Impact of antibiotics for children presenting to general practice with cough on adverse outcomes: secondary analysis from a multicentre prospective cohort study

BACKGROUND: Clinicians commonly prescribe antibiotics to prevent major adverse outcomes in children presenting in primary care with cough and respiratory symptoms, despite limited meaningful evidence of impact on these outcomes. AIM: To estimate the effect of children's antibiotic prescribing on adverse outcomes within 30 days of initial consultation. DESIGN AND SETTING: Secondary analysis of 8320 children in a multicentre prospective cohort study, aged 3 months to <16 years, presenting in primary care across England with acute cough and other respiratory symptoms. METHOD: Baseline clinical characteristics and antibiotic prescribing data were collected, and generalised linear models were used to estimate the effect of antibiotic prescribing on adverse outcomes within 30 days (subsequent hospitalisations and reconsultation for deterioration), controlling for clustering and clinicians' propensity to prescribe antibiotics. RESULTS: Sixty-five (0.8%) children were hospitalised and 350 (4%) reconsulted for deterioration. Clinicians prescribed immediate and delayed antibiotics to 2313 (28%) and 771 (9%), respectively. Compared with no antibiotics, there was no clear evidence that antibiotics reduced hospitalisations (immediate antibiotic risk ratio [RR] 0.83, 95% confidence interval [CI] = 0.47 to 1.45; delayed RR 0.70, 95% CI = 0.26 to 1.90, overall P = 0.44). There was evidence that delayed (rather than immediate) antibiotics reduced reconsultations for deterioration (immediate RR 0.82, 95% CI = 0.65 to 1.07; delayed RR 0.55, 95% CI = 0.34 to 0.88, overall P = 0.024). CONCLUSION: Most children presenting with acute cough and respiratory symptoms in primary care are not at risk of hospitalisation, and antibiotics may not reduce the risk. If an antibiotic is considered, a delayed antibiotic prescription may be preferable as it is likely to reduce reconsultation for deterioration

What gives rise to clinician gut feeling, its influence on management decisions and its prognostic value for children with RTI in primary care: a prospective cohort study.

BACKGROUND: The objectives were to identify 1) the clinician and child characteristics associated with; 2) clinical management decisions following from, and; 3) the prognostic value of; a clinician's 'gut feeling something is wrong' for children presenting to primary care with acute cough and respiratory tract infection (RTI). METHODS: Multicentre prospective cohort study where 518 primary care clinicians across 244 general practices in England assessed 8394 children aged ≥3 months and < 16 years for acute cough and RTI. The main outcome measures were: Self-reported clinician 'gut feeling'; clinician management decisions (antibiotic prescribing, referral for acute admission); and child's prognosis (reconsultation with evidence of illness deterioration, hospital admission in the 30 days following recruitment). RESULTS: Clinician years since qualification, parent reported symptoms (illness severity score ≥ 7/10, severe fever < 24 h, low energy, shortness of breath) and clinical examination findings (crackles/ crepitations on chest auscultation, recession, pallor, bronchial breathing, wheeze, temperature ≥ 37.8 °C, tachypnoea and inflamed pharynx) independently contributed towards a clinician 'gut feeling that something was wrong'. 'Gut feeling' was independently associated with increased antibiotic prescribing and referral for secondary care assessment. After adjustment for other associated factors, gut feeling was not associated with reconsultations or hospital admissions. CONCLUSIONS: Clinicians were more likely to report a gut feeling something is wrong, when they were more experienced or when children were more unwell. Gut feeling is independently and strongly associated with antibiotic prescribing and referral to secondary care, but not with two indicators of poor child health

Development and internal validation of a clinical rule to improve antibiotic use in children presenting to primary care with acute respiratory tract infection and cough: a prognostic cohort study

BACKGROUND: Antimicrobial resistance is a serious threat to public health, with most antibiotics prescribed in primary care. General practitioners (GPs) report defensive antibiotic prescribing to mitigate perceived risk of future hospital admission in children with respiratory tract infections. We developed a clinical rule aimed to reduce clinical uncertainty by stratifying risk of future hospital admission. METHODS: 8394 children aged between 3 months and 16 years presenting with acute cough (for ≤28 days) and respiratory tract infection were recruited to a prognostic cohort study from 247 general practitioner practices in England. Exposure variables included demographic characteristics, parent-reported symptoms, and physical examination signs. The outcome was hospital admission for respiratory tract infection within 30 days, collected using a structured, blinded review of medical records. FINDINGS: 8394 (100%) children were included in the analysis, with 78 (0·9%, 95% CI 0·7%-1·2%) admitted to hospital: 15 (19%) were admitted on the day of recruitment (day 1), 33 (42%) on days 2-7; and 30 (39%) on days 8-30. Seven characteristics were independently associated (p<0·01) with hospital admission: age <2 years, current asthma, illness duration of 3 days or less, parent-reported moderate or severe vomiting in the previous 24 h, parent-reported severe fever in the previous 24 h or a body temperature of 37·8°C or more at presentation, clinician-reported intercostal or subcostal recession, and clinician-reported wheeze on auscultation. The area under the receiver operating characteristic (AUROC) curve for the coefficient-based clinical rule was 0·82 (95% CI 0·77-0·87, bootstrap validated 0·81). Assigning one point per characteristic, a points-based clinical rule consisting of short illness, temperature, age, recession, wheeze, asthma, and vomiting (mnemonic STARWAVe; AUROC 0·81, 0·76-0·85) distinguished three hospital admission risk strata: very low (0·3%, 0·2-0·4%) with 1 point or less, normal (1·5%, 1·0-1·9%) with 2 or 3 points, and high (11·8%, 7·3-16·2%) with 4 points or more. INTERPRETATION: Clinical characteristics can distinguish children at very low, normal, and high risk of future hospital admission for respiratory tract infection and could be used to reduce antibiotic prescriptions in primary care for children at very low risk. FUNDING: National Institute for Health Research (NIHR)

Geographic information system (GIS) maps and malaria control monitoring: intervention coverage and health outcome in distal villages of Khammouane province, Laos

Abstract Background Insecticide-treated nets (ITNs) are a key intervention to control malaria. The intervention coverage varies as a consequence of geographical accessibility to remote villages and limitations of financial and human resources for the intervention. People's adherence to the intervention, i.e., proper use of ITNs, also affects malaria health outcome. The study objective is to explore the impact of the intervention coverage and people's adherence to the intervention on malaria health outcome among targeted villages in various geographic locations. Methods Geographic information system (GIS) maps were developed using the data collected in an active case detection survey in Khammouane province, Laos. The survey was conducted using rapid diagnostic tests (RDTs) and a structured questionnaire at 23 sites in the province from June to July, the rainy season, in 2005. A total of 1,711 villagers from 403 households participated in the survey. Results As indicated on the GIS maps, villages with malaria cases, lower intervention coverage, and lower adherence were identified. Although no malaria case was detected in most villages with the best access to the district center, several cases were detected in the distal villages, where the intervention coverage and adherence to the intervention remained relatively lower. Conclusion Based on the data and maps, it was demonstrated that malaria remained unevenly distributed within districts. Balancing the intervention coverage in the distal villages with the overall coverage and continued promotion of the proper use of ITNs are necessary for a further reduction of malaria cases in the province.</p

Multiple reassortment events in the evolutionary history of H1N1 influenza A virus since 1918

The H1N1 subtype of influenza A virus has caused substantial morbidity and mortality in humans, first documented in the global pandemic of 1918 and continuing to the present day. Despite this disease burden, the evolutionary history of the A/H1N1 virus is not well understood, particularly whether there is a virological basis for several notable epidemics of unusual severity in the 1940s and 1950s. Using a data set of 71 representative complete genome sequences sampled between 1918 and 2006, we show that segmental reassortment has played an important role in the genomic evolution of A/H1N1 since 1918. Specifically, we demonstrate that an A/H1N1 isolate from the 1947 epidemic acquired novel PB2 and HA genes through intra-subtype reassortment, which may explain the abrupt antigenic evolution of this virus. Similarly, the 1951 influenza epidemic may also have been associated with reassortant A/H1N1 viruses. Intra-subtype reassortment therefore appears to be a more important process in the evolution and epidemiology of H1N1 influenza A virus than previously realized

The developmental effects of media-ideal internalization and self-objectification processes on adolescents’ negative body-feelings, dietary restraint, and binge eating

Despite accumulated experimental evidence of the negative effects of exposure to media-idealized images, the degree to which body image, and eating related disturbances are caused by media portrayals of gendered beauty ideals remains controversial. On the basis of the most up-to-date meta-analysis of experimental studies indicating that media-idealized images have the most harmful and substantial impact on vulnerable individuals regardless of gender (i.e., “internalizers” and “self-objectifiers”), the current longitudinal study examined the direct and mediated links posited in objectification theory among media-ideal internalization, self-objectification, shame and anxiety surrounding the body and appearance, dietary restraint, and binge eating. Data collected from 685 adolescents aged between 14 and 15 at baseline (47 % males), who were interviewed and completed standardized measures annually over a 3-year period, were analyzed using a structural equation modeling approach. Results indicated that media-ideal internalization predicted later thinking and scrutinizing of one’s body from an external observer’s standpoint (or self-objectification), which then predicted later negative emotional experiences related to one’s body and appearance. In turn, these negative emotional experiences predicted subsequent dietary restraint and binge eating, and each of these core features of eating disorders influenced each other. Differences in the strength of these associations across gender were not observed, and all indirect effects were significant. The study provides valuable information about how the cultural values embodied by gendered beauty ideals negatively influence adolescents’ feelings, thoughts and behaviors regarding their own body, and on the complex processes involved in disordered eating. Practical implications are discussed

The effects of spatial population dataset choice on estimates of population at risk of disease

Background: The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example.Methods: The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets.Results: The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets.Conclusions: Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. © 2011 Tatem et al; licensee BioMed Central Ltd.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Patient-centric trials for therapeutic development in precision oncology

An enhanced understanding of the molecular pathology of disease gained from genomic studies is facilitating the development of treatments that target discrete molecular subclasses of tumours. Considerable associated challenges include how to advance and implement targeted drug-development strategies. Precision medicine centres on delivering the most appropriate therapy to a patient on the basis of clinical and molecular features of their disease. The development of therapeutic agents that target molecular mechanisms is driving innovation in clinical-trial strategies. Although progress has been made, modifications to existing core paradigms in oncology drug development will be required to realize fully the promise of precision medicine

The International Limits and Population at Risk of Plasmodium vivax Transmission in 2009

Growing evidence shows that Plasmodium vivax malaria is clinically less benign than has been commonly believed. In addition, it is the most widely distributed species of human malaria and is likely to cause more illness in certain regions than the more extensively studied P. falciparum malaria. Understanding where P. vivax transmission exists and measuring the number of people who live at risk of infection is a fundamental first step to estimating the global disease toll. The aim of this paper is to generate a reliable map of the worldwide distribution of this parasite and to provide an estimate of how many people are exposed to probable infection. A geographical information system was used to map data on the presence of P. vivax infection and spatial information on climatic conditions that impede transmission (low ambient temperature and extremely arid environments) in order to delineate areas where transmission was unlikely to take place. This map was combined with population distribution data to estimate how many people live in these areas and are, therefore, exposed to risk of infection by P. vivax malaria. The results show that 2.85 billion people were exposed to some level of risk of transmission in 2009