Automatic extraction of facial median sagittal plane for patients with asymmetry based on the EDMA alignment algorithm

BACKGROUND

We aimed to establish a novel method for automatically constructing three-dimensional (3D) median sagittal plane (MSP) for mandibular deviation patients, which can increase the efficiency of aesthetic evaluating treatment progress. We developed a Euclidean weighted Procrustes analysis (EWPA) algorithm for extracting 3D facial MSP based on the Euclidean distance matrix analysis, automatically assigning weight to facial anatomical landmarks.

METHODS

Forty patients with mandibular deviation were recruited, and the Procrustes analysis (PA) algorithm based on the original mirror alignment and EWPA algorithm developed in this study were used to construct the MSP of each facial model of the patient as experimental groups 1 and 2, respectively. The expert-defined regional iterative closest point algorithm was used to construct the MSP as the reference group. The angle errors of the two experimental groups were compared to those of the reference group to evaluate their clinical suitability.

RESULTS

The angle errors of the MSP constructed by the two EWPA and PA algorithms for the 40 patients were 1.39 ± 0.85°, 1.39 ± 0.78°, and 1.91 ± 0.80°, respectively. The two EWPA algorithms performed best in patients with moderate facial asymmetry, and in patients with severe facial asymmetry, the angle error was below 2°, which was a significant improvement over the PA algorithm.

CONCLUSIONS

The clinical application of the EWPA algorithm based on 3D facial morphological analysis for constructing a 3D facial MSP for patients with mandibular deviated facial asymmetry deformity showed a significant improvement over the conventional PA algorithm and achieved the effect of a dental clinical expert-level diagnostic strategy.

Feasibility of advanced composite endpoint analysis: Post-hoc insights from the vitamin intervention for stroke prevention randomized control trial

BACKGROUND AND AIMS

Stroke is a major cause of mortality and disability, highlighting the importance of prevention. Clinical trials play an important role in evaluating interventions that can maximize stroke prevention. Traditional composite endpoints (TCE) used in clinical trials have limitations, as they pool together events of varying clinical importance. Weighted composite endpoints (WCE) have emerged as a solution to address these limitations and provide more accurate assessments of outcomes. In this study, we investigate the use of WCE in a previously reported negative clinical trial for stroke prevention.

METHODS AND RESULTS

We analyzed data from the Vitamin Intervention for Stroke Prevention (VISP) trial, which compared high dose and low dose multivitamin therapy. We utilized weighted methods to analyze time-to-event outcomes with censoring. The primary outcomes of interest were time to nonfatal stroke, nonfatal coronary events, and death. We calculated modified Kaplan-Meier (KM) curves for each intervention group. We also performed a modified log-rank test to assess significant differences based on the weighted KM curves. The analysis included 3668 VISP trial participants, and most remained event-free throughout the study period. The TCE KM curve showed no significant difference in outcomes between high dose and low dose groups. Similarly, the WCE KM curves, with different weights assigned to each outcome, did not reveal significant differences in outcomes between the studied groups.

CONCLUSION

This post-hoc analysis confirms the negative trial results of VISP and demonstrates the feasibility of using WCE in assessing nutrition-based interventions for stroke prevention.

Fair comparisons of cause-specific and relative survival by accounting for the systematic removal of patients from risk-sets

BACKGROUND

In population-based cancer studies it is common to try to isolate the impact of cancer by estimating net survival. Net survival is defined as the probability of surviving cancer in the absence of any other-causes of death. Net survival can be estimated either in the cause-specific or relative survival framework. Cause-specific survival considers deaths from the cancer as the event of interest. Relative survival incorporates general population expected mortality rates to represent the other-cause mortality rate. Estimation approaches in both frameworks are impacted by the systematic removal of patients from the risk-set, commonly referred to as informative censoring in the cause-specific framework. In the relative survival framework, the Pohar Perme estimator combats the effect of this systematic removal of patients through weighting. When the two frameworks have been compared, informative censoring is rarely accounted for in the cause-specific framework.

METHODS

We investigate the use of weighted cause-specific Kaplan-Meier estimates to overcome the impact of informative censoring and compared approaches to defining weights. Individuals remaining in the risk-set are upweighted using their predicted other-cause survival obtained through various model-based approaches. We also compare weights derived from expected mortality rates. We applied the approaches to US cancer registry data and conducted a simulation study.

RESULTS

Using weighted cause-specific estimates provides a better estimate of marginal net survival. The unweighted Kaplan-Meier estimates have a similar bias to the Ederer II method for relative survival. Weighted Kaplan-Meier estimates are unbiased and similar to the Pohar Perme estimator. There was little variation between the several weighting approaches.

CONCLUSION

In comparisons of cause-specific and relative survival, it is important to compare "like-with-like", therefore, a weighted approach should be considered for both frameworks. If researchers are interested in obtaining net measures in a cause-specific framework, then weighting is needed to account for informative censoring.

COVID-19 inflation weights in the UK and Germany

The COVID-19 pandemic altered consumption patterns significantly in a short period of time. However, official inflation statistics take time to reflect changes in the weights of the CPI consumption basket. Using credit card data for the UK and Germany, we document how consumption patterns changed and quantify the resulting inflation bias. We find that consumers experienced a higher level of inflation at the beginning of the pandemic than what a fixed-weight inflation (or the official-weight) index suggests and lower inflation thereafter. We also show that weights can differ among age groups and in-person vs. online spenders. These differences affect the purchasing power of the population heterogeneously. We conclude that CPI inflation indexes based on frequently updated weights can provide useful inputs to assess changes in the cost of living, including across segments of the population. If shifts in consumption patterns prove persistent, these indexes can help determine the need to introduce new weights and inform monetary policy and the design of support policies for the more vulnerable.

Two-stage sampling in the estimation of growth parameters and percentile norms: sample weights versus auxiliary variable estimation

BACKGROUND

The use of auxiliary variables with maximum likelihood parameter estimation for surveys that miss data by design is not a widespread approach, despite its documented improved efficiency over traditional approaches that deploy sampling weights. Although efficiency gains from the use of Normally distributed auxiliary variables in a model have been recorded in the literature, little is known about the effects of non-Normal auxiliary variables in the parameter estimation.

METHODS

We simulate growth data to mimic SCALES, a two-stage survey of language development with a screening phase (stage one) for which data are observed for the whole sample and an intensive assessments phase (stage two), for which data are observed for a sub-sample, selected using stratified random sampling. In the simulation, we allow a fully observed Poisson distributed stratification criterion to be correlated with the partially observed model responses and develop five generalised structural equation growth models that host the auxiliary information from this criterion. We compare these models with each other and with a weighted growth model in terms of bias, efficiency, and coverage. We finally apply our best performing model to SCALES data and show how to obtain growth parameters and population norms.

RESULTS

Parameter estimation from a model that incorporates a non-Normal auxiliary variable is unbiased and more efficient than its weighted counterpart. The auxiliary variable method is capable of producing efficient population percentile norms and velocities.

CONCLUSIONS

The deployment of a fully observed variable that dominates the selection of the sample and correlates strongly with the incomplete variable of interest appears beneficial for the estimation process.

Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data

Background

Understanding how comorbidity measures contribute to patient mortality is essential both to describe patient health status and to adjust for risks and potential confounding. The Charlson and Elixhauser comorbidity indices are well-established for risk adjustment and mortality prediction. Still, a different set of comorbidity weights might improve the prediction of in-hospital mortality. The present study, therefore, aimed to derive a set of new Swiss Elixhauser comorbidity weightings, to validate and compare them against those of the Charlson and Elixhauser-based van Walraven weights in an adult in-patient population-based cohort of general hospitals.

Methods

Retrospective analysis was conducted with routine data of 102 Swiss general hospitals (2012–2017) for 6.09 million inpatient cases. To derive the Swiss weightings for the Elixhauser comorbidity index, we randomly halved the inpatient data and validated the results of part 1 alongside the established weighting systems in part 2, to predict in-hospital mortality. Charlson and van Walraven weights were applied to Charlson and Elixhauser comorbidity indices. Derivation and validation of weightings were conducted with generalized additive models adjusted for age, gender and hospital types.

Results

Overall, the Elixhauser indices, c-statistic with Swiss weights (0.867, 95% CI, 0.865–0.868) and van Walraven’s weights (0.863, 95% CI, 0.862–0.864) had substantial advantage over Charlson’s weights (0.850, 95% CI, 0.849–0.851) and in the derivation and validation groups. The net reclassification improvement of new Swiss weights improved the predictive performance by 1.6% on the Elixhauser-van Walraven and 4.9% on the Charlson weights.

Conclusions

All weightings confirmed previous results with the national dataset. The new Swiss weightings model improved slightly the prediction of in-hospital mortality in Swiss hospitals. The newly derive weights support patient population-based analysis of in-hospital mortality and seek country or specific cohort-based weightings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-020-05999-5.

Application of relative air pollution index (RAPI)-a new method for aggregate assessment of current air pollution in Cam Pha coal mining area, Quang Ninh province, Vietnam

In this article, the authors apply the relative air pollution index (RAPI) proposed by Pham Ngoc Ho for aggregate assessment of daily air pollution level (RAPI_d) using data from 3 daily standards (1, 8, and 24 h) of each country's standard, including Vietnam Technical Regulation QCVN 05:2013/MONRE. By using the automated data of ambient air at 3 monitoring stations in Cam Pha coal mining area, Quang Ninh province in 2018, results of the frequency of pollution by month (f%) have shown that overall, the air quality in dry season (October-March) is worse than that in rainy season (April-September). Results of pollution frequency by month in a year f% also indicate that air pollution in 2018 at 3 stations is mostly at level I (no pollution) with f% ranged from 10 to 58.3%, but pollution level II-IV (light pollution-very heavy pollution) also happened as f% fluctuated from 20 to 42% in some months. Comparing with air quality assessment in 2011-2015 at this area by periodic monitoring equipment of Quang Ninh Center for Environmental Monitoring, results in 2018 have shown that individual index of RAPI is consistent with the current status of air quality with high accuracy. To compare with RAPI_d, we used VN_AQI_d index of the Vietnam Environment Administration (VEA). Comparison results show that both indices do not encounter eclipsing effect. However, ambiguous effect occurred in the case of VN_AQI_d index (warning not suitable for reality in some cases). In addition, advantages and limitations of these two methods have been analyzed and explained in detail.

Allocation of weights using factor analysis for development of a novel water quality index

Water quality assessment and monitoring is one of the most important aspects for ensuring a good environmental health. A Water Quality Index (WQI) is one of the most frequently used tools for assessing overall quality of water resources. This study uses Factor Analysis (FA) for one of the most significant steps in WQI development - weight determination. Factor analysis has been applied to the water quality parameters shortlisted from Principal Component Analysis in the study area and it grouped the parameters into different sets of loadings. Each loading contained a group of parameters contributing to the overall variance addressed by that loading. Weights were allocated to each loading as well as to individual parameters within each loading. For final aggregation, a hybrid method was followed; where weighted harmonic means were estimated for the parameters within each loading and weighted arithmetic mean was estimated from the results of harmonic mean. The use of multivariate statistical technique reduces the subjectivity in the development of the final WQI and makes the current study a useful step in future for the development of a Ganga Water Quality Index (GWQI). In addition to this, the developed methodology can also be used for developing WQI for any water body depending on the availability of historical data.

A Framework for Optimal Attribute Evaluation and Selection in Hesitant Fuzzy Environment Based on Enhanced Ordered Weighted Entropy Approach for Medical Dataset

Background

In this paper, a generic hesitant fuzzy set (HFS) model for clustering various ECG beats according to weights of attributes is proposed. A comprehensive review of the electrocardiogram signal classification and segmentation methodologies indicates that algorithms which are able to effectively handle the nonstationary and uncertainty of the signals should be used for ECG analysis. Extensive research that focuses on incorporating vagueness in the form of fuzzy sets, fuzzy rough sets and hesitant fuzzy sets (HFS) has been in past decades.

Objective

The paper aims to develop an enhanced entropy based on the clustering technique for calculating the weights of the attributes to finally generate appropriately clustered attributes.

Material and Methods

Finding optimal attributes to make a decision has always been a matter of concern for the researchers. Metrics used for optimal attribute generation can be broadly classified into mutual dependency, similarity, correlation and entropy based metrics in fuzzy domain .The experimentation has been carried out on ECG dataset in a hesitant fuzzy framework with four attributes.

Results

We propose a novel correlation based on an algorithm that takes entropy based weighted attributes as input which effectively generates a relevant and non-redundant set of attributes. We have also derived correlation coefficient formulas for HFSs and applied them to clustering analysis under framework of hesitant fuzzy sets. The results show the comparison of the proposed mathematical model with the existing similarity based on algorithms.

Conclusion

The selection of optimal relevant attributes certainly highlights the robustness and efficacy of the proposed approach. The entire experimentation and comparative results help us conclude that selection of optimal attributes in hesitant fuzzy domain certainly prove to be a powerful tool in order to express uncertainty in the process of data acquisition and classification.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.

Setting the Weights: The Women's Capabilities Index for Malawi

Standard indicators of wellbeing such as the QALY for health and GDP per capita for economic development have been increasingly regarded as being too narrow in focus. There is a need to develop multidimensional measures of wellbeing that encompass the full range of factors that make life worth living. This study is part of a project that aims at developing a multidimensional index based on Sen's capability framework to assess women's wellbeing in rural Malawi: the Women's Capabilities Index. The project identifies a set of capabilities relevant to the context; proposes a methodology to measure robustly these capabilities; aggregates the capabilities into a single metric (index); and validates and tests the index. This paper focuses on the weighting and aggregation of the index. Four weighting methods of aggregation are chosen: two normative approaches; a data-driven approach; and a hybrid method. The different methods have implications on the results which are critically assessed and compared. This study contributes to the literature on the implications of adopting different methods for setting the weights in composite measures of wellbeing.

The Effects of Non-Nutritive Sucking and Pre-Feeding Oral Stimulation on Time to Achieve Independent Oral Feeding for Preterm Infants

Background:

The survival rates of preterm infants has increased over the last years, but oral feeding difficulties are the most common problems encountered by them

Objectives:

This study aimed at comparing the effects of non-nutritive sucking (NNS) and pre-feeding oral stimulation on feeding skills, length of hospital stay and weight gain of 26-32 weeks gestational age preterm infants in NICU, to determine the more effective intervention.

Patients and Methods:

Thirty-two preterm infants were assigned randomly into three groups. One intervention group received pre-feeding oral stimulation program and the other received non-nutritive sucking stimulation, while the control group received a sham intervention. Gestational age of infants was calculated during 1, 4 and 8 oral feeding and discharge time from NICU. The infants’ weights were measured weekly from birth and at discharge time.

Results:

Mean gestational age on 8 time oral feeding per day, in 3 groups was not significant (P = 0.282). Although NNS and pre-feeding oral stimulation groups has fulfilled this criterion 7.55 and 6.07 days sooner than the control group, respectively (a result which is of great clinical and economic importance), but the difference did not reach statistical significance. Weight gaining at discharge time in NNS group was significantly higher than control and pre-feeding oral stimulation groups (P < 0.05).

Conclusions:

This study revealed that pre-feeding oral stimulation and NNS programs both were effective on oral feeding skills and weight gaining of the immature newborns. Yet, it seems that NNS program was more effective than pre-feeding oral stimulation on weight gaining.

Measuring the efficiency of the Greek rural primary health care using a restricted DEA model; the case of southern and western Greece

This is a study to measure the efficiency of the rural Health Centres (HCs) and their Regional Surgeries (RSs) of the 6th Health Prefecture (HP) of Greece, which covers Southern and Western Greece. Data Envelopment Analysis (DEA) was applied under Constant and Variable Returns to Scale, using a weight-restricted, output-oriented model, to calculate pure technical efficiency (PΤΕ), scale efficiency (SE) and total technical efficiency (TE). The selection of inputs, outputs and their relative weights in the model was based on two consecutive consensus panels of experts on Primary Health Care (PHC). Medical personnel, nursing personnel and technological equipment were chosen as inputs and were attributed appropriate weight restrictions. Acute, chronic and preventive consultations where chosen as outputs; each output was constructed by smaller subcategories of different relative importance. Data were collected through a questionnaire sent to all HCs of the covered area. From the 42 HCs which provided complete data, the study identified 9 as technical efficient, 5 as scale efficient and 2 as total efficient. The mean TE, PTE and SE scores of the HCs of the 6th Health Prefecture were 0.57, 0.67 and 0.87, respectively. The results demonstrate noteworthy variation in efficiency in the productive process of the HCs of Southern and Western Greece. The dominant form of inefficiency was technical inefficiency. The HCs of the 6th HP can theoretically produce 33 % more output on average, using their current production factors. These results indicated potential for considerable efficiency improvement in most rural health care units. Emphasis on prevention and chronic disease management, as well as wider structural and organisational reforms, are discussed from the viewpoint of how to increase efficiency.

Prevalence of alcohol-impaired drivers based on random breath tests in a roadside survey in Catalonia (Spain)

Sobriety checkpoints are not usually randomly located by traffic authorities. As such, information provided by non-random alcohol tests cannot be used to infer the characteristics of the general driving population. In this paper a case study is presented in which the prevalence of alcohol-impaired driving is estimated for the general population of drivers. A stratified probabilistic sample was designed to represent vehicles circulating in non-urban areas of Catalonia (Spain), a region characterized by its complex transportation network and dense traffic around the metropolis of Barcelona. Random breath alcohol concentration tests were performed during spring 2012 on 7596 drivers. The estimated prevalence of alcohol-impaired drivers was 1.29%, which is roughly a third of the rate obtained in non-random tests. Higher rates were found on weekends (1.90% on Saturdays and 4.29% on Sundays) and especially at night. The rate is higher for men (1.45%) than for women (0.64%) and it shows an increasing pattern with age. In vehicles with two occupants, the proportion of alcohol-impaired drivers is estimated at 2.62%, but when the driver was alone the rate drops to 0.84%, which might reflect the socialization of drinking habits. The results are compared with outcomes in previous surveys, showing a decreasing trend in the prevalence of alcohol-impaired drivers over time.

Prediction equation for calculating fat mass in young Indian adults

PURPOSE

Accurate measurement or prediction of fat mass is useful in physiology, nutrition and clinical medicine. Most predictive equations currently used to assess percentage of body fat or fat mass, using simple anthropometric measurements were derived from people in western societies and they may not be appropriate for individuals with other genotypic and phenotypic characteristics. We developed equations to predict fat mass from anthropometric measurements in young Indian adults.

METHODS

Fat mass was measured in 60 females and 58 males, aged 20 to 29 yrs by using hydrostatic weighing and by simultaneous measurement of residual lung volume. Anthropometric measure included weight (kg), height (m) and 4 skinfold thickness [STs (mm)]. Sex specific linear regression model was developed with fat mass as the dependent variable and all anthropometric measures as independent variables.

RESULTS

The prediction equation obtained for fat mass (kg) for males was 8.46+0.32 (weight) - 15.16 (height) + 9.54 (log of sum of 4 STs) (R2= 0. 53, SEE=3.42 kg) and - 20.22 + 0.33 (weight) + 3.44 (height) + 7.66 (log of sum of 4 STs) (R2=0.72, SEE=3.01kg) for females.

CONCLUSION

A new prediction equation for the measurement of fat mass was derived and internally validated in young Indian adults using simple anthropometric measurements.

Long-term dynamics of a predator used for biological control and decoupling from mosquito prey in a subtropical treehole ecosystem

We identified, staged and counted the immature stages of mosquitoes from 1,826 censuses (with replacement) of the aquatic contents of ten treeholes surveyed every 2 weeks between 1978 and 1993. These time series were used to examine the population dynamics and effect on prey of the predatory mosquito Toxorhynchites rutilus. The mean annual frequency of occurrence of T. rutilus ranged from 0.02 to 0.67 among holes, and no fourth instars were recovered during a 30-month dry period. Oviposition and pupation by this species were recorded in all months, but most commonly in the spring. Overwintering larvae of the predator increased in weight during the prolonged fourth instar that preceded pupation in the spring. Time series analyses showed that the presence of a fourth instar T. rutilus significantly reduced the abundances of late-stage Aedes triseriatus mosquitoes. Pupal numbers of this prey species were more negatively affected by T. rutilus than were numbers of fourth instar A. triseriatus. Long-term declines in mean annual abundance of A. triseriatus prey during 16 years of observations on two holes were not correlated with increases in the mean annual frequencies of T. rutilus. Local extinctions of the aquatic stages of A. triseriatus within treeholes were common, but in most holes not significantly associated with the presence of T. rutilus, suggesting that predation does not routinely drive mosquito prey locally extinct in this ecosystem. The decoupling of T. rutilus and A. triseriatus, as revealed through these complete and long-term censuses, is contrasted with other reports of generalist predators causing extinctions of mosquito prey. Discrepancies among reported outcomes probably result from differences in duration of sampling periods and statistical procedures along with real differences in the intensity of predation among systems and sites.