Urine Toxicology Screen in Multiple Sleep Latency Test: The Correlation of Positive Tetrahydrocannabinol, Drug Negative Patients, and Narcolepsy

Objective: Drugs can influence results of multiple sleep latency tests (MSLT). We sought to identify the effect of marijuana on MSLT results in pediatric patients evaluated for excessive daytime sleepiness (EDS). Methods: This is a retrospective study of urine drug screens performed the morning before MSLT in 383 patients \u3c 21 years old referred for EDS. MSLT results were divided into those with (1) (-) urine drug screens, (2) urine drug screens (+) for tetrahydrocannabinol (THC) alone or THC plus other drugs, and (3) urine drug screens (+) for drugs other than THC. Groups were compared with Fisher exact tests or one-way ANOVA. Results: 38 (10%) urine drug tests were (+): 14 for THC and 24 for other drugs. Forty-three percent of patients with drug screen (+) for THC had MSLT findings consistent with narcolepsy, 0% consistent with idiopathic hypersomnia, 29% other, and 29% normal. This was statistically different from those with (-) screens (24% narcolepsy, 20% idiopathic hypersomnia, 6% other, 50% normal), and those (+) for drugs other than THC (17% narcolepsy, 33% idiopathic hypersomnia, 4% other, 46% normal (p = 0.01). Six percent (6/93) of patients with MSLT findings consistent with narcolepsy were drug screen (+) for THC; 71% of patients with drug screen (+) for THC had multiple sleep onset REM periods (SOREMS). There were no (+) urine drug screens in patients \u3c 13 years old. Conclusion: Many pediatric patients with (+) urine drug screens for THC met MSLT criteria for narcolepsy or had multiple SOREMs. Drug screening is important in interpreting MSLT findings for children ≥ 13 years

Urine Toxicology Screen in Multiple Sleep Latency Test: The Correlation of Positive Tetrahydrocannabinol, Drug Negative Patients, and Narcolepsy

Objective: Drugs can influence results of multiple sleep latency tests (MSLT). We sought to identify the effect of marijuana on MSLT results in pediatric patients evaluated for excessive daytime sleepiness (EDS). Methods: This is a retrospective study of urine drug screens performed the morning before MSLT in 383 patients \u3c 21 years old referred for EDS. MSLT results were divided into those with (1) (-) urine drug screens, (2) urine drug screens (+) for tetrahydrocannabinol (THC) alone or THC plus other drugs, and (3) urine drug screens (+) for drugs other than THC. Groups were compared with Fisher exact tests or one-way ANOVA. Results: 38 (10%) urine drug tests were (+): 14 for THC and 24 for other drugs. Forty-three percent of patients with drug screen (+) for THC had MSLT findings consistent with narcolepsy, 0% consistent with idiopathic hypersomnia, 29% other, and 29% normal. This was statistically different from those with (-) screens (24% narcolepsy, 20% idiopathic hypersomnia, 6% other, 50% normal), and those (+) for drugs other than THC (17% narcolepsy, 33% idiopathic hypersomnia, 4% other, 46% normal (p = 0.01). Six percent (6/93) of patients with MSLT findings consistent with narcolepsy were drug screen (+) for THC; 71% of patients with drug screen (+) for THC had multiple sleep onset REM periods (SOREMS). There were no (+) urine drug screens in patients \u3c 13 years old. Conclusion: Many pediatric patients with (+) urine drug screens for THC met MSLT criteria for narcolepsy or had multiple SOREMs. Drug screening is important in interpreting MSLT findings for children ≥ 13 years

Urine Toxicology Screen in Multiple Sleep Latency Test: The Correlation of Positive Tetrahydrocannabinol, Drug Negative Patients, and Narcolepsy

OBJECTIVE: Drugs can influence results of multiple sleep latency tests (MSLT). We sought to identify the effect of marijuana on MSLT results in pediatric patients evaluated for excessive daytime sleepiness (EDS). METHODS: This is a retrospective study of urine drug screens performed the morning before MSLT in 383 patients < 21 years old referred for EDS. MSLT results were divided into those with (1) (−) urine drug screens, (2) urine drug screens (+) for tetrahydrocannabinol (THC) alone or THC plus other drugs, and (3) urine drug screens (+) for drugs other than THC. Groups were compared with Fisher exact tests or one-way ANOVA. RESULTS: 38 (10%) urine drug tests were (+): 14 for THC and 24 for other drugs. Forty-three percent of patients with drug screen (+) for THC had MSLT findings consistent with narcolepsy, 0% consistent with idiopathic hypersomnia, 29% other, and 29% normal. This was statistically different from those with (−) screens (24% narcolepsy, 20% idiopathic hypersomnia, 6% other, 50% normal), and those (+) for drugs other than THC (17% narcolepsy, 33% idiopathic hypersomnia, 4% other, 46% normal (p = 0.01). Six percent (6/93) of patients with MSLT findings consistent with narcolepsy were drug screen (+) for THC; 71% of patients with drug screen (+) for THC had multiple sleep onset REM periods (SOREMS). There were no (+) urine drug screens in patients < 13 years old. CONCLUSION: Many pediatric patients with (+) urine drug screens for THC met MSLT criteria for narcolepsy or had multiple SOREMs. Drug screening is important in interpreting MSLT findings for children ≥ 13 years. CITATION: Dzodzomenyo S, Stolfi A, Splaingard D, Earley E, Onadeko O, Splaingard M. Urine toxicology screen in multiple sleep latency test: the correlation of positive tetrahydrocannabinol, drug negative patients, and narcolepsy. J Clin Sleep Med 2015;11(2):93–99

Multi-Vector Approach to Cities’ Transition to Low-Carbon Emission Developments

Globally, cities have made efforts to shift to low-carbon emission development (LED), amidst air pollution, greenhouse gas (GHG) emissions, and high temperature anomalies. However, the emphasis on cities to help shift the global economy to LED has been on a single individual sector approach operating in silos rather than the inter and intra-specific outcomes of multiple sectors. Thus, there are uncertainties of adopting suitable pathways for cities&rsquo; transition to LED, due largely to data paucity and policy incoherence, constrained further by barriers to integrating science, policy, and practice. Hence, the need for cities to take advantage of the benefits of multi-directional perspectives of multiple sectors acting together&mdash;the &ldquo;multi-vector&rdquo; approach, to confront key questions of climate compatible development (CCD) that support LED. Therefore, the paper extends the development narratives of the CCD approach to an &ldquo;enhanced&rdquo; climate compatible development (EnCCD) pathway with in-built questions and determinants to scope cities&rsquo; transition to LED. The EnCCD suggests that the standalone intersection between mitigation and development to deliver LED will not result in cities&rsquo; resilience unless (i) co-benefits, which are outcomes of mitigation and adaptation, and (ii) climate-resilient development, the product of adaptation and development, coevolved. Therefore, the EnCCD transforms the development policy focus of cities on separate, single-purpose sectors, such as energy or transport, into multi-sector portfolios having synergistic benefits of mitigation, adaptation, and development strategies

An assessment of inter-observer agreement in water source classification and sanitary risk observations

Sanitary risk inspection, an observation protocol for identifying contamination hazards around water sources, is promoted for managing rural water supply safety. However, it is unclear how far different observers consistently identify contamination hazards and consistently classify water source types using standard typologies.This study aimed to quantify inter-observer agreement in hazard identification and classification of rural water sources. Six observers separately visited 146 domestic water sources in Siaya County, Kenya, in wet and dry seasons. Each observer independently classified the source type and conducted a sanitary risk inspection using a standard protocol. Water source types assigned by an experienced observer were cross-tabulated against those of his colleagues, as were contamination hazards identified, and inter-observer agreement measures calculated. Agreement between hazards observed by the most experienced observer versus his colleagues was significant but low (intra-class correlation=0.49), with inexperienced observers detecting fewer hazards. Inter-observer agreement in classifying water sources was strong (Cohen’s kappa =0.84). However, some source types were frequently misclassified, such as sources adapted to cope with water insecurity (e.g. tanks drawing on both piped and rainwater).Observers with limited training and experience thus struggle to consistently identify hazards using existing protocols, suggesting observation protocols require revision and their implementation should be supported by comprehensive training. Findings also indicate that field survey teams struggle to differentiate some water source types based on a standard water source classification, particularly sources adapted to cope with water insecurity. These findings demonstrate uncertainties underpinning international monitoring and analyses of safe water access via household surveys.<br/

Earth System's Gatekeeping of “One Health” Approach to Manage Climate-Sensitive Infectious Diseases

Global response to climate-sensitive infectious diseases has been uncertain and slow. The understanding of the underlying vulnerabilities which forms part of changes created by forces within the Earth system has never before been critical until the coronavirus disease 2019, “COVID-19” pandemic with the initial developmental phase linked to weather elements and climate change. Hence, the heightened interest in climate-sensitive infectious diseases and GeoHealth, evident in the renewed calls for “One Health” approach to disease management. “One Health” explains the commonality of human and animal medicine, and links to the bio-geophysical environment, yet are at crossroads with how forces within the Earth system shape etiologies, incidences, and transmission dynamics of infectious diseases. Hence, the paper explores how these forces, which are multistage and driven by climate change impacts on ecosystems affect emerging infectious diseases, leading to the question “what drive the drivers of diseases?” Three questions that challenge broad theories of Earth system science on boundaries and connectivity emerged to guide study designs to further interrogating disease surveillance and health early warning systems. This is because, climate change (a) drives prevailing biological health hazards as part of forces within the Earth system, (b) shifts disease control services of ecosystems and functioning to effectively regulate disease incidence, and (c) modifies pathogen—species hosts relationships. Hence, the need to rethink pluralistic concepts of climate-sensitive diseases in their infection and management from a GeoHealth perspective, which “One Health” potentially conveys, and to also maintain ecosystem health