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E A Fernández

Publications and source records attributed to E A Fernández.

9 recordsLinked to original sources
PubMed2005

Comparison of different methods for hemodialysis evaluation by means of ROC curves: from artificial intelligence to current methods.

BACKGROUND: The National Kidney Foundation Guidelines (DOQI) and the European Renal Association (ERA) have set standards for adequacy of hemodialysis treatment. They recommended minimum single pool doses of 1.2 (Kt/Vsp DOQI), and 1.4 (Kt/Vsp ERA) and a "standard" urea removal ratio (URR) of 65%. Here, we compare an Artificial Intelligence Method (AIM) based on an Artificial Neural Network (ANN) and the usual methods for hemodialysis treatment follow-up such as Smye, Daugirdas, standard urea reduction ratio (URR using post-dialysis urea concentration) and modified URR [Cheng et al. 2001] against equilibrated Kt/V and URR calculated using a 60 min post-dialysis urea concentration. METHODS: We used ROC analysis to evaluate and compare these methodologies. We also propose a method to find a minimum target dose that maximizes the sensitivity, specificity and positive predictive values of the diagnostic tool. RESULTS: From a URR point of view, the ANN, stdURR and mURR perform almost equally well with an area under the curve (AUC) of 0.90, 0.93 and 0.92, respectively, but the ANN achieved the lowest false positive rate (FPR = 7.94%) and error rate (ER = 12.7%). When Kt/V is used as a dose index, the logarithmic single-and double-pool equations perform almost equally (AUC 0.957 and 0.962), and the ANN method achieves an AUC of 0.934. The lowest FPR was for ANN and Kt/Vsp (4.76%), which also achieved the lowest ER of 6.39%. CONCLUSIONS: For both cases (URR and Kt/V), the minimum doses required to achieve the lowest FPR and ER for the standard methods (stdURR and Kt/Vsp) were higher than those reported by the DOQI guidelines, being 70% for stdURR and 1.35 for Kt/Vsp, whereas for those methods using the double-pool Kt/V or equilibrated URR, the dose targets were close to those recommended by DOQI and ERA. Our proposed method for target dose selection is easy to understand, and it takes into account both accuracy and confidence of the adequacy tool. We found the ANN method to be superior to the Smye method for estimation of equilibrated urea, and the results presented here suggest that ANN methods could be useful tools in the analysis of nephrology data.

Artificial Intelligence↗
PubMed2003

Dialysate-side urea kinetics. Neural network predicts dialysis dose during dialysis.

Determination of the adequacy of dialysis is a routine but crucial procedure in patient evaluation. The total dialysis dose, expressed as Kt/V, has been widely recognised to be a major determinant of morbidity and mortality in haemodialysed patients. Many different factors influence the correct determination of Kt/V, such as urea sequestration in different body compartments, access and cardiopulmonary recirculation. These factors are responsible for urea rebound after the end of the haemodialysis session, causing poor Kt/V estimation. There are many techniques that try to overcome this problem. Some of them use analysis of blood-side urea samples, and, in recent years, on-line urea monitors have become available to calculate haemodialysis dose from dialysate-side urea kinetics. All these methods require waiting until the end of the session to calculate the Kt/V dose. In this work, a neural network (NN) method is presented for early prediction of the Kt/V dose. Two different portions of the dialysate urea concentration-time profile (provided by an on-line urea monitor) were analysed: the entire curve A and the first half B, using an NN to predict the Kt/V and compare this with that provided by the monitor. The NN was able to predict Kt/V is the middle of the 4h session (B data) without a significant increase in the percentage error (B data: 6.69% +/- 2.46%; A data: 5.58% +/- 8.77%, mean +/- SD) compared with the monitor Kt/V.

Adult↗
PubMed2001

Detection of abnormality in the electrocardiogram without prior knowledge by using the quantisation error of a self-organising map, tested on the European ischaemia database.

Most systems for the automatic detection of abnormalities in the ECG require prior knowledge of normal and abnormal ECG morphology from pre-existing databases. An automated system for abnormality detection has been developed based on learning normal ECG morphology directly from the patient. The quantisation error from a self-organising map 'learns' the form of the patient's ECG and detects any change in its morphology. The system does not require prior knowledge of normal and abnormal morphologies. It was tested on 76 records from the European Society of Cardiology database and detected 90.5% of those first abnormalities declared by the database to be ischaemic. The system also responded to abnormalities arising from ECG axis changes and slow baseline drifts and revealed that ischaemic episodes are often followed by long-term changes in ECG morphology.

Electrocardiography↗
PubMed2001

Using artificial intelligence to predict the equilibrated postdialysis blood urea concentration.

Total dialysis dose (Kt/V) is considered to be a major determinant of morbidity and mortality in hemodialyzed patients. The continuous growth of the blood urea concentration over the 30- to 60-min period following dialysis, a phenomenon known as urea rebound, is a critical factor in determining the true dose of hemodialysis. The misestimation of the equilibrated (true) postdialysis blood urea or equilibrated Kt/V results in an inadequate hemodialysis prescription, with predictably poor clinical outcomes for the patients. The estimation of the equilibrated postdialysis blood urea (eqU) is therefore crucial in order to estimate the equilibrated (true) Kt/V. In this work we propose a supervised neural network to predict the eqU at 60 min after the end of hemodialysis. The use of this model is new in this field and is shown to be better than the currently accepted methods (Smye for eqU and Daugirdas for eqKt/V). With this approach we achieve a mean difference error of 0.22 +/- 7.71 mg/ml (mean % error: 1.88 +/- 13.46) on the eqU prediction and a mean difference error for eqKt/V of -0.01 +/- 0.15 (mean % error: -0.95 +/- 14.73). The equilibrated Kt/V estimated with the eqU calculated using the Smye formula is not appropriate because it showed a great dispersion. The Daugirdas double-pool Kt/V estimation formula appeared to be accurate and in agreement with the results of the HEMO study.

Adult↗
PubMed1998

Trial of a community-based intervention to decrease infestation of Aedes aegypti mosquitoes in cement washbasins in El Progreso, Honduras.

Washbasins and metal drums are important sources of Aedes aegypti mosquitoes in much of Latin America. When manual cleaning was found to be ineffective in eliminating mosquito larvae in a community-based control programme in El Progreso, Honduras, it was decided to develop and evaluate an improved method of removing mosquito eggs based on commonly-available materials. The method, named La Untadita ('The Little Dab', in English), consists of five steps: mixing chlorine bleach and detergent to make a paste, applying the mixture to the walls of the container, waiting 10 min, scrubbing with a brush, and finally rinsing with water. A field trial of the Untadita was conducted in 13 peri-urban neighbourhoods. At the first post-intervention survey, in spite of high levels of exposure to the community-based intervention, high levels of knowledge regarding the Untadita and high levels of its reported use, little or no impact was discernable on mosquito larvae and pupae. The method was then modified by increasing the recommended quantities of bleach and detergent and simplifying the instructions. In the second post-intervention survey, knowledge of the steps and their order increased further; the intervention neighbourhoods had significantly fewer algae on washbasin walls, an indicator of more effective cleaning; and numbers of pupae and 3rd and 4th instar larvae were significantly lower than in untreated neighbourhoods. Effective promotion of the Untadita should be able to control mosquito infestation in many washbasins, especially those in frequent use, thus reducing the need for chemical and biological larvicides that may be either more costly or less acceptable to householders.

Aedes↗
PubMed1998

Development of an indicator to evaluate the impact, on a community-based Aedes aegypti control intervention, of improved cleaning of water-storage containers by householders.

Householders in a community-based programme to control dengue in El Progreso, Honduras, are being encouraged to improve the cleaning of the water-storage containers in which many of the vectors thrive. The objective of the present study was to develop an indicator of the change occurring in human behaviour. Traditional Aedes aegypti larval indices do not differentiate between containers in which all the immature stages are present and those which hold only first- and second-instar larvae. However, it is not essential to prevent all larval development to limit transmission of pathogens by the adults; if the Ae. aegypti in the containers only manage to develop to young larvae before the containers are cleaned, then control of the vector in these containers will be effective. In field trials, sampling of third- and fourth-instar larvae in washbasins by taking five dips (quick immersions to a standard depth) with a hand-held net was found to be sufficient for estimating the true population size of that same cohort. This sampling method was then included in a large-scale survey of households, conducted for programme monitoring. An index was then developed as a summary measure of the degree of infestation of a washbasin by Ae. aegypti. This index was the sum of four variables assessed in the survey: presence of any immature stages (larvae and/or pupae); presence of pupae; detection of third-fourth-instar larvae in a five-dip sample; and a log-transformation of the number of larvae recovered. Based on this new index, the 884 washbasins encountered in the survey were classified as infestation-free (76.2%), or with low-(6.7%), medium-(14.9%) or high-level (2.2%) infestation. Application of the same procedure to 240 drums encountered in the survey showed that 66.3% were infestation-free and 9.2%, 17.1% and 7.4% had low-, medium- and high-level infestations, respectively. Compared with the traditional indices, this new index should be more sensitive to changes in human behaviour resulting from a control programme exposure than a simple, dichotomous variable (i.e. positive/negative for presence of immature stages). The use of such an index could make the control programme more efficient, allowing the greatest efforts to be targeted at households that have medium-high levels of infestation.

Aedes↗