2,320 research outputs found
The design and development of a decision support package for low back pain
No full textArthritis Care & Research is published by Wiley
Periodicals, Inc. on behalf of the American College of Rheumatology.
This is an open access article under the terms of the Creative Commons
Attribution-NonCommercial-NoDerivs License, which permits use and
distribution in any medium, provided the original work is properly cited,
the use is non-commercial and no modifications or adaptations are made.Objective: To develop a decision support package for people with low back pain (LBP) referred for physiotherapy. Methods: A programme of exploratory work including, literature reviews, a Delphi study, a nominal group with physiotherapists, focus groups with patients' and secondary analysis of existing interview data. Results: We developed an information booklet describing the evidence-based treatment modalities available in a physiotherapy department. This includes data on likely benefits and risks and how the intervention is delivered. The booklet specifically addresses questions identified as important in our exploratory work. Space is provided for patients to note down the pros and cons of each treatment and what matters to them when choosing treatments. The patient is subsequently directed to a section that explores any gaps in knowledge, values, support and choice before finally clarifying if a treatment decision is possible. At this stage they are encouraged to note down any questions or concerns they have to be discussed at the first physiotherapy consultation. This overall package includes patient material in the form of a booklet, posted prior to their consultation, plus the enhanced consultation with the specially trained physiotherapist. Patients then receive their chosen treatment. In addition we developed a training package for physiotherapists that explains the content of the booklet and supports them in using informed shared decision making in their consultation. Conclusion: This package has the potential to improve effectiveness of treatments and patient satisfaction for LBP by facilitating patient choice and thus matching patients more effectively to different treatments. © 2013 American College of Rheumatology
Genetic Optimization Using Derivatives: The rgenoud Package for R
No full textgenoud is an R function that combines evolutionary algorithm methods with a derivative-based (quasi-Newton) method to solve difficult optimization problems. genoud may also be used for optimization problems for which derivatives do not exist. genoud solves problems that are nonlinear or perhaps even discontinuous in the parameters of the function to be optimized. When the function to be optimized (for example, a log-likelihood) is nonlinear in the model's parameters, the function will generally not be globally concave and may have irregularities such as saddlepoints or discontinuities. Optimization methods that rely on derivatives of the objective function may be unable to find any optimum at all. Multiple local optima may exist, so that there is no guarantee that a derivative-based method will converge to the global optimum. On the other hand, algorithms that do not use derivative information (such as pure genetic algorithms) are for many problems needlessly poor at local hill climbing. Most statistical problems are regular in a neighborhood of the solution. Therefore, for some portion of the search space, derivative information is useful. The function supports parallel processing on multiple CPUs on a single machine or a cluster of computers.
Using machine learning to predict antibody response to SARS-CoV-2 vaccination in solid organ transplant recipients: the multicentre ORCHESTRA cohort
No full textObjectives: Study aim is to assess predictors of negative antibody response (AbR) in solid organ transplant (SOT) recipients after the first booster of SARS-CoV-2 vaccination.
Methods: SOT recipients receiving SARS-CoV-2 vaccination were prospectively enrolled (March 2021-January 2022) at six hospitals in Italy and Spain. AbR was assessed at first dose (t0), second dose (t1), 3±1 month (t2), and 1 month after third dose (t3). Negative AbR at t3 was defined as anti-receptor binding domain titre <45 BAU/mL. Machine Learning models were developed to predict the individual risk of negative (vs. positive) AbR using as covariates age, type of transplant, time between transplant and vaccination, immunosuppressive drugs, type of vaccine, and graft function, and subsequently assessed using a validation cohort.
Results: Overall, 1615 SOT recipients (1072 [66.3%] males, mean±standard deviation (SD) age 57.85±13.77) were enrolled and 1211 received three vaccination doses. Negative AbR rate decreased from (886/946) 93.66% to (202/923) 21.90% from t0 to t3. Univariate analysis showed that older patients (mean age 60.21±11.51 vs. 58.11±13.08), anti-metabolites (57.9% vs. 35.1%) steroids (52.9% vs. 38.5%), recent transplantation (<3 years) (17.8% vs. 2.3%), and kidney, heart, or lung compared to liver transplantation (25%, 31.8%, 30.4% vs. 5.5%) had a higher likelihood of negative AbR. Machine learning algorithms showing best prediction performance were logistic regression (precision recall curve-PRAUC mean 0.37 [95%CI 0.36-0.39]) and k-Nearest Neighbors (PRAUC 0.36 [0.35-0.37]).
Conclusions: Almost a quarter of SOT recipients showed negative AbR after first booster dosage. Unfortunately, clinical information cannot efficiently predict negative AbR even with ML algorithms
Constraints to implementing the Essential Health Package in Malawi.
No full textIncreasingly seen as a useful tool of health policy, Essential or Minimal Health Packages direct resources to interventions that aim to address the local burden of disease and be cost-effective. Less attention has been paid to the delivery mechanisms for such interventions. This study aimed to assess the degree to which the Essential Health Package (EHP) in Malawi was available to its population and what health system constraints impeded its full implementation. The first phase of this study comprised a survey of all facilities in three districts including interviews with all managers and clinical staff. In the second and third phase, results were discussed with District Health Management Teams and national level stakeholders, respectively, including representatives of the Ministry of Health, Central Medical Stores, donors and NGOs. The EHP in Malawi is focussing on the local burden of disease; however, key constraints to its successful implementation included a widespread shortage of staff due to vacancies but also caused by frequent trainings and meetings (only 48% of expected man days of clinical staff were available; training and meetings represented 57% of all absences in health centres). Despite the training, the percentage of health workers aware of vital diagnostic and therapeutic approaches to EHP conditions was weak. Another major constraint was shortages of vital drugs at all levels of facilities (e.g. Cotrimoxazole was sufficiently available to treat the average number of patients in only 27% of health centres). Although a few health workers noted some improvement in infrastructure and working conditions, they still considered them to be widely inadequate. In Malawi, as in similar resource poor countries, greater attention needs to be given to the health system constraints to delivering health care. Removal of these constraints should receive priority over the considerable focus on the development and implementation of essential packages of interventions
Violence by clients towards female prostitutes in different work settings: questionnaire survey
No full textNo abstract available
Flexible Rasch Mixture Models with Package psychomix
No full textMeasurement invariance is an important assumption in the Rasch model and mixture models constitute a flexible way of checking for a violation of this assumption by detecting unobserved heterogeneity in item response data. Here, a general class of Rasch mixture models is established and implemented in R, using conditional maximum likelihood estimation of the item parameters (given the raw scores) along with flexible specification of two model building blocks: (1) Mixture weights for the unobserved classes can be treated as model parameters or based on covariates in a concomitant variable model. (2) The distribution of raw score probabilities can be parametrized in two possible ways, either using a saturated model or a specification through mean and variance. The function raschmix() in the R package "psychomix" provides these models, leveraging the general infrastructure for fitting mixture models in the "flexmix" package. Usage of the function and its associated methods is illustrated on artificial data as well as empirical data from a study of verbally aggressive behavior.mixed Rasch model, Rost model, mixture model, flexmix, R
Distributed simulation with COTS simulation packages: A case study in health care supply chain simulation
No full textThe UK National Blood Service (NBS) is a public funded body that is responsible for distributing blood and asso-ciated products. A discrete-event simulation of the NBS supply chain in the Southampton area has been built using the commercial off-the-shelf simulation package (CSP) Simul8. This models the relationship in the health care supply chain between the NBS Processing, Testing and Is-suing (PTI) facility and its associated hospitals. However, as the number of hospitals increase simulation run time be-comes inconveniently large. Using distributed simulation to try to solve this problem, researchers have used techniques informed by SISO’s CSPI PDG to create a version of Simul8 compatible with the High Level Architecture (HLA). The NBS supply chain model was subsequently divided into several sub-models, each running in its own copy of Simul8. Experimentation shows that this distri-buted version performs better than its standalone, conven-tional counterpart as the number of hospitals increases
Study protocol: Improving patient choice in treating low back pain (IMPACT - LBP): A randomised controlled trial of a decision support package for use in physical therapy
No full textCopyright @ 2011 Patel et al - This is an Open Access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Low back pain is a common and costly condition. There are several treatment options for people suffering from back pain, but there are few data on how to improve patients' treatment choices. This study will test the effects of a decision support package (DSP), designed to help patients seeking care for back pain to make better, more informed choices about their treatment within a physiotherapy department. The package will be designed to assist both therapist and patient.
Methods/Design: Firstly, in collaboration with physiotherapists, patients and experts in the field of decision support and decision aids, we will develop the DSP. The work will include: a literature and evidence review; secondary analysis of existing qualitative data; exploration of patients' perspectives through focus groups and exploration of experts' perspectives using a nominal group technique and a Delphi study.
Secondly, we will carry out a pilot single centre randomised controlled trial within NHS Coventry Community Physiotherapy. We will randomise physiotherapists to receive either training for the DSP or not. We will randomly allocate patients seeking treatment for non specific low back pain to either a physiotherapist trained in decision support or to receive usual care. Our primary outcome measure will be patient satisfaction with treatment at three month follow-up. We will also estimate the cost-effectiveness of the intervention, and assess the value of conducting further research.
Discussion: Informed shared decision-making should be an important part of any clinical consultation, particularly when there are several treatments, which potentially have moderate effects. The results of this pilot will help us determine the benefits of improving the decision-making process in clinical practice on patient satisfaction.This work is funded from the National Institute for Health Research (NIHR), Research for Patient Benefit (RfPB) Programme (Ref: PB-PG-0808-17039)
Gene diversity among some endogamous population of Amravati District, Maharashtra, India.
No full textThe present work deals with the distribution of ABO, Rh and sickling alleles as markers to study the genetic structure and micro-demarcation among castes and tribal populations from the Amravati district of Maharashtra. Three loci namely, ABO, Rh and sickling were selected to measure the relative frequency of respective alleles in ten (10) endogamous populations inhabiting the Amravati District. The ABO locus was found to be less polymorphic when compared with other loci. On the other hand, Rh and sickling loci were found to be more polymorphic. Construction of a dendrogram using allele frequency data reveals an interesting relationship among the caste and tribe. An analysis shows three major clades comprising A, B and C. Clade A comprises Islamic Dawoodi Bohra and Hindu Gujrati. Clade B comprises the upper castes, Brahmin, Jain, Kashmiris and Kunbis, while Clade C shows Gonds and Katchhi. This study is a first attempt to provide a genetic landscape of castes and tribes inhabiting the Vidarbha region. The findings are discussed in light of the historical, anthropological and genetic data available for the studied group
Health spending, illicit financial flows and tax incentives in Malawi
No full textThis analysis examines the gaps in health care financing in Malawi and how foregone taxes could fill these gaps. It begins with an assessment of the disease burden and government health expenditure. Then it analyses the tax revenues foregone by the government of Malawi by two main routes • Illicit financial flows (IFF) from the country • Tax incentives. We find that there are significant financing gaps in the health sector; for example, government expenditure is United States Dollars (USD) 177 million for 2013/2014 while projected donor contribution in 2013/2014 is USD 207 million and the total cost for the minimal health package is USD 535 million. Thus the funding gap between the government budget for health and the required spending to provide the minimal package for 2013/2014 is USD 358 million. On the other hand we estimate that almost USD 400million is lost through IFF and corporate utilization of tax incentives each year. The revenues foregone plus the current government health spending would be sufficient to cover the minimal public health package for all Malawians and would help tackle Malawi’s disease burden. Every effort must be made, including improving transparency and revising laws, to curtail IFF and moderate tax incentives.Peer reviewe
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