Fair processes for priority setting: Putting theory into practice: Comment on “expanded HTA: Enhancing fairness and legitimacy”

Embedding health technology assessment (HTA) in a fair process has great potential to capture societal values relevant to public reimbursement decisions on health technologies. However, the development of such processes for priority setting has largely been theoretical. In this paper, we provide further practical lead ways on how these processes can be implemented. We first present the misconception about the relation between facts and values that is since long misleading the conduct of HTA and underlies the current assessment-appraisal split. We then argue that HTA should instead be explicitly organized as an ongoing evidence-informed deliberative process, that facilitates learning among stakeholders. This has important consequences for whose values to consider, how to deal with vested interests, how to consider all values in the decision-making process, and how to communicate decisions. This is in stark contrast to how HTA processes are implemented now. It is time to set the stage for HTA as learning

Before sailing on a domain-wall sea

We discuss the very different roles of the valence-quark and the sea-quark residual masses ($m_{res}^v$ and $m_{res}^s$) in dynamical domain-wall fermions simulations. Focusing on matrix elements of the effective weak hamiltonian containing a power divergence, we find that $m_{res}^v$ can be a source of a much bigger systematic error. To keep all systematic errors due to residual masses at the 1% level, we estimate that one needs $a m_{res}^s \le 10^{-3}$ and $a m_{res}^v \le 10^{-5}$, at a lattice spacing $a\sim 0.1$ fm. The practical implications are that (1) optimal use of computer resources calls for a mixed scheme with different domain-wall fermion actions for the valence and sea quarks; (2) better domain-wall fermion actions are needed for both the sea and the valence sectors.Comment: latex, 25 pages. Improved discussion in appendix, including correction of some technical mistakes; ref. adde

Fair Processes for Priority Setting: Putting Theory into Practice Comment on “Expanded HTA: Enhancing Fairness and Legitimacy”

Embedding health technology assessment (HTA) in a fair process has great potential to capture societal values relevant to public reimbursement decisions on health technologies. However, the development of such processes for priority setting has largely been theoretical. In this paper, we provide further practical lead ways on how these processes can be implemented. We first present the misconception about the relation between facts and values that is since long misleading the conduct of HTA and underlies the current assessmentappraisal split. We then argue that HTA should instead be explicitly organized as an ongoing evidenceinformed deliberative process, that facilitates learning among stakeholders. This has important consequences for whose values to consider, how to deal with vested interests, how to consider all values in the decisionmaking process, and how to communicate decisions. This is in stark contrast to how HTA processes are implemented now. It is time to set the stage for HTA as learnin

Priority setting for universal health coverage: We need evidence-informed deliberative processes, not just more evidence on cost-effectiveness

Priority setting of health interventions is generally considered as a valuable approach to support low- and middle-income countries (LMICs) in their strive for universal health coverage (UHC). However, present initiatives on priority setting are mainly geared towards the development of more cost-effectiveness information, and this evidence does not sufficiently support countries to make optimal choices. The reason is that priority setting is in reality a value-laden political process in which multiple criteria beyond cost-effectiveness are important, and stakeholders often justifiably disagree about the relative importance of these criteria. Here, we propose the use of ‘evidence-informed deliberative processes’ as an approach that does explicitly recognise priority setting as a political process and an intrinsically complex task. In these processes, deliberation between stakeholders is crucial to identify, reflect and learn about the meaning and importance of values, informed by evidence on these values. Such processes then result in the use of a broader range of explicit criteria that can be seen as the product of both international learning (‘core’ criteria, which include eg, cost-effectiveness, priority to the worse off, and financial protection) and learning among local stakeholders (‘contextual’ criteria). We believe that, with these evidence-informed deliberative processes in place, priority setting can provide a more meaningful contribution to achieving UHC

О нижней оценке для одной квадратичной задачи намногообразии Штифеля

Despite technological advances in metabolomics, large parts of the human metabolome are still unexplored. In an untargeted metabolomics screen aiming to identify substrates of the orphan transporter ATP-binding cassette subfamily C member 5 (ABCC5), we identified a class of mammalian metabolites, N-lactoyl-amino acids. Using parallel protein fractionation in conjunction with shotgun proteomics on fractions containing N-lactoyl-Phe-forming activity, we unexpectedly found that a protease, cytosolic nonspecific dipeptidase 2 (CNDP2), catalyzes their formation. N-lactoyl-amino acids are ubiquitous pseudodipeptides of lactic acid and amino acids that are rapidly formed by reverse proteolysis, a process previously considered to be negligible in vivo. The plasma levels of these metabolites strongly correlate with plasma levels of lactate and amino acid, as shown by increased levels after physical exercise and in patients with phenylketonuria who suffer from elevated Phe levels. Our approach to identify unknown metabolites and their biosynthesis has general applicability in the further exploration of the human metabolome

A review of machine learning applications for the proton MR spectroscopy workflow

This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured overview of the state-of-the-art methods. Specifically, we examine and summarize studies published between 2017 and 2023 from major journals in the MR field. We categorize these studies based on a typical MRS workflow, including data acquisition, processing, analysis, and artificial data generation. Our review reveals that ML in MRS is still in its early stages, with a primary focus on processing and analysis techniques, and less attention given to data acquisition. We also found that many studies use similar model architectures, with little comparison to alternative architectures. Additionally, the generation of artificial data is a crucial topic, with no consistent method for its generation. Furthermore, many studies demonstrate that artificial data suffers from generalization issues when tested on in vivo data. We also conclude that risks related to ML models should be addressed, particularly for clinical applications. Therefore, output uncertainty measures and model biases are critical to investigate. Nonetheless, the rapid development of ML in MRS and the promising results from the reviewed studies justify further research in this field.</p

Pathologically confirmed autoimmune encephalitis in suspected Creutzfeldt-Jakob disease

Objective: To determine the clinical features and presence in CSF of antineuronal antibodies in patients with pathologically proven autoimmune encephalitis derived from a cohort of patients with suspected Creutzfeldt-Jakob disease (CJD). Methods: The Dutch Surveillance Centre for Prion Diseases performed 384 autopsies on patients with suspected CJD over a 14-year period (1998-2011). Clinical information was collected from treating physicians. Antineuronal antibodies were tested in CSF obtained postmortem by immunohistochemistry on fresh frozen rat brain sections, by Luminex assay for the presence of wellcharacterized onconeural antibodies, and by cell-based assays for antibodies against NMDAR, GABABR1/2, GABAAR GLUR1/2, LGI1, Caspr2, and DPPX. Results: In 203 patients, a diagnosis of definite CJD was made, while in 181 a variety of other conditions were diagnosed, mainly neurodegenerative. In 22 of these 181, the neuropathologist diagnosed autoimmune encephalitis. One patient was excluded because of lack of clinical information. Inflammator

Investigation of the Domain Wall Fermion Approach to Chiral Gauge Theories on the Lattice

We investigate a recent proposal to construct chiral gauge theories on the lattice using domain wall fermions. We restrict ourselves to the finite volume case, in which two domain walls are present, with modes of opposite chirality on each of them. We couple the chiral fermions on only one of the domain walls to a gauge field. In order to preserve gauge invariance, we have to add a scalar field, which gives rise to additional light mirror fermion and scalar modes. We argue that in an anomaly free model these extra modes would decouple if our model possesses a so-called strong coupling symmetric phase. However, our numerical results indicate that such a phase most probably does not exist. ---- Note: 9 Postscript figures are appended as uuencoded compressed tar file.Comment: 27p. Latex; UCSD/PTH 93-28, Wash. U. HEP/93-6