Activation and On-Scene Intervals for Severe Trauma EMS Interventions: An Analysis of the NEMSIS Database.

Objective: Time to care is a determinant of trauma patient outcomes, and timely delivery of trauma care to severely injured patients is critical in reducing mortality. Numerous studies have analyzed access to care using prehospital intervals from a Carr et al. meta-analysis of studies from 1975 to 2005. Carr et al.'s research sought to determine national mean activation and on-scene intervals for trauma patients using contemporary emergency medical services (EMS) records. Since the Carr et al. meta-analysis was published, the National Highway Traffic Safety Administration (NHTSA) created and refined the National Emergency Medical Services Information System (NEMSIS) database. We sought to perform a modern analysis of prehospital intervals to establish current standards and temporal patterns.Methods: We utilized NEMSIS to analyze EMS data of trauma patients from 2016 to 2019. The dataset comprises more than 94 million EMS records, which we filtered to select for severe trauma and stratified by type of transport and rurality to calculate mean activation and on-scene intervals. Furthermore, we explored the impact of basic life support (BLS) and advanced life support (ALS) of ground units on activation and on-scene time intervals.Results: Mean activation and on-scene intervals for ground transport were statistically different when stratified by rurality. Urban, suburban, and rural ground activation intervals were 2.60 ± 3.94, 2.88 ± 3.89, and 3.33 ± 4.58 minutes, respectively. On-scene intervals were 15.50 ± 10.46, 17.56 ± 11.27, and 18.07 ± 16.13 minutes, respectively. Mean helicopter transport activation time was 13.75 ± 7.44 minutes and on-scene time was 19.42 ± 16.09 minutes. This analysis provides an empirically defined mean for activation and on-scene times for trauma patients based on transport type and rurality. Results from this analysis proved to be significantly longer than the previous analysis, except for helicopter transport on-scene time. Shorter mean intervals were seen in ALS compared to BLS for activation intervals, however ALS on-scene intervals were marginally longer than BLS.Conclusions: With the increasing sophistication of geospatial technologies employed to analyze access to care, these intervals are the most accurate and up-to-date and should be included in access to care models.

Correction to: Economic burden of multiple sclerosis in a population with low physical disability.

It has been highlighted that the original article [1] contained a mistake in the 'Results' section, specifically in the percentages of female subjects and those with diagnosis of RRMS. Please note that this mistake has only been present in the 'Results' section, the Abstract and Table 1 remain unchanged. This article shows the incorrect and correct version of the percentages.

Economic burden of multiple sclerosis in a population with low physical disability.

BACKGROUND: In multiple sclerosis (MS), half of affected people are unemployed within 10 years of diagnosis. The aim of this study was to assess the economic impact of MS in adult subjects with relapsing-remitting MS (RRMS) and primary progressive MS (PPMS). METHODS: A multicenter, non-interventional, cross-sectional study was conducted. The Expanded Disability Status Scale (EDSS) and the 23-item Multiple Sclerosis Work Difficulties Questionnaire (MSWDQ-23) were used to assess disability and work performance, respectively. Only indirect costs were considered using the human capital method, including work costs. Professional support costs and informal caregivers' costs were also estimated. RESULTS: A total of 199 subjects were studied (mean age: 43.9 ± 10.5 years, 60.8% female, 86.4% with RRMS). Median EDSS score was 2.0 (interquartile range: 1.0-3.5) and median MSWDQ-23 total score was 31.5 (15.2, 50.0). The number of employed subjects decreased after MS diagnosis from 70.6 to 47.2%, and the number of retired people increased (23.6%). Mean age of retirement was 43.6 ± 10.5 years. Ten percent of the population had sick leaves (absenteeism was seen in 90.9% of the student population and 30.9% of the employed population). Professional support in their daily life activities was needed in 28.1% of subjects. Costs for sick leave, work absenteeism, premature retirement and premature work disability/pensioner were €416.6 ± 2030.2, €763.4 ± 3161.8, €5810.1 ± 13,159.0 and €1816.8 ± 9630.7, respectively. Costs for professional support and informal caregiving activities were €1026.93 ± 4622.0 and €1328.72, respectively. CONCLUSIONS: MS is responsible for a substantial economic burden due to indirect and informal care costs, even in a population with low physical disability.

A CMOS Low Pass Filter for SoC Lock-in-Based Measurement Devices.

This paper presents a fully integrated Gm-C low pass filter (LPF) based on a current steering Gm reduction-tuning technique, specifically designed to operate as the output stage of a SoC lock-in amplifier. To validate this proposal, a first-order and a second-order single-ended topology were integrated into a 1.8 V to 0.18 µm CMOS (Complementary Metal-Oxide-Semiconductor) process, showing experimentally a tuneable cutoff frequency that spanned five orders of magnitude, from tens of mHz to kHz, with a constant current consumption (below 3 µA/pole), compact size (<0.0140 mm2/pole), and a dynamic range better than 70 dB. Compared to state-of-the-art solutions, the proposed approach exhibited very competitive performances while simultaneously fully satisfying the demanding requirements of on-chip portable measurement systems in terms of highly efficient area and power. This is of special relevance, taking into account the current trend towards multichannel instruments to process sensor arrays, as the total area and power consumption will be proportional to the number of channels.

A 0.18 µm CMOS LDO Regulator for an On-Chip Sensor Array Impedance Measurement System.

This paper presents a fully integrated 0.18 μm CMOS Low-Dropout (LDO) Voltage Regulator specifically designed to meet the stringent requirements of a battery-operated impedance spectrometry multichannel CMOS micro-instrument. The proposed LDO provides a regulated 1.8 V voltage from a 3.6 V to 1.94 V battery voltage over a −40 °C to 100 °C temperature range, with a compact topology (<0.10 mm² area) and a constant quiescent current of only 7.45 μA with 99.985% current efficiency, achieving remarkable state-of-art Figures of Merit (FoMs) for the regulating⁻transient performance. Experimental measurements validate its suitability for the target application, paving the way towards the future achievement of a truly portable System on Chip (SoC) platform for impedance sensors.

A CMOS Self-Contained Quadrature Signal Generator for SoC Impedance Spectroscopy.

This paper presents a low-power fully integrated quadrature signal generator for system-on-chip (SoC) impedance spectroscopy applications. It has been designed in a 0.18 μm-1.8 V CMOS technology as a self-contained oscillator, without the need for an external reference clock. The frequency can be digitally tuned from 10 to 345 kHz with 12-bit accuracy and a relative mean error below 1.7%, thus supporting a wide range of impedance sensing applications. The proposal is experimentally validated in two impedance spectrometry examples, achieving good magnitude and phase recovery results compared to the results obtained using a commercial LCR-meter. Besides the wide frequency tuning range, the proposed programmable oscillator features a total power consumption lower than 0.77 mW and an active area of 0.129 mm², thus constituting a highly suitable choice as stimulation module for instrument-on-a-chip devices.

A Compact Energy Harvesting System for Outdoor Wireless Sensor Nodes Based on a Low-Cost In Situ Photovoltaic Panel Characterization-Modelling Unit.

This paper presents a low-cost high-efficiency solar energy harvesting system to power outdoor wireless sensor nodes. It is based on a Voltage Open Circuit (VOC) algorithm that estimates the open-circuit voltage by means of a multilayer perceptron neural network model trained using local experimental characterization data, which are acquired through a novel low cost characterization system incorporated into the deployed node. Both units-characterization and modelling-are controlled by the same low-cost microcontroller, providing a complete solution which can be understood as a virtual pilot cell, with identical characteristics to those of the specific small solar cell installed on the sensor node, that besides allows an easy adaptation to changes in the actual environmental conditions, panel aging, etc. Experimental comparison to a classical pilot panel based VOC algorithm show better efficiency under the same tested conditions.

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications.

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.

Hepatotoxicity induced by acute and chronic paracetamol overdose in adults. Where do we stand?

Paracetamol (Acetaminophen) poisoning data can reveal the potential deficiencies of paracetamol poisoning management guidelines. We conducted a retrospective cohort study of patients >18years who were attended in the emergency department (ED) of a Spanish tertiary hospital, from 2005 to 2010 for suspected paracetamol overdose and who had measurable paracetamol concentrations. 208 patients suspected of paracetamol poisoning were identified. The annual incidence in the ED increased from 2.0 (95%-CI: 0.2-7.2) cases per 10,000 patients in 2005 to 3.4 (95%-CI: 1.1-8.8) in 2010. Only 7 of 98 patients (7.14%) with acute poisoning at toxic doses showed hepatotoxicity signs, 4 (57.1%) of whom presented acute liver failure (ALF) criteria, while 8 of 10 patients (80%) with chronic paracetamol poisoning at toxic doses presented hepatotoxicity and 3 (37.5%) with ALF criteria. The time required to find medical care was 9.0h for acute poisoning and 49.6h for chronic poisoning (p<0.001). We conclude that the incidence of suspected cases of paracetamol poisoning at our hospital is increasing. The majority of toxicity cases, including ALF, associated with the ingestion of paracetamol were due to chronic poisoning. This finding constitutes an important warning regarding paracetamol chronic poisoning, and clinicians should have a higher index of clinical suspicion for this entity.

A High Performance LIA-Based Interface for Battery Powered Sensing Devices.

This paper proposes a battery-compatible electronic interface based on a general purpose lock-in amplifier (LIA) capable of recovering input signals up to the MHz range. The core is a novel ASIC fabricated in 1.8 V 0.18 µm CMOS technology, which contains a dual-phase analog lock-in amplifier consisting of carefully designed building blocks to allow configurability over a wide frequency range while maintaining low power consumption. It operates using square input signals. Hence, for battery-operated microcontrolled systems, where square reference and exciting signals can be generated by the embedded microcontroller, the system benefits from intrinsic advantages such as simplicity, versatility and reduction in power and size. Experimental results confirm the signal recovery capability with signal-to-noise power ratios down to -39 dB with relative errors below 0.07% up to 1 MHz. Furthermore, the system has been successfully tested measuring the response of a microcantilever-based resonant sensor, achieving similar results with better power-bandwidth trade-off compared to other LIAs based on commercial off-the-shelf (COTS) components and commercial LIA equipment.

Conversion from Prograf to Advagraf in stable paediatric renal transplant patients and 1-year follow-up.

BACKGROUND: The conversion from Prograf to Advagraf on a 1:1 (mg:mg) basis has been questioned in light of the publication of studies showing a decrease in tacrolimus blood concentrations after the administration of Advagraf. METHODS: The bioavailability of Prograf and Advagraf was evaluated in an open-label conversion study in 21 stable renal transplant paediatric patients. Serial blood samples for determining tacrolimus levels were collected during a 24-h period before (on Prograf) and after (on Advagraf) conversion. Tacrolimus pharmacokinetic parameters were calculated using a non-compartmental approach and the relative bioavailability calculated. Clinical and analytical data were obtained at 30, 90, 180 and 360 days after study enrolment. RESULTS: The mean ratio and 90 % confidence interval (CI) for peak plasma drug concentration (C(max)) and the area under the time-concentration curve during the first 24 h (AUC(0-24)) were 81.54 (95 % CI 71.6-92.87) and 87.19 (95 % CI 79.91-95.13), respectively. Renal glomerular filtration rate remained stable over the course of the follow-up. Two patients presented clinical events unrelated to tacrolimus. Tacrolimus levels decreased in the first month, the dose/level ratio increased between months 1 and 6 and slight dose adjustments were required during the follow-up period. CONCLUSIONS: Our results show that Advagraf bioequivalence cannot be ensured in this population. Significant changes in tacrolimus levels and dose were observed on long-term follow-up.

Vancomycin-induced acute kidney injury detected by a prospective pharmacovigilance program from laboratory signals.

BACKGROUND: Retrospective studies have identified elevated vancomycin trough levels >20 mg/L as a predictor of nephrotoxicity with a high variable incidence of 12.6%-65%. However, the elevated levels may represent the effect of renal compromise rather than the cause of nephrotoxicity. The aim of this study was to report the incidence of acute kidney injury (AKI) and associated risk factors in adult patients with vancomycin trough levels >20 mg/L in a prospective Pharmacovigilance Program from Laboratory Signals at a Hospital. METHODS: This was a prospective follow-up of all cases with serum vancomycin trough levels >20 mg/L between June 2010 and May 2011. AKI was defined using the Risk, Injury, Failure, Loss, End-stage criteria. Patients with vancomycin-induced AKI (VIAKI) were compared with vancomycin-tolerant patients. RESULTS: During 12 months of study, 271 samples corresponding to 179 cases were monitored. Vancomycin did not alter the renal function in 68.2% [95% confidence interval (CI): 60.8-74.9] of cases, and 13.4% (95% CI: 8.8-19.3) of AKI cases were induced by other causes. Nephrotoxicity without AKI criteria was found in 10.1% (95% CI: 6.1-15.4) of cases, and VIAKI occurred in 8.4% (95% CI: 4.8-13.4) of cases. The VIAKI group had a significantly lower basal glomerular filtration rate at baseline and higher vancomycin trough levels at the time of the signal. The majority of the group was in the intensive care unit and received nephrotoxic agents during vancomycin therapy. The most frequent stage of VIAKI was injury (53.3%). VIAKI occurred after 7 days (range: 3-14) of treatment, and in 53.3% of cases, the daily dose was >30 mg/kg. Renal function was recovered at discharge in 73.3% of cases and 66.7% of cases had other suspected drugs. CONCLUSIONS: The Pharmacovigilance Program from Laboratory Signals at a Hospital provides early identification and early evaluation of cases. Renal function and vancomycin trough levels should be closely monitored from the second week of treatment in adults, intensive care patients, and those who receive concurrent nephrotoxic agents.

Drug-induced life-threatening potassium disturbances detected by a pharmacovigilance program from laboratory signals.

PURPOSE: Detection and reporting of drug-induced life-threatening potassium disturbances and the study of associated factors under a Pharmacovigilance Program using Laboratory Signals at a Hospital (PPLSH) during a 2-year period. METHODS: All serum potassium levels <2 mmol/l or >7 mmol/l detected at admission to the hospital, including those of patients who died in the emergency ward or during hospitalization, were monitored prospectively from January 2009 through to December 2010. The incidence rate of each etiology of potassium disturbances was calculated. Factors associated with drug-induced potassium disturbances were detected using a multiple logistic regression model. RESULTS: The incidence of true life-threatening drug-induced hyper- and hypokalemia events was 3 and 4.32 (Poisson 95 % confidence interval 1.62-10.24), respectively, per 10,000 admissions. Of the severe potassium disturbances, 32.3 % were drug-induced, and 23 % were lethal. We identified previously undescribed pharmacological causes of hyperkalemia (risedronate, doxazosin) and hypokalemia (acyclovir, teicoplanin, cefepime, meropenem, dexketoprofen colistimethate). Significant predictor factors associated with drug-induced hyperkalemia were the use of polypharmacy (>5 drugs), age (>74 years), sex (female) and kidney disease (glomerular filtration rate <60 ml/min) with the presence of ≥4 comorbid conditions. The only predictor of drug-induced hypokalemia was the use of >5 drugs. The triggering factor associated with drug-induced hyperkalemia and hypokalemia was azotemia and hypoalbuminemia, respectively. CONCLUSIONS: Drug-induced life-threatening potassium disturbances remain a relevant problem. Potential strategies for prevention are to avoid polypharmacy, early discontinuation of treatment of drugs causing hyperkalemia or nephrotoxicity in cases of various clinical situations (cardiac descompensation, infection, hypovolemia) or obstructive causes, and insistence on albumin control during hospitalization.

Access to trauma center care: A statewide system-based approach.

BACKGROUND: Timely access to specialized trauma care is a vital element in patient outcome after severe and critical injury requiring the skills of trauma teams in levels I and II trauma centers to avoid preventable mortality. We used system-based models to estimate timely access to care. METHODS: Trauma system models consisted of ground emergency medical services, helicopter emergency medical services, and designated levels I to V trauma centers were constructed for five states. These models incorporated geographic information systems along with traffic data and census block group data to estimate population access to trauma care within the "golden hour." Trauma systems were further analyzed to identify the optimal location for an additional level I or II trauma center that would provide the greatest increase in access. RESULTS: The population of the states studied totaled 23 million people, of which 20 million (87%) had access to a level I or II trauma center within 60 minutes. Statewide-specific access ranged from 60% to 100%. Including levels III to V trauma centers, access within 60 minutes increased to 22 million (96%), ranging from 95% to 100%. The addition of a levels I and II trauma center in an optimized location in each state would provide timely access to a higher trauma capability for an additional 1.1 million, increasing total access to approximately 21.1 million people (92%). CONCLUSION: This analysis demonstrates that nearly universal access to trauma care is present in these states when including levels I to V trauma centers. However, concerning gaps remain in timely access to levels I and II trauma centers. This study provides an approach to determine more robust statewide estimates of access to care. It highlights the need for a national trauma system, one in which all components of state-managed trauma systems are assembled in a national data set to accurately identify gaps in care. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level IV.

Detecting disability using self-reported and clinical assessments in early-stage relapsing-remitting multiple sclerosis: Looking for a complementary approach.

Disability accrual is mainly driven by progression independent of relapse activity, which is present even in early stages of relapsing-remitting multiple sclerosis (RRMS) and sometimes overlooked. This multicenter, non-interventional study evaluated whether patient-reported outcomes measures (PROMs) could capture disability in 189 early-stage RRMS patients (mean age: 36.1 ± 9.4 years, 71.4% female, mean disease duration: 1.4 ± 0.8 years, median EDSS: 1.0). The 9-Hole Peg Test (9-HPT), NeuroQoL Upper Extremity (NeuroQoL-UE), Timed 25-Foot Walk (T25-FW), Multiple Sclerosis Walking Scale (MSWS-12), Symbol Digit Modalities Test (SDMT), and Perceived Deficits Questionnaire (PDQ-5) were used to assess hand function, gait, and cognition, respectively. These functions were at least mildly affected in this early-stage population, finding significant correlations between PROMs and clinical assessments. PROMs could enable early-stage RRMS patients to communicate their perceived disability in different domains, assisting clinicians in disease monitoring and decision making.

Assessing care-related regret among nurses specialized in multiple sclerosis: A psychometric analysis of a new assessment battery.

Experiences of regret associated with caring for patients with multiple sclerosis (MS) can affect medical decisions. A non-interventional study was conducted to assess the dimensionality and item characteristics of a battery including the Regret Intensity Scale (RIS-10) and 15 items evaluating common situations experienced by nurses in MS care. A total of 97 nurses were included. The RIS-10 showed good internal reliability and a unidimensional structure according to Mokken analysis. All-item homogeneity coefficients exceeded 0.30, whereas scalability for the overall RIS-10 was 0.66, indicating a strong scale. This battery showed adequate psychometric properties to evaluate regret among MS nurses.

Sick leave and occupational burnout among nurses caring for patients with multiple sclerosis.

BACKGROUND: Sick leave is a common problem among healthcare professionals. Nurses play a critical role in the multidisciplinary management of multiple sclerosis (MS). However, limited information is available on the phenomenon of sick leave among MS nurses. OBJECTIVE: The aim of this study was to assess the presence of sick leave among nurses caring for patients with MS and to identify associated factors. METHODS: We conducted a multicenter, non-interventional, cross-sectional, web-based study. Nurses involved in MS care from across Spain answered a survey composed of demographic characteristics, professional background, questions about their standard practice, and a behavioral battery including the Maslach Burnout Inventory - Human Services Survey (MBI-HSS). A multivariable logistic regression analysis was conducted to determine the association between nurses' characteristics and sick leave. RESULTS: Ninety-six nurses were included in the study. Mean age (SD) was 44.6 (9.8) years, and 91.7% were female. Participants had a median of 6 (IQR 3.0, 11.0) years of expertise in MS managing a median of 15 (5.0, 35.0) patients per week. Sixteen participants (16.7%) had been on sick leave in the last 6 months, with a median absence of 14.5 days (7.0, 30.0). Sixteen nurses (16.7%) reported severe burnout. Participants on sick leave had higher levels of emotional exhaustion (mean MBI-HSS scores of 22.3 and 16.0, p=0.01) and inadequate interactions with their colleagues (mean Practice Environment Scale - Nursing Work Index scores of 11.8 and 13.1, p=0.01) than their counterparts. Burnout was associated with higher risk of sick leave in the multivariable analysis (OR=1.06 [95% CI 1.00, 1.13], p=0.04) after adjustment for confounders. CONCLUSIONS: Occupational burnout is associated with increased risk of sick leave among nurses managing patients with MS. Identifying burnout may be critical for implementing specific intervention strategies to maintain an adequate functioning of MS care units.

Preferences Toward Attributes of Disease-Modifying Therapies: The Role of Nurses in Multiple Sclerosis Care.

ABSTRACT: BACKGROUND: Nurses play an essential role in coordinating the care of patients with multiple sclerosis (MS) throughout their disease trajectory in a complex treatment landscape. The aim of this study was to assess nurses' preferences toward different disease-modifying therapy attributes. METHODS: We conducted a multicenter, noninterventional, cross-sectional study in collaboration with the Sociedad Española de Enfermería Neurológica. Nurses actively involved in MS care were invited to participate in the study. Prevention of disability progression, preservation of cognitive function, side effect profile and safety monitoring, and method of administration were the treatment attributes tested. Conjoint analysis was used to assess preferences in 8 simulated treatment options and rank them from most to least preferred. RESULTS: A total of 98 nurses were included in the study. The mean (SD) age was 44.7 (9.8) years, and 91.8% were female with a mean (SD) time of experience in MS care of 7.5 (5.4) years. Participants prioritized preservation of cognition (38.6%), followed by preventing disability progression (35.2%) and side effect risk and safety monitoring (13.5%). Route and frequency of administration were the least preferred attributes (7.4% and 5.3%, respectively). Estimated utilities were consistent across the sample according to sociodemographic and professional practice characteristics. CONCLUSIONS: Nurses' preferences toward treatments were mainly driven by efficacy attributes. This information may support the role of nurses in the multidisciplinary management of MS facilitating shared decision making.

A programmable plug & play sensor interface for WSN applications.

Cost reduction in wireless sensor networks (WSN) becomes a priority when extending their application to fields where a great number of sensors is needed, such as habitat monitoring, precision agriculture or diffuse greenhouse emission measurement. In these cases, the use of smart sensors is expensive, consequently requiring the use of low-cost sensors. The solution to convert such generic low-cost sensors into intelligent ones leads to the implementation of a versatile system with enhanced processing and storage capabilities to attain a plug and play electronic interface able to adapt to all the sensors used. This paper focuses on this issue and presents a low-voltage plug & play reprogrammable interface capable of adapting to different sensor types and achieving an optimum reading performance for every sensor. The proposed interface, which includes both electronic and software elements so that it can be easily integrated in WSN nodes, is described and experimental test results to validate its performance are given.

An FPGA-Based Machine Learning Tool for In-Situ Food Quality Tracking Using Sensor Fusion.

The continuous development of more accurate and selective bio- and chemo-sensors has led to a growing use of sensor arrays in different fields, such as health monitoring, cell culture analysis, bio-signals processing, or food quality tracking. The analysis and information extraction from the amount of data provided by these sensor arrays is possible based on Machine Learning techniques applied to sensor fusion. However, most of these computing solutions are implemented on costly and bulky computers, limiting its use in in-situ scenarios outside complex laboratory facilities. This work presents the application of machine learning techniques in food quality assessment using a single Field Programmable Gate Array (FPGA) chip. The characteristics of low-cost, low power consumption as well as low-size allow the application of the proposed solution even in space constrained places, as in food manufacturing chains. As an example, the proposed system is tested on an e-nose developed for beef classification and microbial population prediction.