222 research outputs found
Fluctuations and response of nonequilibrium states
A generalized fluctuation-response relation is found for thermal systems
driven out of equilibrium. Its derivation is independent of many details of the
dynamics, which is only required to be first-order. The result gives a
correction to the equilibrium fluctuation-dissipation theorem, in terms of the
correlation between observable and excess in dynamical activity caused by the
perturbation. Previous approaches to this problem are recovered and extended in
a unifying scheme
Entropy and efficiency of a molecular motor model
In this paper we investigate the use of path-integral formalism and the
concepts of entropy and traffic in the context of molecular motors. We show
that together with time-reversal symmetry breaking arguments one can find
bounds on efficiencies of such motors. To clarify this techinque we use it on
one specific model to find both the thermodynamic and the Stokes efficiencies,
although the arguments themselves are more general and can be used on a wide
class of models. We also show that by considering the molecular motor as a
ratchet, one can find additional bounds on the thermodynamic efficiency
Practical guidance for applying the ADNEX model from the IOTA group to discriminate between different subtypes of adnexal tumors.
All gynecologists are faced with ovarian tumors on a regular basis, and the accurate preoperative diagnosis of these masses is important because appropriate management depends on the type of tumor. Recently, the International Ovarian Tumor Analysis (IOTA) consortium published the Assessment of Different NEoplasias in the adneXa (ADNEX) model, the first risk model that differentiates between benign and four types of malignant ovarian tumors: borderline, stage I cancer, stage II-IV cancer, and secondary metastatic cancer. This approach is novel compared to existing tools that only differentiate between benign and malignant tumors, and therefore questions may arise on how ADNEX can be used in clinical practice. In the present paper, we first provide an in-depth discussion about the predictors used in ADNEX and the ability for risk prediction with different tumor histologies. Furthermore, we formulate suggestions about the selection and interpretation of risk cut-offs for patient stratification and choice of appropriate clinical management. This is illustrated with a few example patients. We cannot propose a generally applicable algorithm with fixed cut-offs, because (as with any risk model) this depends on the specific clinical setting in which the model will be used. Nevertheless, this paper provides a guidance on how the ADNEX model may be adopted into clinical practice
The expected value of sample information calculations for external validation of risk prediction models
In designing external validation studies of clinical prediction models,
contemporary sample size calculation methods are based on the frequentist
inferential paradigm. One of the widely reported metrics of model performance
is net benefit (NB), and the relevance of conventional inference around NB as a
measure of clinical utility is doubtful. Value of Information methodology
quantifies the consequences of uncertainty in terms of its impact on clinical
utility of decisions. We introduce the expected value of sample information
(EVSI) for validation as the expected gain in NB from conducting an external
validation study of a given size. We propose algorithms for EVSI computation,
and in a case study demonstrate how EVSI changes as a function of the amount of
current information and future study's sample size. Value of Information
methodology provides a decision-theoretic lens to the process of planning a
validation study of a risk prediction model and can complement conventional
methods when designing such studies.Comment: 14 pages, 4 figures, 0 table
Monotone return to steady nonequilibrium
We propose and analyze a new candidate Lyapunov function for relaxation
towards general nonequilibrium steady states. The proposed functional is
obtained from the large time asymptotics of time-symmetric fluctuations. For
driven Markov jump or diffusion processes it measures an excess in dynamical
activity rates. We present numerical evidence and we report on a rigorous
argument for its monotonous time-dependence close to the steady nonequilibrium
or in general after a long enough time. This is in contrast with the behavior
of approximate Lyapunov functions based on entropy production that when driven
far from equilibrium often keep exhibiting temporal oscillations even close to
stationarity.Comment: Accepted for publication in Phys. Rev. Let
Three myths about risk thresholds for prediction models
Acknowledgments This work was developed as part of the international initiative of strengthening analytical thinking for observational studies (STRATOS). The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies (http://stratos-initiative.org/). Members of the STRATOS Topic Group ‘Evaluating diagnostic tests and prediction models’ are Gary Collins, Carl Moons, Ewout Steyerberg, Patrick Bossuyt, Petra Macaskill, David McLernon, Ben van Calster, and Andrew Vickers. Funding The study is supported by the Research Foundation-Flanders (FWO) project G0B4716N and Internal Funds KU Leuven (project C24/15/037). Laure Wynants is a post-doctoral fellow of the Research Foundation – Flanders (FWO). The funding bodies had no role in the design of the study, collection, analysis, interpretation of data, nor in writing the manuscript. Contributions LW and BVC conceived the original idea of the manuscript, to which ES, MVS and DML then contributed. DT acquired the data. LW analyzed the data, interpreted the results and wrote the first draft. All authors revised the work, approved the submitted version, and are accountable for the integrity and accuracy of the work.Peer reviewedPublisher PD
Current fluctuations in stochastic systems with long-range memory
We propose a method to calculate the large deviations of current fluctuations
in a class of stochastic particle systems with history-dependent rates.
Long-range temporal correlations are seen to alter the speed of the large
deviation function in analogy with long-range spatial correlations in
equilibrium systems. We give some illuminating examples and discuss the
applicability of the Gallavotti-Cohen fluctuation theorem.Comment: 10 pages, 1 figure. v2: Minor alterations. v3: Very minor alterations
for consistency with published version appearing at
http://stacks.iop.org/1751-8121/42/34200
Predicting COVID-19 prognosis in the ICU remained challenging: external validation in a multinational regional cohort
Objective: Many prediction models for Coronavirus Disease 2019 (COVID-19) have been developed. External validation is mandatory before implementation in the Intensive Care Unit (ICU). We selected and validated prognostic models in the Euregio Intensive Care COVID (EICC) cohort.
Study design and setting: In this multinational cohort study, routine data from COVID-19 patients admitted to ICUs within the Euregio Meuse-Rhine were collected from March to August 2020. COVID-19 models were selected based on model type, predictors, outcomes, and reporting. Furthermore, general ICU scores were assessed. Discrimination was assessed by area under the receiver operating characteristic curves (AUCs) and calibration by calibration-in-the-large and calibration plots. A random-effects meta-analysis was used to pool results.
Results: 551 patients were admitted. Mean age was 65.4±11.2 years, 29% were female, and ICU mortality was 36%. Nine out of 238 published models were externally validated. Pooled AUCs were between 0.53 and 0.70 and calibration-in-the-large between -9% and 6%. Calibration plots showed generally poor but, for the 4C Mortality score and SEIMC score, moderate calibration.
Conclusion: Of the nine prognostic models that were externally validated in the EICC cohort, only two showed reasonable discrimination and moderate calibration. For future pandemics, better models based on routine data are needed to support admission decision-making
Monotonicity of the dynamical activity
The Donsker-Varadhan rate function for occupation-time fluctuations has been
seen numerically to exhibit monotone return to stationary nonequilibrium [Phys.
Rev. Lett. 107, 010601 (2011)]. That rate function is related to dynamical
activity and, except under detailed balance, it does not derive from the
relative entropy for which the monotonicity in time is well understood. We give
a rigorous argument that the Donsker-Varadhan function is indeed monotone under
the Markov evolution at large enough times with respect to the relaxation time,
provided that a "normal linear-response" condition is satisfied.Comment: 19 pages, 1 figure; v3: Section I extended, 3 references adde
Characterization of nuclear material by Neutron Resonance Transmission Analysis
The use of Neutron Resonance Transmission Analysis for the
characterization of nuclear materials is discussed. The method, which relies on resonance structures in neutron-induced reaction cross sections, can be applied as a non-destructive method to characterise complex nuclear materials such as melted fuel resulting from a severe nuclear accident. Results of a demonstration experiment at the GELINA facility reveal that accurate data can be obtained at a compact facility even in the case of strong overlapping resonances
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