What helps volunteers to continue with their work?

Aim: The aim of the study was to understand what volunteers perceived to be the factors helping them to continue working as volunteers, thereby assisting project leaders to improve the recruitment procedures, as well as quality of service, in the future. Methodology: A focus group interview was held with the 14 most active volunteers in order to understand their perceptions about their work and their ability to continue their work as volunteers. The recorded interview was transcribed, translated and analysed. Findings: The volunteers feel that their work consists of various forms of support to patients. They see themselves as mediators (advocates) for the patients within the health care services. They have difficulties with some patients, who have high expectations of them. They also feel deeply about the difficulties experienced by many patients, particularly poverty. They are strongly motivated by their desire to help their own community. This is reinforced when they are thanked by patients whose health has improved as a result of the assistance they provided. They feel that, as people, they have gained knowledge and confidence. The support from the project coordinators/fieldworkers is very important to them. Conclusions: The findings above represent what would be motivational in general: internal motivation, the ability to see the importance of your work, positive feedback, a plan to deal with difficulties and support from senior colleagues. It is therefore important to ensure such support and cooperation at various levels. Keywords: Home-based care, volunteers, AIDS, motivation. For full text, click here: SA Fam Pract 2004;46(1) :25-2

Who are good home-based care volunteers?

Aim: The aim of the study was to describe the characteristics of volunteers who remained active in the home-based care project located in Tzaneen (Limpopo Province) and thereby assist the project leaders to improve the recruitment and quality of the service in the future. Methodology: Structured questionnaires were completed with all the available volunteers trained during 1999. The questionnaires were quantitatively analysed manually. Results: Ninety-six (96) people attended the introductory phase of the home-based care course during 1999. Seventy-one (71) were volunteers and 25 were people living with HIV. Forty-six (46) of the participants completed the questionnaires (44 volunteers plus two people living with HIV working as volunteers). Twenty-seven (27) volunteers could not be traced, as they were no longer active in the project. The following factors were associated with active volunteers: 1. Married 2. Female 3. >30 years of age 4. Breadwinners themselves or have a husband/spouse who is the breadwinner. Conclusions: Presently, most of the active volunteers are married, female, older than 30 and are the breadwinner themselves or have a husband who is the breadwinner. Key words: Home-based care, volunteers, Aids, characteristics For full text, click here: SA Fam Pract 2004; 46(2) : 29-3

Predicting need for hospital admission in patients with traumatic brain injury or skull fractures identified on CT imaging : a machine learning approach

Background: Patients with mild traumatic brain injury on CT scan are routinely admitted for inpatient observation. Only a small proportion of patients require clinical intervention. We recently developed a decision rule using traditional statistical techniques that found neurologically intact patients with isolated simple skull fractures or single bleeds <5 mm with no preinjury antiplatelet or anticoagulant use may be safely discharged from the emergency department. The decision rule achieved a sensitivity of 99.5% (95% CI 98.1% to 99.9%) and specificity of 7.4% (95% CI 6.0% to 9.1%) to clinical deterioration. We aimed to transparently report a machine learning approach to assess if predictive accuracy could be improved. Methods: We used data from the same retrospective cohort of 1699 initial Glasgow Coma Scale (GCS) 13–15 patients with injuries identified by CT who presented to three English Major Trauma Centres between 2010 and 2017 as in our original study. We assessed the ability of machine learning to predict the same composite outcome measure of deterioration (indicating need for hospital admission). Predictive models were built using gradient boosted decision trees which consisted of an ensemble of decision trees to optimise model performance. Results: The final algorithm reported a mean positive predictive value of 29%, mean negative predictive value of 94%, mean area under the curve (C-statistic) of 0.75, mean sensitivity of 99% and mean specificity of 7%. As with logistic regression, GCS, severity and number of brain injuries were found to be important predictors of deterioration. Conclusion: We found no clear advantages over the traditional prediction methods, although the models were, effectively, developed using a smaller data set, due to the need to divide it into training, calibration and validation sets. Future research should focus on developing models that provide clear advantages over existing classical techniques in predicting outcomes in this population

Performance of the Hull Salford Cambridge Decision Rule (HSC DR) for early discharge of patients with findings on CT scan of the brain : a CENTER-TBI validation study

Background: There is international variation in hospital admission practices for patients with mild traumatic brain injury (TBI) and injuries on CT scan. Only a small proportion of patients require neurosurgical intervention, while many guidelines recommend routine admission of all patients. We aim to validate the Hull Salford Cambridge Decision Rule (HSC DR) and the Brain Injury Guidelines (BIG) criteria to select low-risk patients for discharge from the emergency department. Method: A cohort from 18 countries of Glasgow Coma Scale 13–15 patients with injuries on CT imaging was identified from the multicentre Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) Study (conducted from 2014 to 2017) for secondary analysis. A composite outcome measure encompassing need for ongoing hospital admission was used, including seizure activity, death, intubation, neurosurgical intervention and neurological deterioration. We assessed the performance of our previously derived prognostic model, the HSC DR and the BIG criteria at predicting deterioration in this validation cohort. Results: Among 1047 patients meeting the inclusion criteria, 267 (26%) deteriorated. Our prognostic model achieved a C-statistic of 0.81 (95% CI: 0.78 to 0.84). The HSC DR achieved a sensitivity of 100% (95% CI: 97% to 100%) and specificity of only 4.7% (95% CI: 3.3% to 6.5%) for deterioration. Using the BIG criteria for discharge from the ED achieved a higher specificity (13.3%, 95% CI: 10.9% to 16.1%) and lower sensitivity (94.6%, 95% CI: 90.5% to 97%), with 12/105 patients recommended for discharge subsequently deteriorating, compared with 0/34 with the HSC DR. Conclusion: Our decision rule would have allowed 3.5% of patients to be discharged, none of whom would have deteriorated. Use of the BIG criteria may select patients for discharge who have too high a risk of subsequent deterioration to be used clinically. Further validation and implementation studies are required to support use in clinical practice

Factors associated with increased Emergency Department transfer in older long-term care residents: a systematic review

The proportion of adults older than 65 years is rapidly increasing. Care home residents in this age group have disproportionate rates of transfer to the Emergency Department (ED) and around 40% of attendances might be avoidable. We did a systematic review to identify factors that predict ED transfer from care homes. Six electronic databases were searched. Observational studies that provided estimates of association between ED attendance and variables at a resident or care home level were included. 26 primary studies met the inclusion criteria. Seven common domains of factors assessed for association with ED transfer were identified and within these domains, male sex, age, presence of specific comorbidities, polypharmacy, rural location, and care home quality rating were associated with likelihood of ED transfer. The identification of these factors provides useful information for policy makers and researchers intending to either develop interventions to reduce hospitalisations or use adjusted rates of hospitalisation as a care home quality indicator

What influences decisions to transfer older care-home residents to the emergency department? A synthesis of qualitative reviews

Background care home residents aged over 65 have disproportionate rates of emergency department (ED) attendance and hospitalisation. Around 40% attendances may be avoidable, and hospitalisation is associated with harms. We synthesised the evidence available in qualitative systematic reviews of different stakeholders’ experiences of decisions to transfer residents to the ED. Methods six electronic databases, references and citations of included reviews and relevant policy documents were searched. Reviews of qualitative studies exploring factors that influenced care home staff, medical practitioners, residents’ family or residents’ experiences and factors influencing decisions to transfer residents to the ED were included. Thematic analysis was used to synthesise findings. Results six previous reviews were included, which synthesised the findings of 34 primary studies encompassing 152 care home residents, 283 resident family members or carers and 447 care home staff. Of the primary studies, 19 were conducted in the North America, seven in Australia, five were conducted in Scandinavia, two in the United Kingdom and one in Holland. Three themes were identified: (i) power dynamics between residents, family members, care home staff and health care professionals (external to the care home) influence decisions; (ii) admission can be necessary; however, (iii) some decisions may be driven by factors other than clinical need. Conclusion transfer decisions are complex and are determined not just by changes in health status interventions aimed at reducing avoidable transfers need to address the key role family members have in transfer decisions, the medical legal fears of care home staff and barriers to accessing community services

Fungal pathogens of Proteaceae

Species of Leucadendron, Leucospermum and Protea (Proteaceae) are in high demand for the international floriculture market due to their brightly coloured and textured flowers or bracts. Fungal pathogens, however, create a serious problem in cultivating flawless blooms. The aim of the present study was to characterise several of these pathogens using morphology, culture characteristics, and DNA sequence data of the rRNA-ITS and LSU genes. In some cases additional genes such as TEF 1-α and CHS were also sequenced. Based on the results of this study, several novel species and genera are described. Brunneosphaerella leaf blight is shown to be caused by three species, namely B. jonkershoekensis on Protea repens, B. nitidae sp. nov. on Protea nitida and B. protearum on a wide host range of Protea spp. (South Africa). Coniothyrium-like species associated with Coniothyrium leaf spot are allocated to other genera, namely Curreya grandicipis on Protea grandiceps, and Microsphaeropsis proteae on P. nitida (South Africa). Diaporthe leucospermi is described on Leucospermum sp. (Australia), and Diplodina microsperma newly reported on Protea sp. (New Zealand). Pyrenophora blight is caused by a novel species, Pyrenophora leucospermi, and not Drechslera biseptata or D. dematoidea as previously reported. Fusicladium proteae is described on Protea sp. (South Africa), Pestalotiopsis protearum on Leucospermum cuneiforme (Zimbabwe), Ramularia vizellae and R. stellenboschensis on Protea spp. (South Africa), and Teratosphaeria capensis on Protea spp. (Portugal, South Africa). Aureobasidium leaf spot is shown to be caused by two species, namely A. proteae comb. nov. on Protea spp. (South Africa), and A. leucospermi sp. nov. on Leucospermum spp. (Indonesia, Portugal, South Africa). Novel genera and species elucidated in this study include Gordonomyces mucovaginatus and Pseudopassalora gouriqua (hyphomycetes), and Xenoconiothyrium catenata (coelomycete), all on Protea spp. (South Africa)

Ceratocystis ficicola causing a serious disease of Ficus carica in Greece

Ceratocystis ficicola causes vascular wilt of fig trees in Japan, invading root systems and the main stems eventually leading to tree death. In surveys from 2018 to 2020 in fig orchards in Greece, this fungus was detected in two separated regions. The fungus was consistently isolated from infected wood and from rhizosphere soil. The isolates were identified based on multi-locus phylogenetic analyses of rpb2, bt1 and tef1 gene regions and detailed morphological characteristics, including comparisons with an ex-type isolate of C. ficicola from Japan. The pathogenicity of Greek isolates was proven on Ficus carica and F. benjamina plants. Ceratocystis ficicola is a soilborne pathogen, and the occurrence of vascular wilt outbreaks suggest that the pathogen spreads within and between orchards with infested soil and wood debris during ploughing. The pathogen is also spreading in Greece with infected propagation material. This is the first detailed report of C. ficicola outside Japan, and there is concern over potential spread of the pathogen to other Mediterranean countries, where approx. 70% of the world fig production occurs.The Department of Science and Technology/National Research Foundation Center of Excellence in Plant Health Biotechnology, South Africa.https://oajournals.fupress.net/index.php/pmam2022BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant Patholog

Scoping review of the effectiveness of 10 high-impact initiatives (HIIs) for recovering urgent and emergency care services

Introduction Prolonged ambulance response times and unacceptable emergency department (ED) wait times are significant challenges in urgent and emergency care systems associated with patient harm. This scoping review aimed to evaluate the evidence base for 10 urgent and emergency care high-impact initiatives identified by the National Health Service (NHS) England. Methods A two-stage approach was employed. First, a comprehensive search for reviews (2018–2023) was conducted across PubMed, Epistemonikos and Google Scholar. Additionally, full-text searches using Google Scholar were performed for studies related to the key outcomes. In the absence of sufficient review-level evidence, relevant available primary research studies were identified through targeted MEDLINE and HMIC searches. Relevant reviews and studies were mapped to the 10 high-impact initiatives. Reviewers worked in pairs or singly to identify studies, extract, tabulate and summarise data. Results The search yielded 20 771 citations, with 48 reviews meeting the inclusion criteria across 10 sections. In the absence of substantive review-level evidence for the key outcomes, primary research studies were also sought for seven of the 10 initiatives. Evidence for interventions improving ambulance response times was generally scarce. ED wait times were commonly studied using ED length of stay, with some evidence that same day emergency care, acute frailty units, care transfer hubs and some in-patient flow interventions might reduce direct and indirect measures of wait times. Proximal evidence existed for initiatives such as urgent community response, virtual hospitals/hospital at home and inpatient flow interventions (involving flow coordinators), which did not typically evaluate the NHS England outcomes of interest. Conclusions Effective interventions were often only identifiable as components within the NHS England 10 high-impact initiative groupings. The evidence base remains limited, with substantial heterogeneity in urgent and emergency care initiatives, metrics and reporting across different studies and settings. Future research should focus on well-defined interventions while remaining sensitive to local context

Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19 : observational cohort study

Background Measurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19. Methods We undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis. Results We analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019). Conclusions Post-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19