Objective: Initial identification of new investigational drugs for the treatment of epilepsy is commonly conducted in well-established mouse acute and chronic seizure models: for example, maximal electroshock (MES), 6 Hz, and corneal kindling. Comparison of the median effective dose (ED50) of approved antiseizure drugs (ASDs) vs investigational agents in these models provides evidence of their potential for clinical efficacy. Inbred and outbred mouse strains exhibit differential seizure susceptibility. However, few comparisons exist of the ED50 or median behaviorally impairing dose (TD50) of prototype ASDs in these models in inbred C57Bl/6 vs outbred CF-1 mice, both of which are often used for ASD discovery. Methods: We defined the strain-related ED50s and TD50s of several mechanistically distinct ASDs across established acute seizure models (MES, 6 Hz, and corneal-kindled mouse). We further quantified the strain-related effect of the MES ED50 of each ASD on gross behavior in a locomotor activity assay. Finally, we describe a novel pharmacoresistant corneal-kindling protocol that is suitable for moderate-throughput ASD screening and demonstrates highly differentiated ASD sensitivity. Results: We report significant strain-related differences in the MES ED50 of valproic acid (CF-1 ED50: 90 mg/kg [95% confidence interval (CI) 165-214] vs C57Bl/6: 276 mg/kg [226-366]), as well as significant differences in the ED50 of levetiracetam in the pharmacoresistant 6 Hz test (CF-1: 22.5 mg/kg [14.7-30.2] vs C57Bl/6: >500 mg/kg [CI not defined]). There were no differences in the calculated TD50 of these ASDs between strains. Furthermore, the MES ED50 of phenobarbital significantly enhanced locomotor activity of outbred CF-1, but not C57Bl/6, mice. Significance: Altogether, this study provides strain-related information to differentiate investigational agents from ASD standards-of-care in commonly employed preclinical discovery models and describes a novel kindled seizure model to further explore the mechanisms of drug-resistant epilepsy. K E Y W O R D S 6 Hz test, amphetamine, corneal-kindled seizure, maximal electroshock test, open field test 2 | METHODS 2.1 | Animals All animal experimentation was approved by the University of Washington Institutional Animal Care and Use Committee. CF-1 male mice (4-8 weeks; Envigo Laboratories, Indianapolis, IN, USA) and C57Bl/6NCrl male mice (4-8 weeks; Charles River Laboratories) were housed, by strain, five mice per cage in a temperature-controlled vivarium on a 14:10 light/dark cycle. Animals had access to irradiated chow (Picolab 5053) and water ad libitum, except during testing. Mice were allowed a minimum of 4 days habituation to the housing facility, given a minimum of 1 hour
Background Monitoring surgical recovery has traditionally been confined to metrics measurable within the hospital and clinic setting. However, commercially available mobile sensors are now capable of extending measurements into a patient’s home. As these sensors were developed for nonmedical applications, their clinical role has yet to be established. The aim of this systematic review is to evaluate the relationship between data generated by mobile sensors and postoperative outcomes. Objective The objective of this study is to describe the current use of mobile sensors in the perioperative setting and the correlation between their data and clinical outcomes. Methods A systematic search of EMBASE, MEDLINE, and Cochrane Library from inception until April 2019 was performed to identify studies of surgical patients monitored with mobile sensors. Sensors were considered if they collected patient metrics such as step count, temperature, or heart rate. Studies were included if patients underwent major surgery (≥1 inpatient postoperative day), patients were monitored using mobile sensors in the perioperative period, and the study reported postoperative outcomes (ie, complications and hospital readmission). For studies including step count, a pooled analysis of the step count per postoperative day was calculated for the complication and noncomplication cohorts using mean and a random-effects linear model. The Grading of Recommendations, Assessment, Development, and Evaluation tool was used to assess study quality. Results From 2209 abstracts, we identified 11 studies for review. Reviewed studies consisted of either prospective observational cohorts (n=10) or randomized controlled trials (n=1). Activity monitors were the most widely used sensors (n=10), with an additional study measuring temperature, respiratory rate, and heart rate (n=1). Low step count was associated with worse postoperative outcomes. A median step count of around 1000 steps per postoperative day was associated with adverse surgical outcomes. Within the studies, there was heterogeneity between the type of surgery and type of reported postoperative outcome. Conclusions Despite significant heterogeneity in the type of surgery and sensors, low step count was associated with worse postoperative outcomes across surgical specialties. Further studies and standardization are needed to assess the role of mobile sensors in postoperative care, but a threshold of approximately 1000 steps per postoperative day warrants further investigation.
Monitoring surgical recovery has traditionally been confined to metrics measurable within the hospital and clinic setting. However, commercially available mobile sensors are now capable of extending measurements into a patient’s home. As these sensors were developed for non-medical applications their clinical role has yet to be established. The aim of this systematic review is to evaluate the relationship between data generated by mobile sensors and postoperative outcomes. The objective of this study is to describe the current utilization of mobile sensors in the perioperative setting, and the correlation between their data and clinical outcomes. A systematic search of EMBASE, Medline and Cochrane Library, from inception until April 2019, was performed to identify studies of surgical patients monitored with mobile sensors. Sensors were considered if they collected patient metrics such as step count, temperature or heart rate. Studies were included if patients underwent major surgery (≥ 1 inpatient postoperative day), were monitored using mobile sensors in the perioperative period and reported postoperative outcomes (i.e. complications and hospital readmission). For studies including step count, a pooled analysis of the step count per postoperative day was calculated for the complication and non-complication cohorts using mean and Random-effects RELM model. The GRADE tool was used to assess study quality. From 2209 abstracts we identified 11 studies for review. Reviewed studies consisted of either prospective observational cohorts (N = 10) or randomized controlled trials (N = 1). Activity monitors were the most widely used sensors (N = 10), with an additional study measuring temperature, respiratory rate and heart rate (N = 1). Low step count was associated with worse postoperative outcomes. A median step count of less than around 1000 steps per postoperative day was associated with adverse surgical outcomes. Within the studies there was heterogeneity between the type of surgery and type of reported postoperative outcome. Despite significant heterogeneity in type of surgery and sensors, low step count was associated with worse postoperative outcomes across surgical specialties. Further studies and standardization are needed to assess the role of mobile sensors in postoperative care, but a threshold of approximately 1000 steps per postoperative day warrants further investigation.
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