scholarly journals Predicting the natural history of metabolic syndrome with a Markov-system dynamic model: a novel approach

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Abbas Rezaianzadeh ◽  
Esmaeil Khedmati Morasae ◽  
Davood Khalili ◽  
Mozhgan Seif ◽  
Ehsan Bahramali ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Natural History ◽  
Markov Model ◽  
Transition Probabilities ◽  
Model Fitting ◽  
System Dynamic ◽  
Markov System ◽  
Novel Approach ◽  
Kolmogorov Smirnov ◽  
Mean Differences

Abstract Background Markov system dynamic (MSD) model has rarely been used in medical studies. The aim of this study was to evaluate the performance of MSD model in prediction of metabolic syndrome (MetS) natural history. Methods Data gathered by Tehran Lipid & Glucose Study (TLGS) over a 16-year period from a cohort of 12,882 people was used to conduct the analyses. First, transition probabilities (TPs) between 12 components of MetS by Markov as well as control and failure rates of relevant interventions were calculated. Then, the risk of developing each component by 2036 was predicted once by a Markov model and then by a MSD model. Finally, the two models were validated and compared to assess their performance and advantages by using mean differences, mean SE of matrices, fit of the graphs, and Kolmogorov-Smirnov two-sample test as well as R2 index as model fitting index. Results Both Markov and MSD models were shown to be adequate for prediction of MetS trends. But the MSD model predictions were closer to the real trends when comparing the output graphs. The MSD model was also, comparatively speaking, more successful in the assessment of mean differences (less overestimation) and SE of the general matrix. Moreover, the Kolmogorov-Smirnov two-sample showed that the MSD model produced equal distributions of real and predicted samples (p = 0.808 for MSD model and p = 0.023 for Markov model). Finally, R2 for the MSD model was higher than Markov model (73% for the Markov model and 85% for the MSD model). Conclusion The MSD model showed a more realistic natural history than the Markov model which highlights the importance of paying attention to this method in therapeutic and preventive procedures.

scholarly journals A Markovian Approach To The Modeling Of Sound Propagation In Urban Streets

2012 ◽  
Author(s):  
Zaiton Haron ◽  
David Oldham
Keyword(s):  
Markov Process ◽  
Markov Model ◽  
Diffuse Reflection ◽  
Sound Propagation ◽  
Transition Probabilities ◽  
Transition Probability ◽  
Multiple Reflections ◽  
Urban Streets ◽  
Novel Approach ◽  
Markovian Approach

Kertas kerja ini menguji kaedah novel, iaitu Markov untuk tujuan simulasi pengorakan bunyi di jalan raya. Kaedah ini menganggap deretan bangunan di tepi jalan menyerap dan memantulkan bunyi secara berserak. Proses simulasi menganggap proses pengorakan bunyi sebagai proses Markov jujukan pertama bercirikan matrix kebarangkalian perpindahan pancaran bunyi di antara permukaan–permukaan. Keputusan simulasi menggunakan kaedah Markov dibandingkan dengan keputusan diperolehi dari model kommersial RAYNOISE dengan menggunakan pilihan pantulan berserak. Hasil keputusan menunjukkan paras tekanan bunyi di jalan raya yang diramal oleh kaedah Markov mempunyai kesepadanan yang baik dengan ramalan diperolehi dari model RAYNOISE. Ini menunjukkan kaedah Markov mempunyai potensi untuk meramal pantulan berganda bagi keadaan sempadan berserak. Kesan agihan serapan permukaan bangunan juga dikaji, dan dengan skop dan anggapan kajian didapati jalan raya yang mempunyai deretan bangunan berpermukaan menyerap bunyi berupaya menghasilkan pengurangan bunyi kurang dari 1 dB. Kata kunci: Pantulan berserak; proses Markov; kebarangkalian perpindahan; pengorakan bunyi; kawalan bunyi bising This paper examined the capability of the novel approach called Markov in the simulation of sound propagation in streets. The approach assumes that the facades lining the streets absorb and reflect sound diffusely. The simulation process treated the sound propagation process as first order Markov process characterised by a matrix of transition probabilities relating to sound radiation between surfaces. The results of simulation using Markov model were compared with the results obtained from a commercial model, RAYNOISE using the diffuse reflection option. The results showed that sound pressure level in a street predicted by the Markov model was in good agreement with predictions obtained using RAYNOISE model. This suggest that the Markov model has the potential to predict multiple reflections for diffuse boundary conditions. The effects of distribution absorption of building facades were also investigated and within the scope and assumptions in this study; it is shown streets with absorbent building facade result in sound reductions typically less than 1 dB. Key words: Diffuse reflection; Markov process; transition probability; sound propagation; noise control

scholarly journals States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model

2021 ◽  
Vol 18 (14) ◽  
pp. 7449
Author(s):  
Juan Xiong ◽  
Qiyu Fang ◽  
Jialing Chen ◽  
Yingxin Li ◽  
Huiyi Li ◽  
...  
Keyword(s):  
Postpartum Depression ◽  
Markov Model ◽  
Normal State ◽  
Sojourn Time ◽  
Transition Probabilities ◽  
Transition Probability ◽  
Public Health Problem ◽  
Mental States ◽  
Hazard Ratio ◽  
Multiple Time

Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natural transition trajectories of PPD has rarely been explored. Methods: In this research, a quantitative longitudinal study was conducted to explore the PPD progression process, providing information on the transition probability, hazard ratio, and the mean sojourn time in the three postnatal mental states, namely normal state, mild PPD, and severe PPD. The multi-state Markov model was built based on 912 depression status assessments in 304 Chinese primiparous women over multiple time points of six weeks postpartum, three months postpartum, and six months postpartum. Results: Among the 608 PPD status transitions from one visit to the next visit, 6.2% (38/608) showed deterioration of mental status from the level at the previous visit; while 40.0% (243/608) showed improvement at the next visit. A subject in normal state who does transition then has a probability of 49.8% of worsening to mild PPD, and 50.2% to severe PPD. A subject with mild PPD who does transition has a 20.0% chance of worsening to severe PPD. A subject with severe PPD is more likely to improve to mild PPD than developing to the normal state. On average, the sojourn time in the normal state, mild PPD, and severe PPD was 64.12, 6.29, and 9.37 weeks, respectively. Women in normal state had 6.0%, 8.5%, 8.7%, and 8.8% chances of progress to severe PPD within three months, nine months, one year, and three years, respectively. Increased all kinds of supports were associated with decreased risk of deterioration from normal state to severe PPD (hazard ratio, HR: 0.42–0.65); and increased informational supports, evaluation of support, and maternal age were associated with alleviation from severe PPD to normal state (HR: 1.46–2.27). Conclusions: The PPD state transition probabilities caused more attention and awareness about the regular PPD screening for postnatal women and the timely intervention for women with mild or severe PPD. The preventive actions on PPD should be conducted at the early stages, and three yearly; at least one yearly screening is strongly recommended. Emotional support, material support, informational support, and evaluation of support had significant positive associations with the prevention of PPD progression transitions. The derived transition probabilities and sojourn time can serve as an importance reference for health professionals to make proactive plans and target interventions for PPD.

A Markov Model of the Natural History of Multiple Sclerosis

1985 ◽  
Vol 4 (4) ◽  
pp. 227-239 ◽  
Author(s):  
Christina Wolfson ◽  
Christian Confavreux
Keyword(s):  
Multiple Sclerosis ◽  
Natural History ◽  
Markov Model ◽  
History Of

scholarly journals Forecasting the Long-Run Behavior of the Stock Price of Some Selected Companies in the Malaysian Construction Sector: A Markov Chain Approach

2020 ◽  
Vol 5 (2) ◽  
pp. 296-308
Author(s):  
Wajeeh Mustafa Sarsour ◽  
Shamsul Rijal Muhammad Sabri
Keyword(s):  
Markov Model ◽  
Stock Prices ◽  
Stock Price ◽  
Transition Probabilities ◽  
Return Time ◽  
Price Increase ◽  
State Model ◽  
Construction Sector ◽  
Long Run ◽  
Three State Model

The fluctuations in stock prices produce a high risk that makes investors uncertain about their investment decisions. The present paper provides a methodology to forecast the long-term behavior of five randomly selected equities operating in the Malaysian construction sector. The method used in this study involves Markov chains as a stochastic analysis, assuming that the price changes have the proparty of Markov dependency with their transition probabilities. We identified a three-state Markov model (i.e., increase, stable, fall) and a two-state Markov model (i.e., increase and fall). The findings suggested that the chains had limiting distributions. The mean return time was computed for respective equities as well as to determine the average duration to return to a stock price increase. The analysis might aid investors in improving their investment knowledge, and they will be able to make better decisions when an equity portfolio possesses higher transition probabilities, higher limiting distribution, and lowest mean return time in response to a price increase. Finally, our investigations suggest that investors are more likely to invest in the GKent based on the three-state model, while VIZIONE seems to be a better investment choice based on a two-state model.

scholarly journals Rhythmic grouping biases in simultaneous bilinguals

2020 ◽  
Vol 23 (5) ◽  
pp. 1070-1081 ◽  
Author(s):  
Natalie Boll-Avetisyan ◽  
Anjali Bhatara ◽  
Annika Unger ◽  
Thierry Nazzi ◽  
Barbara Höhle
Keyword(s):  
Speech Processing ◽  
Model Fitting ◽  
Bimodal Distribution ◽  
Individual Performance ◽  
Special Role ◽  
Language Experience ◽  
Novel Approach ◽  
French Speaking ◽  
German Speaking ◽  
Language Context

AbstractThis study provides a novel approach for testing the universality of perceptual biases by looking at speech processing in simultaneous bilingual adults learning two languages that support the maintenance of this bias to different degrees. Specifically, we investigated the Iambic/Trochaic Law, an assumed universal grouping bias, in simultaneous French–German bilinguals, presenting them with streams of syllables varying in intensity, duration or neither and asking them whether they perceived them as strong-weak or weak-strong groupings. Results showed robust, consistent grouping preferences. A comparison to monolinguals from previous studies revealed that they pattern with German-speaking monolinguals, and differ from French-speaking monolinguals. The distribution of simultaneous bilinguals' individual performance was best explained by a model fitting a unimodal (not bimodal) distribution, failing to support two subgroups of language dominance. Moreover, neither language experience nor language context predicted their performance. These findings suggest a special role for universal biases in simultaneous bilinguals.

A semi-markov model for clinical trials

1965 ◽  
Vol 2 (02) ◽  
pp. 269-285 ◽  
Author(s):  
George H. Weiss ◽  
Marvin Zelen
Keyword(s):  
Clinical Trials ◽  
Probability Distribution ◽  
Acute Leukemia ◽  
Markov Model ◽  
Markov Models ◽  
Transition Probabilities ◽  
State Transitions ◽  
Semi Markov Processes ◽  
Absorbing States ◽  
Epidemic Diseases

This paper applies the theory of semi-Markov processes to the construction of a stochastic model for interpreting data obtained from clinical trials. The model characterizes the patient as being in one of a finite number of states at any given time with an arbitrary probability distribution to describe the length of stay in a state. Transitions between states are assumed to be chosen according to a stationary finite Markov chain.Other attempts have been made to develop stochastic models of clinical trials. However, these have all been essentially Markovian with constant transition probabilities which implies that the distribution of time spent during a visit to a state is exponential (or geometric for discrete Markov chains). Markov models need also to assume that the transitions in the state of a patient depend only on absolute time whereas the semi-Markov model assumes that transitions depend on time relative to a patient. Thus the models are applicable to degenerative diseases (cancer, acute leukemia), while Markov models with time dependent transition probabilities are applicable to colds and epidemic diseases. In this paper the Laplace transforms are obtained for (i) probability of being in a state at timet, (ii) probability distribution to reach absorption state and (iii) the probability distribution of the first passage times to go from initial states to transient or absorbing states, transient to transient, and transient to absorbing. The model is applied to a clinical study of acute leukemia in which patients have been treated with methotrexate and 6-mercaptopurine. The agreement between the data and the model is very good.

scholarly journals Lipid Abnormalities in the Natural History of Diabetes

2015 ◽  
Vol 16 (2) ◽  
pp. 83-88
Author(s):  
Muhammad Hafizur Rahman ◽  
Liaquat Ali
Keyword(s):  
Metabolic Syndrome ◽  
Natural History ◽  
Total Cholesterol ◽  
Fasting Glucose ◽  
Serum Triglyceride ◽  
Hdl Cholesterol ◽  
Family History Of Diabetes ◽  
History Of ◽  
Lipid Abnormalities ◽  
Design And Methods

Objective: To explore lipid abnormalities in normoglycemic first-degree diabetic relatives (FDRs) and prediabetic and diabetic subjects in the natural history of diabetes.Research design and methods: Thirty six impaired fasting glucose (IFG), 61 isolated impaired glucose tolerance (I-IGT), 64 combined IFG-IGT, 73 diabetic, and 32 FDRs along with 57 normoglycemic healthy controls without family history of diabetes in 1st degree relatives, were selected purposively following 2003 ADA cut-off values and 2006 WHO/IDF grouping. Anthropometry and blood pressure of the subjects were taken. Fasting and 2-h plasma glucose and HbA1C were measured. Fasting plasma triglyceride, total cholesterol and HDL cholesterol were measured by enzymatic colorimetric method.Results: Serum triglyceride was higher in IFG, I-IGT, IFG-IGT, diabetic and FDRs compared to Control [145 (59- 307), 128 (66-584), 166 (68-764), 161 (69-750) and 130 (81-281) vs. 108 (47-219) mg/dl, P<0.01, P<0.01, P<0.001, P<0.001 and P<0.05]. Total cholesterol was raised in IFG-IGT and diabetes compared to Control [185 (105-310), 185 (123-326) vs. 171 (101-235) mg/dl, P<0.05] and FDRs. But HDL did not differ among the groups. Prevalence of metabolic syndrome was higher in IFG, I-IGT, IFG-IGT and diabetes and FDRs than Control [55%, 38%, 57%, 58% and 36% vs. 15%, P<0.001, P<0.01, P<0.001, P<0.001 and P<0.05] and also in IFGIGT and diabetic compared to I-IGT and FDRs (P<0.05).Conclusions: Higher prevalence of metabolic syndrome and raised serum triglyceride is seen among diabetic, prediabetic and 1st degree diabetic-relatives. Total cholesterol and non-HDL cholesterol is raised only in IFG-IGT and diabetes, the more decompensated glycemic states.J MEDICINE July 2015; 16 (2) : 83-88

Impact of thiopurines on the natural history and surgical outcome of ulcerative colitis: a cohort study

Gut ◽  
2018 ◽  
Vol 68 (4) ◽  
pp. 623-632 ◽  
Author(s):  
Carl Eriksson ◽  
Sara Rundquist ◽  
Yang Cao ◽  
Scott Montgomery ◽  
Jonas Halfvarson
Keyword(s):  
Ulcerative Colitis ◽  
Natural History ◽  
Hospital Admission ◽  
Cox Regression ◽  
University Hospital ◽  
Cumulative Probability ◽  
Disease Extent ◽  
Novel Approach ◽  
Beneficial Impact

ObjectiveThiopurines are used as maintenance therapy in ulcerative colitis (UC), but whether these drugs influence the natural history of the disease is unknown. We aimed to assess the effect of thiopurines in terms of colectomy, hospital admission, progression in disease extent and anti-tumour necrosis factor (TNF) therapy within 10 years from initiation.DesignPatients diagnosed with UC within the Örebro University Hospital catchment area, during 1963–2010, who initiated thiopurines (n=253) were included. To overcome the risk of confounding by indication, we compared patients who stopped treatment within 12 months because of an adverse reaction (n=76) with patients who continued therapy or discontinued due to other reasons (n=177) and assessed long-term outcomes using Cox regression with adjustment for potential confounding factors.ResultsThe cumulative probability of colectomy within 10 years was 19.5% in tolerant patients compared with 29.0% in intolerant (adjusted HR 0.49; 95% CI 0.21 to 0.73). The probability of hospital admission was 34.0% in tolerant versus 56.2% in intolerant patients (adjusted HR 0.36; 95% CI 0.23 to 0.56). The risk for progression in disease extent was 20.4% in tolerant patients compared with 48.8% in intolerant (adjusted HR 0.47; 95% CI 0.21 to 1.06). Within 10 years, 16.1% of tolerant and 27.5% of intolerant patients received anti-TNF therapy (adjusted HR 0.49; 95% CI 0.26 to 0.92).ConclusionBased on the novel approach of comparing patients tolerant and intolerant to thiopurines, we reveal that thiopurines have a profound beneficial impact of the natural history and long-term colectomy rates of UC.

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