Medication storage in Emergency Medical Services : temperature ranges from a South African sample

CITATION: Wylie, C. A., et al. 2021. Medication storage in Emergency Medical Services : temperature ranges from a South African sample. South African Journal of Pre-hospital Emergency Care, 2(1):2-6, doi:10.24213/2-1-4480.The original publication is available at https://www.journals.ac.za/index.php/sajpec/Background: Pre-hospital emergency care providers working in emergency medical services (EMS) are licenced to administer medication to the acutely ill and injured. In South Africa, there are significant seasonal variations in temperature, sometimes far exceeding the recommended medication storage temperature. The aim of this study was to determine the summer temperature ranges inside select emergency vehicles and storage facilities in four provinces in South Africa. Methods: A prospective, observational study was conducted in four (Cape Town, Western Cape; Johannesburg, Gauteng; Durban, KwaZulu-Natal; Potchefstroom, North West) provinces during the summer (February – March) months of 2019. A continuous temperature monitoring device was placed in the medication storage room, the response vehicle drug bags, and an ambulance at a single private EMS base in each of the provinces. Temperature data were recorded in fifteen-minute intervals. The data were extracted after six weeks and subjected to descriptive analysis. Data were also analysed in six-hourly strata to account for daily temperature variations. Results: A total of 36 002 temperature readings were recorded during the study period. The mean (range) temperature across the four bases was 25.4°C (13.1–56.8) for ambulances, 25.7°C (13.3–49.1) for primary response vehicles, and 24.4°C (17.3–33.9) for medication storage facilities. The highest mean (range) temperatures, of 33.7°C (20.4–47.9), were recorded in a Johannesburg-based primary response vehicle between 12h00 and 18h00. Conclusion: Current medication storing and transporting practices not maintain temperatures according to the recommended storage conditions. Further investigation should address the implication of temperature fluctuations on medication degradation, and a sustainable, cost-effective solution should be developed to store medication in the pre-hospital setting.https://www.journals.ac.za/index.php/sajpec/article/view/4480Publisher's versio

Nonlinear Dynamics in Ecosystem Response to Climatic Change: Case Studies and Policy Implications

Many biological, hydrological, and geological processes are interactively linked in ecosystems. These ecological phenomena normally vary within bounded ranges, but rapid, nonlinear changes to markedly different conditions can be triggered by even small differences if threshold values are exceeded. Intrinsic and extrinsic ecological thresholds can lead to effects that cascade among systems, precluding accurate modeling and prediction of system response to climate change. Ten case studies from North America illustrate how changes in climate can lead to rapid, threshold-type responses within ecological communities; the case studies also highlight the role of human activities that alter the rate or direction of system response to climate change. Understanding and anticipating nonlinear dynamics are important aspects of adaptation planning since responses of biological resources to changes in the physical climate system are not necessarily proportional and sometimes, as in the case of complex ecological systems, inherently nonlinear

A retrospective descriptive analysis of non-physician-performed prehospital endotracheal intubation practices and performance in South Africa

Introduction Prehospital advanced airway management, including endotracheal intubation (ETI), is one of the most commonly performed advanced life support skills. In South Africa, prehospital ETI is performed by non-physician prehospital providers. This practice has recently come under scrutiny due to lower first pass (FPS) and overall success rates, a high incidence of adverse events (AEs), and limited evidence regarding the impact of ETI on mortality. The aim of this study was to describe non-physician ETI in a South African national sample in terms of patient demographics, indications for intubation, means of intubation and success rates. A secondary aim was to determine what factors were predictive of first pass success. Methods This study was a retrospective chart review of prehospital ETIs performed by non-physician prehospital providers, between 01 January 2017 and 31 December 2017. Two national private Emergency Medical Services (EMS) and one provincial public EMS were sampled. Data were analysed descriptively and summarised. Logistic regression was performed to evaluate factors that affect the likelihood of FPS. Results A total of 926 cases were included. The majority of cases were adults (n = 781, 84.3%) and male (n = 553, 57.6%). The most common pathologies requiring emergency treatment were head injury, including traumatic brain injury (n = 328, 35.4%), followed by cardiac arrest (n = 204, 22.0%). The mean time on scene was 46 minutes (SD = 28.3). The most cited indication for intubation was decreased level of consciousness (n = 515, 55.6%), followed by cardiac arrest (n = 242, 26.9%) and ineffective ventilation (n = 96, 10.4%). Rapid sequence intubation (RSI, n = 344, 37.2%) was the most common approach. The FPS rate was 75.3%, with an overall success rate of 95.7%. Intubation failed in 33 (3.6%) patients. The need for ventilation was inversely associated with FPS (OR = 0.42, 95% CI: 0.20–0.88, p = 0.02); while deep sedation (OR = 0.56, 95% CI: 0.36–0.88, p = 0.13) and no drugs (OR = 0.47, 95% CI: 0.25–0.90, p = 0.02) compared to RSI was less likely to result in FPS. Increased scene time (OR = 0.99, 95% CI: 0.985–0.997, p < 0.01) was inversely associated FPS. Conclusion This is one of the first and largest studies evaluating prehospital ETI in Africa. In this sample of ground-based EMS non-physician ETI, we found success rates similar to those reported in the literature. More research is needed to determine AE rates and the impact of ETI on patient outcome. There is an urgent need to standardise prehospital ETI reporting in South Africa to facilitate future research

Development of a psychological intervention for fatigue after stroke

Post-stroke fatigue (PSF) is common and distressing, but there is insufficient evidence to recommend any effective treatment for it. Psychological interventions are effective in treating fatigue in other conditions. This paper describes the development and evaluation of the feasibility of a psychological intervention for PSF.Based on psychological correlates of PSF and evidence-based psychological interventions for fatigue in other medical conditions, we developed a manualised psychological intervention for PSF, with input from stroke clinicians, psychological therapists, and stroke survivors. The intervention was delivered by a clinical psychologist to 12 participants with PSF to test its acceptability and feasibility. According to the feedback from participants and therapists, the intervention was refined for future use.The intervention consisted of six individual, face-to-face treatment sessions, and one follow-up, telephone-delivered booster session. It included psycho-education and discussion of strategies to promote physical and social activities and to challenge unhelpful thoughts. Four participants dropped out and the remaining eight participants completed the intervention. These eight participants also completed all assessments and feedback and reported fatigue levels as lower at the end of the study than at the baseline. All participants reported favourable opinions on the intervention and suggested that the last two treatment sessions be combined and the booster session be delivered in person as opposed to telephone.This psychological intervention was acceptable to stroke patients and was feasible in the local health service. These findings suggest that a randomised controlled trial to test efficacy is warranted

Genome modeling system: A knowledge management platform for genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio