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1.
Perioper Med (Lond) ; 10(1): 59, 2021 Dec 15.
Article in English | MEDLINE | ID: mdl-34906248

ABSTRACT

BACKGROUND: Continuous peripheral nerve catheters (PNCs) have been shown to provide superior postoperative analgesia, decrease opioid consumption, and improve patient satisfaction compared with single injection techniques. In order to achieve success and reliability, accurate catheter positioning is an essential element of PNC placement. An agitated solution of normal saline, D5W, or a local anesthetic solution can be produced by the introduction of air to the injectate, creating air bubbles that can enhance ultrasonographic visualization and possibly improve block success. METHODS: Eighty-three patients were enrolled. Ultrasound-guided continuous popliteal sciatic nerve blocks were performed by positioning the tip of a Tuohy needle between the tibial and common peroneal branches of the sciatic nerve and threading a catheter. An agitated local anesthetic solution was injected through the catheter, viewed with color Doppler ultrasound and video recorded. A peripheral block score (lower score = greater blockade, range 0-14) was calculated based upon the motor and sensory testing at 10, 20, and 30 min after block completion. The color Doppler agitation coverage pattern for the branches of the sciatic nerve was graded as follows: complete (> 50%), partial (> 0%, ≤ 50%), or none (0%). RESULTS: The degree of nerve blockade at 30 min as judged by median (10th, 90th percentile) peripheral block score was significant for partial or complete color Doppler coverage of the sciatic nerve injectate compared to no coverage [3 (0, 7) vs 8 (4, 14); p < 0.01] and block onset was faster (p = 0.03). The block success was higher in groups with partial or complete coverage of the branches of the sciatic nerve vs no coverage (96% vs 70%; p = 0.02). CONCLUSIONS: Injection of an agitated solution through a popliteal sciatic perineural catheter is predictive of accurate catheter placement when partial or complete coverage of the sciatic nerve branches is visualized with color Doppler ultrasound. TRIAL REGISTRATION: NCT01591603.

2.
J Am Med Inform Assoc ; 20(3): 420-6, 2013 May 01.
Article in English | MEDLINE | ID: mdl-23161894

ABSTRACT

OBJECTIVE: Medication  safety requires that each drug be monitored throughout its market life as early detection of adverse drug reactions (ADRs) can lead to alerts that prevent patient harm. Recently, electronic medical records (EMRs) have emerged as a valuable resource for pharmacovigilance. This study examines the use of retrospective medication orders and inpatient laboratory results documented in the EMR to identify ADRs. METHODS: Using 12 years of EMR data from Vanderbilt University Medical Center (VUMC), we designed a study to correlate abnormal laboratory results with specific drug administrations by comparing the outcomes of a drug-exposed group and a matched unexposed group. We assessed the relative merits of six pharmacovigilance measures used in spontaneous reporting systems (SRSs): proportional reporting ratio (PRR), reporting OR (ROR), Yule's Q (YULE), the χ(2) test (CHI), Bayesian confidence propagation neural networks (BCPNN), and a gamma Poisson shrinker (GPS). RESULTS: We systematically evaluated the methods on two independently constructed reference standard datasets of drug-event pairs. The dataset of Yoon et al contained 470 drug-event pairs (10 drugs and 47 laboratory abnormalities). Using VUMC's EMR, we created another dataset of 378 drug-event pairs (nine drugs and 42 laboratory abnormalities). Evaluation on our reference standard showed that CHI, ROR, PRR, and YULE all had the same F score (62%). When the reference standard of Yoon et al was used, ROR had the best F score of 68%, with 77% precision and 61% recall. CONCLUSIONS: Results suggest that EMR-derived laboratory measurements and medication orders can help to validate previously reported ADRs, and detect new ADRs.


Subject(s)
Drug-Related Side Effects and Adverse Reactions/diagnosis , Electronic Health Records , Pharmacovigilance , Algorithms , Humans , Product Surveillance, Postmarketing/methods
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