RESUMO
BACKGROUND: Caesarean section is recommended in situations in which vaginal birth presents a greater likelihood of adverse maternal or perinatal outcomes than normal. However, it is associated with a higher risk of complications, especially when performed without a clear medical indication. Since labour attendants have no standardised clinical method to assist in this decision, statistical tools developed based on multiple labour variables may be an alternative. The objective of this paper was to develop and evaluate the accuracy of models for caesarean section prediction using maternal and foetal characteristics collected at admission and through labour. METHOD: This is a secondary analysis of the World Health Organization's Better Outcomes in Labour Difficulty prospective cohort study in two sub-Saharan African countries. Data were collected from women admitted for labour and childbirth in 13 hospitals in Nigeria as well as Uganda between 2014 and 2015. We applied logistic regression to develop different models to predict caesarean section, based on the time when intrapartum assessment was made. To evaluate discriminatory capacity of the various models, we calculated: area under the curve, diagnostic accuracy, positive predictive value, negative predictive value, sensitivity and specificity. RESULTS: A total of 8957 pregnant women with 12.67% of caesarean births were used for model development. The model based on labour admission characteristics showed an area under the curve of 78.70%, sensitivity of 63.20%, specificity of 78.68% and accuracy of 76.62%. On the other hand, the models that applied intrapartum assessments performed better, with an area under the curve of 93.66%, sensitivity of 80.12%, specificity of 89.26% and accuracy of 88.03%. CONCLUSION: It is possible to predict the likelihood of intrapartum caesarean section with high accuracy based on labour characteristics and events. However, the accuracy of this prediction is considerably higher when based on information obtained throughout the course of labour.
Assuntos
Cesárea/psicologia , Cesárea/estatística & dados numéricos , Modelos Estatísticos , Parto/psicologia , Adulto , Feminino , Humanos , Nigéria , Valor Preditivo dos Testes , Gravidez , Estudos Prospectivos , UgandaRESUMO
The POSEIDON group (Patient-Oriented Strategies Encompassing IndividualizeD Oocyte Number) has introduced "the ability to retrieve the number of oocytes needed to achieve at least one euploid embryo for transfer" as an intermediate marker of successful outcome in IVF/ICSI cycles. This study aimed to develop a novel calculator to predict the POSEIDON marker. We analyzed clinical and embryonic data of infertile couples who underwent IVF/ICSI with the intention to have trophectoderm biopsy for preimplantation genetic testing for aneuploidy. We used the negative binomial distribution to model the number of euploid blastocysts and the adaptive LASSO (Least Absolute Shrinkage and Selection Operator) method for variable selection. The fitted model selected female age, sperm source used for ICSI, and the number of mature (metaphase II) oocytes as predictors (p < 0.0001). Female age was the most important factor for predicting the probability of a blastocyst being euploid given each mature oocyte (loglikelihood of age [adjusted for sperm source]: 30.9; df = 2; p < 0.0001). The final predictive model was developed using logistic regression analysis, and internally validated by the holdout method. The predictive ability of the model was assessed by the ROC curve, which resulted in an area under the curve of 0.716. Using the final model and mathematical equations, we calculated the individualized probability of blastocyst euploidy per mature retrieved oocyte and the minimum number of mature oocytes required to obtain ≥1 euploid blastocyst-with their 95% confidence interval [CI]-for different probabilities of success. The estimated predicted probabilities of a mature oocyte turn into a euploid blastocyst decreased progressively with female age and was negatively modulated overall by use of testicular sperm across age (p < 0.001). A calculator was developed to make two types of predictions automatically, one using pretreatment information to estimate the minimum number of mature oocytes to achieve ≥1 euploid blastocyst, and another based on the actual number of mature oocytes collected/accumulated to estimate the chances of having a euploid blastocyst using that oocyte cohort for IVF/ICSI. The new ART calculator may assist in clinical counseling and individualized treatment planning regarding the number of oocytes required for at least one euploid blastocyst in IVF/ICSI procedures.
RESUMO
This multicenter study evaluated the reliability of the recently published ART calculator for predicting the minimum number of metaphase II (MII) oocytes (MIImin) to obtain at least one euploid blastocyst in patients undergoing in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI). We used clinical and embryonic retrospective data of 1,464 consecutive infertile couples who underwent IVF/ICSI with the intention to have preimplantation genetic testing for aneuploidy. The validation procedure followed a stepwise approach. Firstly, we assessed the distribution of euploid blastocysts per patient and found that it followed a negative binomial distribution. Secondly, we used generalized linear models and applied the Lasso procedure-including MII oocytes to adjust the data-to select the factors predicting the response variable "euploid blastocyst." Third, a logistic regression model-fit to the binomial response euploid (yes/no) for each MII oocyte-was built using the relevant factors. The observational unit was the "woman" whereas the response was the pair (m, n), where n is the number of retrieved MII oocytes and m the corresponding number of euploid blastocysts. The model was internally validated by randomly splitting the data into training and validation sets. The R-squares (~0.25) and the area under the ROC curve (~0.70) did not differ between the training and validation datasets. Fourth, mathematical equations and the calculated probabilities generated by the validation model were used to determine the MIImin required for obtaining at least one euploid blastocyst according to different success probabilities. Lastly, we compared the fittings generated by the validation model and the ART calculator and assessed the predictive value of the latter using the validation dataset. The fittings were sufficiently close for both the estimated probabilities of blastocyst euploid per MII oocyte (r = 0.91) and MIImin (r = 0.88). The ART calculator positive predictive values, i.e., the frequency of patients with at least one euploid blastocyst among those who achieved the estimated MIImin, were 84.8%, 87.5%, and 90.0% for 70%, 80%, and 90% predicted probabilities of success, respectively. The ART calculator effectively predicts the MIImin needed to achieve at least one euploid blastocyst in individual patients undergoing IVF/ICSI. The prediction tool might be used for counseling and planning IVF/ICSI treatments.
RESUMO
A maioria das avaliações econômicas que participam dos processos de decisão de incorporação e financiamento de tecnologias dos sistemas de saúde utiliza modelos de decisão para avaliar os custos e benefícios das estratégias comparadas. Apesar do grande número de avaliações econômicas conduzidas no Brasil, há necessidade de aprofundamento metodológico sobre os tipos de modelos de decisão e sua aplicabilidade no nosso meio. O objetivo desta revisão de literatura é contribuir para o conhecimento e o uso de modelos de decisão nos contextos nacionais das avaliações econômicas de tecnologias em saúde. Este artigo apresenta definições gerais sobre modelos e preocupações com o seu uso; descreve os principais modelos: árvore de decisão, Markov, microssimulação, simulação de eventos discretos e dinâmicos; discute os elementos envolvidos na escolha do modelo; e exemplifica os modelos abordados com estudos de avaliação econômica nacionais de tecnologias preventivas e de programas de saúde, diagnósticas e terapêuticas.
Most economic evaluations that participate in decision-making processes for incorporation and financing of technologies of health systems use decision models to assess the costs and benefits of the compared strategies. Despite the large number of economic evaluations conducted in Brazil, there is a pressing need to conduct an in-depth methodological study of the types of decision models and their applicability in our setting. The objective of this literature review is to contribute to the knowledge and use of decision models in the national context of economic evaluations of health technologies. This article presents general definitions about models and concerns with their use; it describes the main models: decision trees, Markov chains, micro-simulation, simulation of discrete and dynamic events; it discusses the elements involved in the choice of model; and exemplifies the models addressed in national economic evaluation studies of diagnostic and therapeutic preventive technologies and health programs.
Assuntos
Tecnologia Biomédica/economia , Análise Custo-Benefício , Técnicas de Apoio para a Decisão , Árvores de DecisõesRESUMO
O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.
The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.
RESUMO
The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.
O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.
RESUMO
The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.
O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.
RESUMO
The present work is aimed at analyzing the efficiency of decision support models which are based on mathematical programming to help with the choice of the adequate period for sowing, as well as, the technological pattern (high, medium and low yield) to the cultivation of wheat in relation to the losses which can be caused by frost, giberella, hail and excessive rain during the harvest season. The economical results were defined from data gathered in a group of 27 production units in Ijuí and surroundings. The levels and probabilities of the losses were estimated through review of specialized literature, also considering the experience of farmers and technicians of the region. It was suggested that the model which provided more support for the decision taking was the maximization model of gross margin restricted to reaching a determined economical result in a pre-established probability.
O objetivo do trabalho foi analisar a capacidade de modelos de ajuda à decisão baseados na programação matemática para subsidiar a escolha da época de semeadura e do padrão tecnológico (alto, médio e baixo rendimento) para a cultura do trigo em função das perdas que podem ser provocadas por geada, giberela, granizo e excesso de chuva na colheita. Os resultados econômicos da cultura foram definidos a partir dos dados de um grupo de 27 unidades de produção da região de Ijuí. Os níveis e as probabilidades das perdas foram estimados por meio de uma revisão da literatura especializada, tendo sido também levada em consideração a experiência dos agricultores e de técnicos da região. Foi concluído que o modelo de maximização da margem bruta sob a restrição de atingir certo resultado econômico a uma probabilidade pré-fixada foi o que proporcionou mais subsídios para a tomada de decisão.