Cost-effectiveness of low-astigmatism correction with toric or spherical intraocular lenses combined with corneal incisions: an economic evaluation.

PURPOSE: To assess the cost-effectiveness of the treatment of low corneal astigmatism (≤1.5 diopters) at the moment of cataract surgery. SETTING: Qvision, Ophthalmology Department, VITHAS Almería Hospital, Spain. DESIGN: Economic evaluation. METHODS: A decision tree was used to assess the cost-effectiveness of implanting spherical vs toric intraocular lenses (IOLs) or spherical lens combined with the following corneal incisions: limbal-relaxing incisions conducted manually (M-LRI) or assisted by femtosecond laser (F-LRI), arcuate keratotomies conducted manually (M-AK) or assisted by femtosecond laser (F-AK), and intrastromal arcuate keratotomies (F-iAK). Outcomes of cost were selected from a patient perspective considering the gross cost of each one of the surgeries at European centers, and the effectiveness variable was the probability of achieving a visual acuity of 20/20 postoperatively. A sensitivity analysis was conducted to assess the uncertainty considering the evidence retrieved from the transition probabilities of the model, effectiveness, and cost. RESULTS: F-AK or toric IOLs were the most effective treatments, increasing an 16% or 9%, respectively, in the percentage of eyes attaining 20/20 vision. The M-LRI, F-iAK, and F-LRI procedures were strongly dominated while the M-AK and toric IOL were weakly dominated by the F-AK. A patient with low corneal astigmatism would need to be willing to pay 360€ (95% CI, 231-1224) with F-AK and 472€ (95% CI, 149-4490) with toric IOLs for a 10% increase in the probability of achieving 20/20 vision. CONCLUSIONS: From patient perspective, F-AK was generally the most cost-effective treatment, although toric IOLs can dominate in some countries.

Economic evaluations in cataract surgery: a narrative review.

Economic evaluations are tools for assessing emerging technologies and a complement for decision-making in healthcare systems. However, this topic may not be familiar for doctors and academics, who may be confused when interpreting the results of studies using these tools. Cataract is a disease which has received special attention in healthcare systems due to its high incidence, the great impact that it could have on patients' quality of life, and the fact that it can be definitively solved in almost all cases through cataract surgery. Historically, economic evaluations in cataract surgery have been conducted for many purposes by simply assessing whether the surgery is cost-effective for specific questions related to the implantation of multifocal intraocular lenses, surgical techniques, optimizing assessments, preventing diseases or complications, etc. Moreover, although there are systematic reviews about cataract surgery and narrative reviews introducing the concept of economic evaluations, as far as we know, no previous study has been conducted that synthesizes and integrates evidence coming from both fields. Thus, the purpose of this narrative review is to introduce doctors and academics to economic evaluation tools, to describe how these have been historically applied to cataract surgery, and to provide special considerations for the correct interpretation of economic studies.

Simulations of Multifocal Vision in Patients With Previous Monofocal Intraocular Lens Implantation.

PURPOSE: To evaluate the effectiveness and patient acceptance of multifocal vision simulation in patients with previous monofocal intraocular lens (IOL) implantation, and to explore their willingness-to-pay (WTP) and willingness-to-accept (WTA) based on the perceived advantages and disadvantages of multifocal vision. METHODS: Seventeen patients with previous monofocal IOL implantation participated in this cross-sectional study. The SimVis Gekko device (2EyesVision SL) was used to simulate monofocal (Evaluation B) and multifocal (Evaluation C) visual experiences, compared to their existing vision (Evaluation A). Visual acuity at three distances and defocus curves were measured. Patients responded to inquiries about visual quality in each evaluation, bothersomeness of photic phenomena, probability to select the visual experience, and the monetary value they associated with enhanced WTP or diminished WTA visual quality. RESULTS: The simulations underestimated the visual acuity reported for the IOL in existing literature by one or two lines, depending on the testing distance. This underestimation was more pronounced in defocus curves. However, 70.6% of patients were likely or very likely to opt for multifocal vision, indicating they perceived the benefits of multifocality. The WTP for multifocal vision was twice that of monofocal vision, and the WTP/WTA ratio exceeded 1, suggesting the perceived vision benefits outweighed potential drawbacks. CONCLUSIONS: Despite underestimating the expected postoperative visual performance, the multifocal simulation enabled patients to perceive the benefits of multifocal vision to some extent. This system could be beneficial in avoiding potential postoperative complaints, but the possible rise in false-positive results should be considered and evaluated in future research. [J Refract Surg. 2023;39(12):831-839.].

Economic Evaluation of Cataract: A Systematic Mapping Review.

INTRODUCTION: The purpose of this article was to ascertain the existing literature and find the gaps in economic evaluations of cataracts. METHODS: Systematic methods were used to search and collect the published literature on economic evaluations of cataracts. A mapping review of studies published in the following bibliographical databases was performed: the National Library of Medicine (PubMed), EMBASE, Web of Science (WOS), and the Central of Reviews and Dissemination (CRD) database. A descriptive analysis was conducted and relevant studies were classified into different groups. RESULTS: Among 984 studies screened, 56 studies were included in the mapping review. Four research questions were answered. There has been a progressive increase of publications during the last decade. The majority of the included studies were published by authors from institutions in the USA and UK. The most commonly investigated area was cataract surgery followed by intraocular lenses (IOLs). The studies were classified into different categories according to the main outcome evaluated, such as comparisons between different surgical techniques, costs of the cataract surgery, second eye cataract surgery costs, quality of life gain after cataract surgery, waiting time of cataract surgery and costs, and cataract evaluation, follow-up, and costs. In the IOL classification, the most frequently studied area was the comparison between monofocal and multifocal IOLs, followed by the comparison between toric and monofocal IOLs. CONCLUSIONS: Cataract surgery is a cost-effective procedure compared with other non-ophthalmic and ophthalmic interventions and surgery waiting time is an important factor to consider because vision loss has a huge and broad-ranging impact on society. Numerous gaps and inconsistencies are found among the studies included. For this reason, there is a need for further studies according to the classification described in the mapping review.

GPS Tracking to Monitor the Spatiotemporal Dynamics of Cattle Behavior and Their Relationship with Feces Distribution.

The sustainability of agrosilvopastoral systems, e.g., dehesas, is threatened. It is necessary to deepen the knowledge of grazing and its environmental impact. Precision livestock farming (PLF) technologies pose an opportunity to monitor production practices and their effects, improving decision-making to avoid or reduce environmental damage. The objective of this study was to evaluate the potential of the data provided by commercial GPS collars, together with information about farm characteristics and weather conditions, to characterize the distribution of cattle dung in paddocks, paying special attention to the identification of hotspots with an excessive nutrient load. Seven animals were monitored with smart collars on a dehesa farm located in Cordoba, Spain. Dung deposition was recorded weekly in 90 sampling plots (78.5 m2) distributed throughout the paddock. Grazing behavior and animal distribution were analyzed in relation to several factors, such as terrain slope, insolation or distance to water. Animal presence in sampling plots, expressed as fix, trajectory segment or time counting, was regressed with dung distribution. Cattle showed a preference for flat terrain and areas close to water, with selection indices of 0.30 and 0.46, respectively. The accumulated animal presence during the experimental period explained between 51.9 and 55.4% of the variance of dung distribution, depending on the indicator used, but other factors, such as distance to water, canopy cover or ambient temperature, also had a significant effect on the spatiotemporal dynamics of dung deposition. Regression models, including GPS data, showed determination coefficients up to 82.8% and were able to detect hotspots of dung deposition. These results are the first step in developing a decision support tool aimed at managing the distribution of dung in pastures and its environmental effects.

S3 and Recovery and Resilience Funds: A Case Study Built on the Experience of 10 Spanish Regions.

The EU's response to the COVID-19 crisis, namely the approval of the Next Generation package, provides an opportunity to explore to what extent the existing Smart Specialisation regional strategies and related ecosystems have been taken into account in the highly relevant territorial context in which the national Recovery Plans have been designed. According to our results the potential of the Smart Specialisation approach (S3) in relation with its place-based strategic prioritisation may have been overlooked in the process. The research is based on a desk review of relevant documents and recent literature in this field; followed by semi-structured interviews with regional planners and practitioners from 10 Spanish regions (autonomous communities); complemented, in a second phase, by the organisation of a focus group to validate the initial results. During our research we identified the main contributions that the Smart Specialisation approach has so far made to the regions (mainly in terms of participative governance and creation of regional ecosystems); and the unanimous perception shared by all the practitioners interviewed that the S3 approach has led to a change of vision in public intervention. However, all of the interviewed regions have confirmed that the drafting of the national recovery and resilience plan lacked an ex-ante alignment with the regional S3 strategies, and failed to consider the existing regional S3 ecosystems. The separation of the recovery logic (based on the operation of public consultations at national level to identify strategic projects) from the S3 logic (based on a strategic prioritisation exercise conducted by each regional ecosystem) confirms that an opportunity may have been missed in the recovery planning process to consolidate the multi-actor, multilevel and place-based S3 approach. Although there is a certain degree of disappointment among regional practitioners as a result of this misalignment, the majority of them believe in the possibility of an ex-post alignment between the two processes, that can protect existing regional shared visions. However, without clear recognition of the S3 ecosystems and the S3 managing bodies, the significant role that Smart Specialisation could play in the recovery process may be at risk.

A Low-Cost IoT-Based System to Monitor the Location of a Whole Herd.

Animal location technologies have evolved considerably in the last 60 years. Nowadays, animal tracking solutions based on global positioning systems (GPS) are commercially available. However, existing devices have several constraints, mostly related to wireless data transmission and financial cost, which make impractical the monitorization of all the animals in a herd. The main objective of this work is to develop a low-cost solution to enable the monitorization of a whole herd. An IoT-based system, which requires some animals of the herd being fitted with GPS collars connected to a Sigfox network and the rest with low-cost Bluetooth tags, has been developed. Its performance has been tested in two commercial farms, raising sheep and beef cattle, through the monitorization of 50 females in each case. Several collar/tag ratios, which define the cost per animal of the solution, have been simulated. Results demonstrate that a low collar/tag ratio enable the monitorization of a whole sheep herd. A larger ratio is needed for beef cows because of their grazing behavior. Nevertheless, the optimal ratio depends on the purpose of location data. Large variability has been observed for the number of hourly and daily messages from collars and tags. The system effectiveness for the monitorization of all the animals in a herd has been certainly proved.

Near-Infrared Spectroscopy and Geostatistical Analysis for Modeling Spatial Distribution of Analytical Constituents in Bulk Animal By-Product Protein Meals.

Control and inspection operations within the context of safety and quality assessment of bulk foods and feeds are not only of particular importance, they are also demanding challenges, given the complexity of food/feed production systems and the variability of product properties. Existing methodologies have a variety of limitations, such as high costs of implementation per sample or shortcomings in early detection of potential threats for human/animal health or quality deviations. Therefore, new proposals are required for the analysis of raw materials in situ in a more efficient and cost-effective manner. For this purpose, a pilot laboratory study was performed on a set of bulk lots of animal by-product protein meals to introduce and test an approach based on near-infrared (NIR) spectroscopy and geostatistical analysis. Spectral data, provided by a fiber optic probe connected to a Fourier transform (FT) NIR spectrometer, were used to predict moisture and crude protein content at each sampling point. Variographic analysis was carried out for spatial structure characterization, while ordinary Kriging achieved continuous maps for those parameters. The results indicated that the methodology could be a first approximation to an approach that, properly complemented with the Theory of Sampling and supported by experimental validation in real-life conditions, would enhance efficiency and the decision-making process regarding safety and adulteration issues.

Evaluation of local approaches to obtain accurate near-infrared (NIR) equations for prediction of ingredient composition of compound feeds.

This research work investigated new methods to improve the accuracy of intact feed calibrations for the near-infrared (NIR) prediction of the ingredient composition. When NIR reflection spectroscopy, together with linear models, was used for the prediction of the ingredient composition, the results were not always acceptable. Therefore, other methods have been investigated. Three different local methods (comparison analysis using restructured near-infrared and constituent data [CARNAC]), locally weighed regression [LWR], and LOCAL) were applied to a large (N = 20 320) and heterogeneous population of non-milled feed compounds for the NIR prediction of the inclusion percentage of wheat and sunflower meal, as representative of two different classes of ingredients. Compared with partial least-squares regression, results showed considerable reductions of standard error of prediction values for all methods and ingredients: reductions of 59, 47, and 50% with CARNAC, LWR, and LOCAL, respectively, for wheat, and reductions of 49, 45, and 43% with CARNAC, LWR, and LOCAL, respectively, for sunflower meal. These results are a valuable achievement in coping with legislation and manufacture requirements concerning the labeling of intact feedstuffs.

Pixel selection for near-infrared chemical imaging (NIR-CI) discrimination between fish and terrestrial animal species in animal protein by-product meals.

This paper proposes a method based on near-infrared hyperspectral imaging for discriminating between terrestrial and fish species in animal protein by-products used in livestock feed. Four algorithms (Mahalanobis distance, Kennard-Stone, spatial interpolation, and binning) were compared in order to select an appropriate subset of pixels for further partial least squares discriminant analysis (PLS-DA). The method was applied to a set of 50 terrestrial and 40 fish meals analyzed in the 1000-1700 nm range. Models were then tested using an external validation set comprising 45 samples (25 fish and 20 terrestrial). The PLS-DA models obtained using the four subset-selection algorithms yielded a classification accuracy of 99.80%, 99.79%, 99.85%, and 99.61%, respectively. The results represent a first step for the analysis of mixtures of species and suggest that NIR-CI, providing valuable information on the origin of animal components in processed animal proteins, is a promising method that could be used as part of the EU feed control program aimed at eradicating and preventing bovine spongiform encephalopathy (BSE) and related diseases.

Feasibility of diode-array instruments to carry near-infrared spectroscopy from laboratory to feed process control.

Near-infrared calibrations were developed for the instantaneous prediction of the chemical and ingredient composition of intact compound feeds. Two rather different instruments were compared (diode array vs grating monochromator). The grating monochromator was used in a static mode in the laboratory, whereas the diode-array instrumentbetter adapted to online analysiswas placed on a conveyor belt to simulate measurements at a feed mill plant. Modified partial least squares (MPLS) equations were developed using the same set of samples analyzed in the two instruments. Sample set 1 ( N = 398) was used to predict crude protein (CP) and crude fiber (CF), while sample set 2 ( N = 393) was used for the prediction of one macroingredient (sunflower meal, SFM) and one microingredient (mineral-vitamin premix, MVP). The standard error of cross-validation (SECV) and the coefficient of determination (R2) values for CF were better using the monochromator instrument. However, results obtained for CP, SFM, and MVP using the samples analyzed in the diode-array instrument showed similar or even greater accuracy than those obtained using samples analyzed in the grating monochromator. The excellent predictive ability [R2> 0.95; RPD (ratio of standard deviation to SECV) > 3] obtained for CP, CF, and SFM opens the way for the online use of NIRS diode-array instruments for surveillance and monitoring in the manufacture, processing, and marketing of compound feeds. R2, RPD, and SECV values for MVP showed similar performance for both instruments. Although RPD values did not reach the minimum recommended for quantitative analysis, results are encouraging for an ingredient present in feed compounds in such very low amounts.

Near-infrared reflectance spectroscopy for predicting amino acids content in intact processed animal proteins.

Near-infrared calibrations were developed for the instantaneous prediction of amino acids composition of processed animal proteins (PAPs). Two sample presentation modes were compared (ground vs intact) for demonstrating the viability of the analysis in the intact form, avoiding the need for milling. Modified partial least-squares (MPLS) equations for the prediction of amino acids in PAPs were developed using the same set of samples (N = 92 PAPs) analyzed in ground and intact form and in three cups differing in the optical window size. The standard error for cross validation (SECV) and the coefficient of determination (1-VR) values yielded with the calibrations developed using the samples analyzed in the intact form showed similar or even better accuracy than those obtained with finely ground samples. The excellent predictive ability (1-VR > 0.90; CV < 3.0%) obtained for the prediction of amino acids in intact processed animal proteins opens an enormous expectative for the on-line implementation of NIRS technology in the processing and marketing of these important protein feed ingredients, alleviating the costs and time associated with the routine quality controls.