暂无摘要。

The Fezouata Biota (Morocco) is a Burgess Shale-type (BST) assemblage that provides a wealth of information on Early Ordovician ecosystems. Much work has been done to compare the preservation of the Fezouata Biota to other BSTs. However, studies investigating preservation variations within the Fezouata Biota are rare. Here, we use probabilities to investigate the preservation of various ecological categories of Fezouata eumetazoans. Complex taphonomic processes and phylum-specific constraints have led to the better preservation of predators/scavengers in this biota. However, no differences in preservation are observed between vagile and sessile taxa. Importantly, Tremadocian taxa are better preserved than Floian ones. As such, this study highlights the gradual closure of the BST window of preservation in the Zagora region of Morocco and constitutes a benchmark for future palaeoecological and evolutionary studies on the Fezouata Biota.

BACKGROUND: ML predictive models have shown their capability to improve risk prediction and assist medical decision-making, nevertheless, there is a lack of accuracy systems to early identify future rapid CKD progressors in Colombia and even in South America.
OBJECTIVE: The purpose of this study was to develop a series of interpretable machine learning models that predict GFR at 6-months, 9-months, and 12-months.
METHODS: Over 29,000 CKD patients stages 1 to 3b (estimated GFR, <60 ml/min / 1.73 m2) with an average of 3-year follow-up data were included. We used the machine learning extreme gradient boosting (XGBoost) to build three models to predict the next eGFR. Models were internally and externally validated. In addition, we included SHapley Additive exPlanation (SHAP) values to offer interpretable global and local prediction models.
RESULTS: All models showed a good performance in development and external validation. However, the 6-months XGBoost prediction model showed the best performance in internal (MAE average= 6.07; RSME= 78.87), and in external validation (MAE average= 6.45, RSME= 18.94). The top 3 most influential features that pushed the predicted eGFR value to lower values were the interpolated values for eGFR and creatinine, and eGFR at baseline.
CONCLUSIONS: In the current study we have developed and validated machine learning models to predict the next eGFR value at different intervals. Furthermore, we attempted to approach the need for prediction explanation by offering transparent predictions.

暂无摘要。

Variability is inherent in most biological systems due to differences among members of the population. Two types of variation are commonly observed in studies: differences among samples and the \"error\" in estimating a population parameter (e.g. mean) from a sample. While these concepts are fundamentally very different, the associated variation is often expressed using similar notation-an interval that represents a range of values with a lower and upper bound. In this article we discuss how common intervals are used (and misused).

Background: Significant atrioventricular valve dysfunction can be associated with mortality or need for transplant in functionally univentricular heart patients undergoing staged palliation. The purposes of this study are to characterize the impact of concomitant atrioventricular valve intervention on outcomes at each stage of single ventricle palliation and to identify risk factors associated with poor outcomes in these patients. Methods: The Society of Thoracic Surgeons Congenital Heart Surgery Database was queried for functionally univentricular heart patients undergoing single ventricle palliation from 2013 through 2022. Separate analyses were performed on cohorts corresponding to each stage of palliation (1: initial palliation; 2: superior cavopulmonary anastomosis; 3: Fontan procedure). Bivariate analysis of demographics, diagnoses, comorbidities, preoperative risk factors, operative characteristics, and outcomes with and without concomitant atrioventricular valve intervention was performed. Multiple logistic regression was used to identify predictors associated with operative mortality or major morbidity. Results: Concomitant atrioventricular valve intervention was associated with an increased risk of operative mortality or major morbidity for each cohort (cohort 1: 62% vs 46%, P < .001; cohort 2: 37% vs 19%, P < .001; cohort 3: 22% vs 14%, P < .001). Black race in cohort 1 (odds ratio [OR] 3.151, 95% CI 1.181-9.649, P = .03) and preterm birth in cohort 2 (OR 1.776, 95% CI 1.049-3.005, P = .032) were notable predictors of worse morbidity or mortality. Conclusions: Concomitant atrioventricular valve intervention is a risk factor for operative mortality or major morbidity at each stage of single ventricle palliation. Several risk factors are associated with these outcomes and may be useful in guiding decision-making.

BACKGROUND: The World Database for Pediatric and Congenital Heart Surgery (WDPCHS), sponsored by the World Society for Pediatric and Congenital Heart Surgery (WSPCHS), provides complex congenital heart surgery outcomes analyses for member programs. This report represents the seven-year descriptive analysis of outcomes from active members of the WDPCHS.
METHODS: Individual institutions submit data based on the specific procedure via a password protected platform. The data are collected, stored, and analyzed at Kirklin Solutions Inc., based in Birmingham, Alabama. This report presents a descriptive analysis of these procedures submitted from January 1, 2017, to December 31, 2023.
RESULTS: A total of 50,174 procedures were submitted with an overall mortality of 4.6%. The majority of submissions were from Asian countries. The majority of cases submitted from these countries were of STAT mortality category I and II. Repair of a ventricular septal defect (with a mortality of 0.8%) and correction of tetralogy of Fallot (2.0% mortality) were the most common procedures submitted to the database.
CONCLUSIONS: The WSPCHS accomplished one of its missions in 2017 when the WDPCHS began accepting data from pediatric and congenital heart surgery programs across the globe. In doing so, it became one of the first organizations to create a platform for the exchange of knowledge and experience, regardless of the socioeconomic status of the particular program or country.

Physiologists often express the change in the value of a measurement made on two occasions as a ratio of the initial value. This is usually motivated by an assumption that the absolute change fails to capture the true extent of the alteration that has occurred in attaining the final value - if there is initial variation among individual cases. While it may appear reasonable to use ratios to standardize the magnitude of change in this way, the perils of doing so have been widely documented. Ratios frequently have intractable statistical properties, both when taken in isolation and when analysed using techniques such as regression. A new method of computing a standardized metric of change, based on principal components analysis (PCA), is described. It exploits the collinearity within sets of initial, absolute change and final values. When these sets define variables subjected to PCA, the standardized measure of change is obtained as the product of the loading of absolute change onto the first principal component (PC1) and the eigenvalue of PC1. It is demonstrated that a sample drawn from a population of these standardized measures: approximates a normal distribution (unlike the corresponding ratios); lies within the same range; and preserves the rank order of the ratios. It is also shown that this method can be used to express the magnitude of a physiological response in an experimental condition relative to that obtained in a control condition. KEY POINTS: The intractable statistical properties of ratios and the perils of using ratios to standardize the magnitude of change are well known. A new method of computing a standardized metric, based on principal components analysis (PCA), is described, which exploits the collinearity within sets of initial, absolute change and final values. A sample drawn from a population of these PCA-derived measures: approximates a normal distribution (unlike the corresponding ratios); lies within the same range as the ratios; and preserves the rank order of the ratios. The method can also be applied to express the magnitude of a physiological response in an experimental condition relative to a control condition.

Novel interventions for seroma prevention are urgently needed in clinical practice. Animal models are pivotal tools for testing these interventions; however, a significant translational gap persists between clinical and animal model outcomes. This systematic review aims to assess the methodological characteristics and quality of animal models utilized for seroma prevention. A meta-analysis was performed to estimate the expected seroma incidence rate for control groups and determine the effect size of typical interventions. We systematically retrieved all studies describing animal models in which seroma formation was induced. Methodological characteristics, risks of bias, and study quality were assessed. Seroma volume and -incidence data were used for the meta-analysis. In total, 55 studies were included, with 42 eligible for meta-analysis. Rats (69%) were the most frequently used species, with mastectomy (50%) being the predominant surgical procedure in these models. Despite significant risks of bias across all studies, an improving trend in reporting quality per decade was observed. The meta-analysis revealed an average seroma incidence of 90% in typical control groups. The average intervention halved the seroma incidence (RR = 0.49; CI 0.35, 0.70) and significantly reduced seroma volume (SMD = -3.31; CI -4.21, -2.41), although notable heterogeneity was present. In conclusion, animal models for seroma prevention exhibit methodological flaws and multiple risks of bias. Implementing sufficiently powered positive and negative control groups could improve the internal validity of these models. More research is needed for further development of animal seroma models.

BACKGROUND: There have been concerns about the potential cardiovascular (CV) adverse effects associated with methylphenidate (MTH) use. However, only limited evidence exists on the long-term safety of MTH.
OBJECTIVE: To evaluate whether MTH use is associated with long-term CV risk.
METHODS: This was a retrospective cohort study using 2003-2017 data from the Health and Welfare Database in Taiwan. Patients newly diagnosed with attention deficit and hyperactivity disorder (ADHD) and between 3 and 18 years of age were included. Two treatment statuses were assessed: initial treatment ≥7 days and ≥180 days. Patients treated with MTH were compared with those receiving non-medication therapy. One-to-one propensity score matching was used to balance between-group differences. Study outcomes included major CV events, chronic CV disease, cardiogenic shock and all-cause mortality. Cox proportional hazard models were used to estimate HRs between the two groups.
RESULTS: We began with 307 459 patients with ADHD. After exclusion, 224 732 patients were included in the final cohort. The results showed that compared with non-ADHD medication users, patients who were treated with MTH for more than 7 days had a similar risk of major CV events (HR 0.85, 95% CI 0.72 to 0.99; p=0.040). Identical trends were found in groups who were treated for more than 180 days (HR 0.83, 95% CI 0.69 to 1.00; p=0.050). The results of the sensitivity analyses were consistent with the main analyses across all groups and individual outcomes.
CONCLUSIONS: Short-term MTH use did not increase CV risk among patients with ADHD. More evidence on long-term MTH use and risk of cardiogenic shock and death is warranted.