharm ; 44(2): 459-465, 2022 Apr.
Article in English | MEDLINE | ID: mdl-34978662

ABSTRACT

Background Medication review is time-consuming and not exhaustive in most French hospitals. We routinely use an innovative hybrid decision support system using Artificial Intelligence to prioritize medication review by scoring prescriptions by their risk of containing at least one drug related problem (DRP). Aim Our aim was to attest that the prescriptions with low risk of DRPs ruled out by the tool in everyday practice were effectively free of any DRPs with potentially severe clinical impact. Methods We conducted a randomized single-blinded study to compare the rate of pharmaceutical interventions (PI) between low and high-risk prescriptions defined by the tool's calculated score. Prescriptions were reviewed daily by a clinical pharmacist. Proportion of prescriptions with at least one severe DRP was calculated in both groups. Severe DRPs were characterized through a multidisciplinary approach. Results Four hundred and twenty (107 low score and 313 high score) prescriptions were analyzed. The percentage of prescriptions with severe DRPs was dramatically decreased in low score prescriptions (2.8% vs. 15.3% for high-risk; p = 0.0248). A significant difference was found (94% vs. 20%; p < 0.001) in the percentage of severe DRPs detected by the hybrid approach compared to a CDSS. During the study period, the hybrid tool allowed to rule out 55% of all prescriptions in our hospital.Conclusion This hybrid decision support tool has shown to be accurate to detect DRPs in daily practice. Despite some limitations, it offers the best possible solution to prioritized medication review, considering the shortage of clinical pharmacists in France and considerably improves the safety of patients' care.


Subject(s)
Artificial Intelligence , Drug-Related Side Effects and Adverse Reactions , Humans , Machine Learning , Medication Review , Pharmacists , Prescriptions
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