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1.
PLoS One ; 15(10): e0239960, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33017421

RESUMO

The outbreak of Corona Virus Disease 2019 (COVID-19) in Wuhan has significantly impacted the economy and society globally. Countries are in a strict state of prevention and control of this pandemic. In this study, the development trend analysis of the cumulative confirmed cases, cumulative deaths, and cumulative cured cases was conducted based on data from Wuhan, Hubei Province, China from January 23, 2020 to April 6, 2020 using an Elman neural network, long short-term memory (LSTM), and support vector machine (SVM). A SVM with fuzzy granulation was used to predict the growth range of confirmed new cases, new deaths, and new cured cases. The experimental results showed that the Elman neural network and SVM used in this study can predict the development trend of cumulative confirmed cases, deaths, and cured cases, whereas LSTM is more suitable for the prediction of the cumulative confirmed cases. The SVM with fuzzy granulation can successfully predict the growth range of confirmed new cases and new cured cases, although the average predicted values are slightly large. Currently, the United States is the epicenter of the COVID-19 pandemic. We also used data modeling from the United States to further verify the validity of the proposed models.


Assuntos
Infecções por Coronavirus/epidemiologia , Modelos Teóricos , Pneumonia Viral/epidemiologia , Probabilidade , Máquina de Vetores de Suporte , China/epidemiologia , Previsões , Lógica Fuzzy , Humanos , Redes Neurais de Computação , Pandemias , Estados Unidos/epidemiologia
2.
J Chem Phys ; 153(11): 114119, 2020 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-32962383

RESUMO

The complexity associated with an epidemic defies any quantitatively reliable predictive theoretical scheme. Here, we pursue a generalized mathematical model and cellular automata simulations to study the dynamics of infectious diseases and apply it in the context of the COVID-19 spread. Our model is inspired by the theory of coupled chemical reactions to treat multiple parallel reaction pathways. We essentially ask the question: how hard could the time evolution toward the desired herd immunity (HI) be on the lives of people? We demonstrate that the answer to this question requires the study of two implicit functions, which are determined by several rate constants, which are time-dependent themselves. Implementation of different strategies to counter the spread of the disease requires a certain degree of a quantitative understanding of the time-dependence of the outcome. Here, we compartmentalize the susceptible population into two categories, (i) vulnerables and (ii) resilients (including asymptomatic carriers), and study the dynamical evolution of the disease progression. We obtain the relative fatality of these two sub-categories as a function of the percentages of the vulnerable and resilient population and the complex dependence on the rate of attainment of herd immunity. We attempt to study and quantify possible adverse effects of the progression rate of the epidemic on the recovery rates of vulnerables, in the course of attaining HI. We find the important result that slower attainment of the HI is relatively less fatal. However, slower progress toward HI could be complicated by many intervening factors.


Assuntos
Doenças Transmissíveis/imunologia , Doenças Transmissíveis/patologia , Imunidade Coletiva , Modelos Teóricos , Controle de Doenças Transmissíveis , Humanos , Modelos Biológicos , Probabilidade , Processos Estocásticos
3.
Phys Biol ; 17(6): 065001, 2020 09 22.
Artigo em Inglês | MEDLINE | ID: mdl-32959788

RESUMO

Epidemiological models usually contain a set of parameters that must be adjusted based on available observations. Once a model has been calibrated, it can be used as a forecasting tool to make predictions and to evaluate contingency plans. It is customary to employ only point estimators of model parameters for such predictions. However, some models may fit the same data reasonably well for a broad range of parameter values, and this flexibility means that predictions stemming from them will vary widely, depending on the particular values employed within the range that gives a good fit. When data are poor or incomplete, model uncertainty widens further. A way to circumvent this problem is to use Bayesian statistics to incorporate observations and use the full range of parameter estimates contained in the posterior distribution to adjust for uncertainties in model predictions. Specifically, given an epidemiological model and a probability distribution for observations, we use the posterior distribution of model parameters to generate all possible epidemic curves, whose information is encapsulated in posterior predictive distributions. From these, one can extract the worst-case scenario and study the impact of implementing contingency plans according to this assessment. We apply this approach to the evolution of COVID-19 in Mexico City and assess whether contingency plans are being successful and whether the epidemiological curve has flattened.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Epidemias , Pneumonia Viral/epidemiologia , Teorema de Bayes , Infecções por Coronavirus/mortalidade , Bases de Dados Factuais , Epidemias/estatística & dados numéricos , Humanos , Conceitos Matemáticos , México/epidemiologia , Modelos Biológicos , Modelos Estatísticos , Pandemias , Pneumonia Viral/mortalidade , Probabilidade , Fatores de Tempo , Incerteza
4.
Rev Peru Med Exp Salud Publica ; 37(2): 195-202, 2020.
Artigo em Espanhol, Inglês | MEDLINE | ID: mdl-32876206

RESUMO

OBJECTIVES: To determine the probability of controlling the outbreak of COVID-19 in Peru, in a pre- and post-quarantine scenario using mathematical simulation models. MATERIALS AND METHODS: Outbreak si mulations for the COVID-19 pandemic are performed, using stochastic equations under the following assumptions: a pre-quarantine population R0 of 2.7 or 3.5, a post-quarantine R0 of 1.5, 2 or 2.7, 18% or 40%, of asymptomatic positives and a maximum response capacity of 50 or 150 patients in the intensive care units. The success of isolation and contact tracing is evaluated, no other mitigation measures are included. RESULTS: In the pre-quarantine stage, success in controlling more than 80% of the simulations occurred only if the isolation of positive cases was implemented from the first case, after which there was less than 40% probability of success. In post-quarantine, with 60 positive cases it is necessary to isolate them early, track all of their contacts and decrease the R0 to 1.5 for outbreak control to be successful in more than 80% of cases. Other scenarios have a low probability of success. CONCLUSIONS: The control of the outbreak in Peru during pre-quarantine stage demanded requirements that were difficult to comply with, therefore quarantine was necessary; to successfully suspend it would require a significant reduction in the spread of the disease, early isolation of positives and follow-up of all contacts of positive patients.


Assuntos
Simulação por Computador , Infecções por Coronavirus/epidemiologia , Surtos de Doenças/prevenção & controle , Pneumonia Viral/epidemiologia , Busca de Comunicante/métodos , Infecções por Coronavirus/prevenção & controle , Humanos , Unidades de Terapia Intensiva/estatística & dados numéricos , Modelos Teóricos , Pandemias/prevenção & controle , Peru/epidemiologia , Pneumonia Viral/prevenção & controle , Probabilidade , Quarentena
5.
Medicine (Baltimore) ; 99(33): e21085, 2020 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-32871979

RESUMO

The lymph nodal invasion diagnosis is critical for therapeutic-decision and follows up in gastric cancer. However, the number of nodes to be examined for nodal invasion diagnosis is still under controversy, and the model for quantifying risk of missing positive node is currently not reported yet. We analyzed the nodal invasion status of 13,857 gastric cancer samples with records of primary tumor stage, the number of examined and positive lymph nodes in the surveillance, epidemiology, and end results (SEER) database, fitting a beta-binomial model. The nodes need to be examined with different primary tumor stage were determined based on the model. Overall, examining 11 lymph nodes reduces the probability of missing positive nodes to <10%, and the currently median nodes dissected is adequate (12 nodes). While the number of nodes demands to be dissected for T1, T2, T3, and T4 subgroups are 6, 19, 40, and 66, respectively. The currently implemented median value for these samples was 12, 12, 13, and 16, separately. It implies that the number of nodes to be examined is sufficient for early gastric cancer (T1), but it is inadequate for middle and advanced gastric cancer (T2-T3). The clinical significance of nodal staging score was validated with survival information. In summary, we first quantified the lymph nodes to be examined during surgery using a beta-binomial model, and validated with survival information.


Assuntos
Linfonodos/patologia , Metástase Linfática/diagnóstico , Metástase Linfática/patologia , Estadiamento de Neoplasias/métodos , Neoplasias Gástricas/diagnóstico , Neoplasias Gástricas/patologia , Reações Falso-Negativas , Feminino , Humanos , Linfonodos/cirurgia , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Probabilidade , Estudos Retrospectivos , Programa de SEER , Sensibilidade e Especificidade , Neoplasias Gástricas/epidemiologia , Neoplasias Gástricas/cirurgia , Análise de Sobrevida
6.
Nat Commun ; 11(1): 4575, 2020 09 11.
Artigo em Inglês | MEDLINE | ID: mdl-32917868

RESUMO

A central issue in drug risk-benefit assessment is identifying frequencies of side effects in humans. Currently, frequencies are experimentally determined in randomised controlled clinical trials. We present a machine learning framework for computationally predicting frequencies of drug side effects. Our matrix decomposition algorithm learns latent signatures of drugs and side effects that are both reproducible and biologically interpretable. We show the usefulness of our approach on 759 structurally and therapeutically diverse drugs and 994 side effects from all human physiological systems. Our approach can be applied to any drug for which a small number of side effect frequencies have been identified, in order to predict the frequencies of further, yet unidentified, side effects. We show that our model is informative of the biology underlying drug activity: individual components of the drug signatures are related to the distinct anatomical categories of the drugs and to the specific drug routes of administration.


Assuntos
Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Aprendizado de Máquina , Algoritmos , Biologia Computacional/métodos , Bases de Dados de Produtos Farmacêuticos , Humanos , Preparações Farmacêuticas/administração & dosagem , Probabilidade
7.
BMC Infect Dis ; 20(1): 598, 2020 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-32791999

RESUMO

BACKGROUND: The emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China, at the end of 2019 has caused widespread transmission around the world. As new epicentres in Europe and America have arisen, of particular concern is the increased number of imported coronavirus disease 2019 (COVID-19) cases in Africa, where the impact of the pandemic could be more severe. We aim to estimate the number of COVID-19 cases imported from 12 major epicentres in Europe and America to each African country, as well as the probability of reaching 10,000 cases in total by the end of March, April, May, and June following viral introduction. METHODS: We used the reported number of cases imported from the 12 major epicentres in Europe and America to Singapore, as well as flight data, to estimate the number of imported cases in each African country. Under the assumption that Singapore has detected all the imported cases, the estimates for Africa were thus conservative. We then propagated the uncertainty in the imported case count estimates to simulate the onward spread of the virus, until 10,000 cases are reached or the end of June, whichever is earlier. Specifically, 1,000 simulations were run separately under four different combinations of parameter values to test the sensitivity of our results. RESULTS: We estimated Morocco, Algeria, South Africa, Egypt, Tunisia, and Nigeria as having the largest number of COVID-19 cases imported from the 12 major epicentres. Based on our 1,000 simulation runs, Morocco and Algeria's estimated probability of reaching 10,000 cases by end of March was close to 100% under all scenarios. In particular, we identified countries with less than 1,000 cases in total reported by end of June whilst the estimated probability of reaching 10,000 cases by then was higher than 50% even under the most optimistic scenario. CONCLUSIONS: Our study highlights particular countries that are likely to reach (or have reached) 10,000 cases far earlier than the reported data suggest, calling for the prioritization of resources to mitigate the further spread of the epidemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , África/epidemiologia , Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/virologia , Humanos , Modelos Estatísticos , Pandemias , Pneumonia Viral/virologia , Probabilidade
9.
HNO ; 68(9): 640-647, 2020 Sep.
Artigo em Alemão | MEDLINE | ID: mdl-32780222

RESUMO

BACKGROUND: Radiotherapy (RT) is an integral part of the treatment of many tumors located in the vicinity of sensitive organs and structures, including tumors of the head and neck and base of skull in particular. Due to the risk of side effects associated with RT, the use of highly conformal RT techniques is favored. For many indications, proton therapy (PT) is therefore already part of the modern treatment standard. OBJECTIVE: This article presents an overview of current indications for PT with emphasis on tumors in the head and neck region and the base of skull. Furthermore, a summary and discussion of relevant results and current developments are included. MATERIALS AND METHODS: The work comprises an evaluation of relevant studies and an overview of current issues related to PT of tumors in the areas of the head, neck, and base of skull. RESULTS: Overall, the studies on PT show promising results. In addition to dosimetric studies, clinical studies also point to advantages of PT, especially with regard to the reduction of side effects. DISCUSSION: Currently, use of the model-based approach is being discussed. This is intended to identify those patients who benefit most from PT based on the normal tissue complication probability (NTCP). PT for re-RT is also discussed.


Assuntos
Neoplasias de Cabeça e Pescoço , Terapia com Prótons , Neoplasias da Base do Crânio , Neoplasias de Cabeça e Pescoço/terapia , Humanos , Probabilidade , Dosagem Radioterapêutica , Base do Crânio
10.
Braz Oral Res ; 34 Suppl 2: e078, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32785486

RESUMO

Physicians and dentists usually make clinical decisions and recommendations without a clear understanding of the meaning of the numbers regarding the accuracy of diagnostic tests and the efficacy of treatments. This critical review aimed to identify problems in the communication of diagnostic test accuracy and treatment benefits and to suggest strategies to improve risk communication in these contexts. Most clinical decisions are taken under uncertainty. Health professionals cannot predict the outcome in one individual patient. This uncertainty invites these professionals to make decisions based on heuristics, which gives rise to several cognitive biases. Cognitive biases are automatic and unconscious, so how is it possible to mitigate their undesirable effects on risk interpretation in the context of clinical practice? Some forms of risk communication reinforce cognitive bias, while others weaken them. Maybe one of the most difficult obstacles to overcome is the difficulty to think with numbers. This difficulty probably arises from a mismatch of ancestral adaptations of the brain having to deal with modern environments, which are quite different from the ancestral ones. There are two quite common, but bad, forms of risk communication: the conditional probability and the relative risk reduction or efficacy. People, including physicians and dentists, are confused with this kind of information. The main methods discovered so far to facilitate a clearer understanding are to emphasize the base rates of the events and to use absolute numbers, that is to use natural frequencies, instead of percentages and conditional probabilities.


Assuntos
Comunicação , Viés , Humanos , Probabilidade
12.
PLoS One ; 15(8): e0236553, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32756597

RESUMO

OBJECTIVES: The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necessity of developing a clinical decision support system (CDSS) employing AI. Therefore, in this study, we proposed a "Dr. Answer" AI software based on the clinical outcome prediction model for prostate cancer treated with radical prostatectomy. METHODS: The Dr. Answer AI was developed based on a clinical outcome prediction model, with a user-friendly interface. We used 7,128 clinical data of prostate cancer treated with radical prostatectomy from three hospitals. An outcome prediction model was developed to calculate the probability of occurrence of 1) tumor, node, and metastasis (TNM) staging, 2) extracapsular extension, 3) seminal vesicle invasion, and 4) lymph node metastasis. Random forest and k-nearest neighbors algorithms were used, and the proposed system was compared with previous algorithms. RESULTS: Random forest exhibited good performance for TNM staging (recall value: 76.98%), while k-nearest neighbors exhibited good performance for extracapsular extension, seminal vesicle invasion, and lymph node metastasis (80.24%, 98.67%, and 95.45%, respectively). The Dr. Answer AI software consisted of three primary service structures: 1) patient information, 2) clinical outcome prediction, and outcomes according to the National Comprehensive Cancer Network guideline. CONCLUSION: The proposed clinical outcome prediction model could function as an effective CDSS, supporting the decisions of the physicians, while enabling the patients to understand their treatment outcomes. The Dr. Answer AI software for prostate cancer helps the doctors to explain the treatment outcomes to the patients, allowing the patients to be more confident about their treatment plans.


Assuntos
Inteligência Artificial , Sistemas de Apoio a Decisões Clínicas , Prognóstico , Neoplasias da Próstata/epidemiologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Humanos , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Invasividade Neoplásica/genética , Probabilidade , Próstata/patologia , Próstata/cirurgia , Antígeno Prostático Específico/sangue , Prostatectomia , Neoplasias da Próstata/sangue , Neoplasias da Próstata/fisiopatologia , Neoplasias da Próstata/terapia , Glândulas Seminais/patologia , Glândulas Seminais/cirurgia , Resultado do Tratamento
13.
Nature ; 584(7821): 393-397, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32814886

RESUMO

The rate of global-mean sea-level rise since 1900 has varied over time, but the contributing factors are still poorly understood1. Previous assessments found that the summed contributions of ice-mass loss, terrestrial water storage and thermal expansion of the ocean could not be reconciled with observed changes in global-mean sea level, implying that changes in sea level or some contributions to those changes were poorly constrained2,3. Recent improvements to observational data, our understanding of the main contributing processes to sea-level change and methods for estimating the individual contributions, mean another attempt at reconciliation is warranted. Here we present a probabilistic framework to reconstruct sea level since 1900 using independent observations and their inherent uncertainties. The sum of the contributions to sea-level change from thermal expansion of the ocean, ice-mass loss and changes in terrestrial water storage is consistent with the trends and multidecadal variability in observed sea level on both global and basin scales, which we reconstruct from tide-gauge records. Ice-mass loss-predominantly from glaciers-has caused twice as much sea-level rise since 1900 as has thermal expansion. Mass loss from glaciers and the Greenland Ice Sheet explains the high rates of global sea-level rise during the 1940s, while a sharp increase in water impoundment by artificial reservoirs is the main cause of the lower-than-average rates during the 1970s. The acceleration in sea-level rise since the 1970s is caused by the combination of thermal expansion of the ocean and increased ice-mass loss from Greenland. Our results reconcile the magnitude of observed global-mean sea-level rise since 1900 with estimates based on the underlying processes, implying that no additional processes are required to explain the observed changes in sea level since 1900.


Assuntos
Temperatura Alta , Camada de Gelo/química , Água do Mar/análise , Água do Mar/química , Monitoramento Ambiental , Aquecimento Global/estatística & dados numéricos , Groenlândia , História do Século XX , História do Século XXI , Probabilidade , Incerteza
14.
Value Health ; 23(8): 1049-1055, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32828217

RESUMO

OBJECTIVES: Using an example of an existing model constructed by the National Institute for Health and Care Excellence (NICE) to inform a real health technology assessment, this study seeks to demonstrate how a discretely integrated condition event (DICE) simulation can improve the implementation of Markov models. METHODS: Using the technical report and spreadsheet, the original model was translated to a standard DICE simulation without making any changes to the design. All original analyses were repeated and the results were compared. Aspects that could have improved the original design were then considered. RESULTS: The original model consisted of 32 copies (8 risk strata × 4 treatments) of the Markov structure, containing more than 6000 Microsoft Excel® formulas (18 MB files). Three aspects (nonadherence, scheduled treatment stop, and end of fracture risk) were handled by incorporating weighted averages into the cycle-specific calculations. The DICE implementation used 3 conditions to represent the states and a single transition event to apply the probabilities; 3 additional events processed the special aspects, and profiles handled the 8 strata (0.12 MB file). One replication took 16 seconds. The original results were reproduced but extensive additional sensitivity analyses, including structural analyses, were enabled. CONCLUSION: Implementing a real Markov model using DICE simulation both preserves the advantages of the approach and expands the available tools, improving transparency and ease of use and review.


Assuntos
Simulação por Computador , Cadeias de Markov , Modelos Estatísticos , Avaliação da Tecnologia Biomédica/organização & administração , Técnicas de Apoio para a Decisão , Humanos , Probabilidade
15.
PLoS One ; 15(8): e0237255, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32764804

RESUMO

In this study, washing tests were performed using samples prepared by contaminating fabrics with hemoglobin, and a kinetic analysis was conducted based the probability density functional method, which expresses the cleaning power using two parameters σrl (related to the cleaning mechanism) and µrl (related to the level of cleaning power). This method allows for the processing of uncertainties specific to protein washing under the assumption that the soil adhesion and detergency are in accordance with a normal distribution. A certain amount of hemoglobin solution was soaked in a cloth, dried, and steam-treated, and then used as a sample for a cleaning test. Two parameters σrl and µrl were calculated based on the detergency (%) after 5 min, 10 min, 15 min, and 20 min of washing with respect to different pH and temperature levels, and different sodium dodecyl sulfate (SDS) concentration and temperature levels. Based on the results, the value of σrl indicated that the hemoglobin was removed by the dissolving action. In addition, µrl increased in accordance with an increase in the pH, SDS concentration, and temperature. With respect to µrl, the relationship of ΔX + ΔY = Δ(X+Y) was observed in several cases, where ΔX represents the effect of the pH or SDS concentration, ΔY is the temperature effect, and Δ(X+Y) is the combined effect. Therefore, there may be an additive relationship between the pH and temperature effects, and the SDS concentration and temperature effects.


Assuntos
Detergentes/química , Hemoglobinas/análise , Dodecilsulfato de Sódio/química , Têxteis/análise , Humanos , Concentração de Íons de Hidrogênio , Cinética , Probabilidade , Solubilidade , Temperatura
16.
PLoS One ; 15(8): e0237880, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32813749

RESUMO

OBJECTIVES: To analyse the use of polymyxins for the treatment of ventilator-associated pneumonia (VAP) at a teaching hospital where carbapenem-resistant gram-negative bacteria are endemic. PATIENTS AND METHODS: This was a historical cohort study of patients receiving polymyxins to treat VAP in ICUs at a public university hospital in southern Brazil between January 1, 2017 and January 31, 2018. RESULTS: During the study period, 179 cases of VAP were treated with polymyxins. Of the 179 patients, 158 (88.3%) were classified as having chronic critical illness. Death occurred in 145 cases (81.0%). Multivariate analysis showed that the factors independently associated with mortality were the presence of comorbidities (P<0.001) and the SOFA score of the day of polymyxin prescription (P<0.001). Being a burn patient was a protective factor for mortality (P<0.001). Analysis of the 14-day survival probability showed that mortality was higher among the patients who had sepsis or septic shock at the time of polymyxin prescription (P = 0.028 and P<0.001, respectively). Acinetobacter baumannii was identified as the etiological agent of VAP in 121 cases (67.6%). In our cohort, polymyxin consumption and the incidence density of VAP were quite high. CONCLUSIONS: In our study, comprised primarily of chronically critically ill patients, there was a high prevalence of VAP caused by multidrug-resistant bacteria, consistent with healthcare-associated infections in low- and middle-income countries. Presence of comorbidities and the SOFA score at the time of polymyxin prescription were predictors of mortality in this cohort. Despite aggressive antimicrobial treatment, mortality was high, stressing the need for antibiotic stewardship.


Assuntos
Carbapenêmicos/uso terapêutico , Farmacorresistência Bacteriana Múltipla , Pneumonia Associada à Ventilação Mecânica/tratamento farmacológico , Pneumonia Associada à Ventilação Mecânica/microbiologia , Polimixinas/uso terapêutico , Adulto , Idoso , Feminino , Mortalidade Hospitalar , Humanos , Incidência , Unidades de Terapia Intensiva , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Pneumonia Associada à Ventilação Mecânica/mortalidade , Probabilidade , Análise de Sobrevida , Fatores de Tempo
17.
PLoS One ; 15(8): e0236957, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32764769

RESUMO

OBJECTIVES: Compared with unaffected individuals, patients with type 2 diabetes (T2DM) have higher risk of hypertension, and diabetes combined with hypertension can lead to server cardiovascular disease. Therefore, the purpose of this study was to establish a simple nomogram model to identify the determinants of hypertension in patients with T2DM and to quickly calculate the probability of hypertension in individuals with T2DM. MATERIALS AND METHODS: A total of 643,439 subjects participating in the national physical examination has been recruited in this cross-sectional study. After excluding unqualified subjects, 30,507 adults with T2DM were included in the final analysis. 21,355 and 9,152 subjects were randomly assigned to the model developing group and validation group, respectively, with a ratio of 7:3. The potential risk factors used in this study to assess hypertension in patients with T2DM included questionnaire investigation and physical measurement variables. We used the least absolute shrinkage and selection operator models to optimize feature selection, and the multivariable logistic regression analysis was for predicting model. Discrimination and calibration were assessed using the receiver operating curve (ROC) and calibration curve. RESULTS: The results showed that the major determinants of hypertension in patients with T2DM were age, gender, drinking, exercise, smoking, obesity and atherosclerotic vascular disease. The area under ROC curve of developing group and validation group are both 0.814, indicating that the prediction model owns high disease recognition ability. The p values of the two calibration curves are 0.625 and 0.445, suggesting that the nomogram gives good calibration. CONCLUSION: The individualized nomogram model can facilitate improved screening and early identification of patients with hypertension in T2DM. This procedure will be useful in developing regions with high epidemiological risk and poor socioeconomic status just like Urumqi, in Northern China.


Assuntos
Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/epidemiologia , Hipertensão/complicações , Hipertensão/epidemiologia , Adulto , Idoso , Idoso de 80 Anos ou mais , China/epidemiologia , Estudos Transversais , Feminino , Humanos , Masculino , Programas de Rastreamento , Pessoa de Meia-Idade , Nomogramas , Probabilidade , Prognóstico , Fatores de Risco , Inquéritos e Questionários , Adulto Jovem
18.
J R Soc Interface ; 17(168): 20200144, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32693748

RESUMO

A novel coronavirus (SARS-CoV-2) emerged as a global threat in December 2019. As the epidemic progresses, disease modellers continue to focus on estimating the basic reproductive number [Formula: see text]-the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modelling approaches and resulting estimates of [Formula: see text] during the beginning of the outbreak vary widely, despite relying on similar data sources. Here, we present a statistical framework for comparing and combining different estimates of [Formula: see text] across a wide range of models by decomposing the basic reproductive number into three key quantities: the exponential growth rate, the mean generation interval and the generation-interval dispersion. We apply our framework to early estimates of [Formula: see text] for the SARS-CoV-2 outbreak, showing that many [Formula: see text] estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of [Formula: see text], including the shape of the generation-interval distribution, in efforts to estimate [Formula: see text] at the outset of an epidemic.


Assuntos
Número Básico de Reprodução , Betacoronavirus , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Surtos de Doenças , Modelos Biológicos , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Número Básico de Reprodução/estatística & dados numéricos , Teorema de Bayes , China/epidemiologia , Surtos de Doenças/estatística & dados numéricos , Epidemias/estatística & dados numéricos , Humanos , Cadeias de Markov , Método de Monte Carlo , Pandemias , Probabilidade , Incerteza
19.
JAMA ; 324(3): 270-278, 2020 07 21.
Artigo em Inglês | MEDLINE | ID: mdl-32692387

RESUMO

Importance: Philanthropy is an increasingly important source of support for health care institutions. There is little empirical evidence to inform ethical guidelines. Objective: To assess public attitudes regarding specific practices used by health care institutions to encourage philanthropic donations from grateful patients. Design, Setting, and Participants: Using the Ipsos KnowledgePanel, a probability-based sample representative of the US population, a survey solicited opinions from a primary cohort representing the general population and 3 supplemental cohorts (with high income, cancer, and with heart disease, respectively). Exposures: Web-based questionnaire. Main Outcomes and Measures: Descriptive analyses (with percentages weighted to make the sample demographically representative of the US population) evaluated respondents' attitudes regarding the acceptability of strategies hospitals may use to identify, solicit, and thank donors; perceptions of the effect of physicians discussing donations with their patients; and opinions regarding gift use and stewardship. Results: Of 831 individuals targeted for the general population sample, 513 (62%) completed surveys, of whom 246 (48.0%) were women and 345 (67.3%) non-Hispanic white. In the weighted sample, 47.0% (95% CI, 42.3%-51.7%) responded that physicians giving patient names to hospital fundraising staff after asking patients' permission was definitely or probably acceptable; 8.5% (95% CI, 5.7%-11.2%) endorsed referring without asking permission. Of the participants, 79.5% (95% CI, 75.6%-83.4%) reported it acceptable for physicians to talk to patients about donating if patients have brought it up; 14.2% (95% CI, 10.9%-17.6%) reported it acceptable when patients have not brought it up; 9.9% (95% CI, 7.1%-12.8%) accepted hospital development staff performing wealth screening using publicly available data to identify patients capable of large donations. Of the participants, 83.2% (95% CI, 79.5%-86.9%) agreed that physicians talking with their patients about donating may interfere with the patient-physician relationship. For a hypothetical patient who donated $1 million, 50.1% (95% CI, 45.4%-54.7%) indicated it would be acceptable for the hospital to show thanks by providing nicer hospital rooms, 26.0% (95% CI, 21.9%-30.1%) by providing expedited appointments, and 19.8% (95% CI, 16.1%-23.5%) by providing physicians' cell phone numbers. Conclusions and Relevance: In this survey study of participants drawn from the general US population, a substantial proportion did not endorse legally allowable approaches for identifying, engaging, and thanking patient-donors.


Assuntos
Atitude Frente a Saúde , Obtenção de Fundos/métodos , Doações , Hospitais , Pacientes/psicologia , Papel do Médico/psicologia , Adulto , Distribuição por Idade , Idoso , Estudos de Coortes , Economia Hospitalar , Feminino , Obtenção de Fundos/ética , Doações/ética , Cardiopatias , Hospitais/ética , Humanos , Renda , Masculino , Pessoa de Meia-Idade , Neoplasias , Pacientes/estatística & dados numéricos , Probabilidade , Distribuição por Sexo , Fatores Socioeconômicos , Inquéritos e Questionários/estatística & dados numéricos , Estados Unidos , Adulto Jovem
20.
Bone Joint J ; 102-B(7): 950-958, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32600136

RESUMO

AIMS: To assess how the cost-effectiveness of total hip arthroplasty (THA) and total knee arthroplasty (TKA) varies with age, sex, and preoperative Oxford Hip or Knee Score (OHS/OKS); and to identify the patient groups for whom THA/TKA is cost-effective. METHODS: We conducted a cost-effectiveness analysis using a Markov model from a United Kingdom NHS perspective, informed by published analyses of patient-level data. We assessed the cost-effectiveness of THA and TKA in adults with hip or knee osteoarthritis compared with having no arthroplasty surgery during the ten-year time horizon. RESULTS: THA and TKA cost < £7,000 per quality-adjusted life-year (QALY) gained at all preoperative scores below the absolute referral thresholds calculated previously (40 for OHS and 41 for OKS). Furthermore, THA cost < £20,000/QALY for patients with OHS of ≤ 45, while TKA was cost-effective for patients with OKS of ≤ 43, since the small improvements in quality of life outweighed the cost of surgery and any subsequent revisions. Probabilistic and one-way sensitivity analyses demonstrated that there is little uncertainty around the conclusions. CONCLUSION: If society is willing to pay £20,000 per QALY gained, THA and TKA are cost-effective for nearly all patients who currently undergo surgery, including all patients at and above our calculated absolute referral thresholds. Cite this article: Bone Joint J 2020;102-B(7):950-958.


Assuntos
Artroplastia de Quadril/economia , Artroplastia do Joelho/economia , Medidas de Resultados Relatados pelo Paciente , Anos de Vida Ajustados por Qualidade de Vida , Encaminhamento e Consulta , Idoso , Análise Custo-Benefício , Feminino , Humanos , Masculino , Cadeias de Markov , Pessoa de Meia-Idade , Osteoartrite do Quadril/cirurgia , Osteoartrite do Joelho/cirurgia , Probabilidade , Reino Unido
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