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Nephrology (Carlton, Vic.) Jul 2022Baseline serum creatinine values are required to diagnose acute kidney injury but are often unavailable. We evaluated four conventional equations to estimate creatinine....
AIM
Baseline serum creatinine values are required to diagnose acute kidney injury but are often unavailable. We evaluated four conventional equations to estimate creatinine. We then developed and validated a new equation corrected by age and gender.
METHODS
We retrospectively examined adults who, at first hospital admission, had available baseline creatinine data and developed acute kidney injury ≥24 h after admission. We split the study population: 50% (derivation) to develop a new linear equation and 50% (validation) to compare against conventional equations for bias, precision, and accuracy. We stratified analyses by age and gender.
RESULTS
We studied 3139 hospitalized adults (58% male, median age 71). Conventional equations performed poorly in bias and accuracy in patients aged <60 or ≥75 (68% of the study population). The new linear equation had less bias and more accuracy. There were no clinically significant differences in precision. The median (95% confidence interval) difference in creatinine values estimated via the new equation minus measured baselines was 0.9 (-3.0, 5.9) and -0.5 (-7.0, 3.7) μmol/L in female patients 18-60 and 75-100, and -1.5 (-4.2, 2.2) and -7.8 (-12.7, -3.6) μmol/L in male patients 18-60 and 75-100, respectively. The new equation improved reclassification of KDIGO AKI stages compared to the MDRD II equation by 5.0%.
CONCLUSION
Equations adjusted for age and gender are less biased and more accurate than unadjusted equations. Our new equation performed well in terms of bias, precision, accuracy, and reclassification.
Topics: Acute Kidney Injury; Adult; Aged; Creatinine; Female; Glomerular Filtration Rate; Humans; Kidney; Male; Retrospective Studies
PubMed: 35471640
DOI: 10.1111/nep.14047 -
Evidence-based Complementary and... 2014Introduction. Qigong is currently considered as meditative movement, mindful exercise, or complementary exercise and is being explored for relief of symptoms in... (Review)
Review
Introduction. Qigong is currently considered as meditative movement, mindful exercise, or complementary exercise and is being explored for relief of symptoms in fibromyalgia. Aim. This narrative review summarizes randomized controlled trials, as well as additional studies, of qigong published to the end of 2013 and discusses relevant methodological issues. Results. Controlled trials indicate regular qigong practice (daily, 6-8 weeks) produces improvements in core domains for fibromyalgia (pain, sleep, impact, and physical and mental function) that are maintained at 4-6 months compared to wait-list subjects or baselines. Comparisons with active controls show little difference, but compared to baseline there are significant and comparable effects in both groups. Open-label studies provide information that supports benefit but remain exploratory. An extension trial and case studies involving extended practice (daily, 6-12 months) indicate marked benefits but are limited by the number of participants. Benefit appears to be related to amount of practice. Conclusions. There is considerable potential for qigong to be a useful complementary practice for the management of fibromyalgia. However, there are unique methodological challenges, and exploration of its clinical potential will need to focus on pragmatic issues and consider a spectrum of trial designs. Mechanistic considerations need to consider both system-wide and more specific effects.
PubMed: 25477991
DOI: 10.1155/2014/379715 -
Proceedings of the Conference.... Jun 2021We consider the problem of learning to simplify medical texts. This is important because most reliable, up-to-date information in biomedicine is dense with jargon and...
We consider the problem of learning to simplify medical texts. This is important because most reliable, up-to-date information in biomedicine is dense with jargon and thus practically inaccessible to the lay audience. Furthermore, manual simplification does not scale to the rapidly growing body of biomedical literature, motivating the need for automated approaches. Unfortunately, there are no large-scale resources available for this task. In this work we introduce a new corpus of parallel texts in English comprising technical and lay summaries of all published evidence pertaining to different clinical topics. We then propose a new metric based on likelihood scores from a masked language model pretrained on scientific texts. We show that this automated measure better differentiates between technical and lay summaries than existing heuristics. We introduce and evaluate baseline encoder-decoder Transformer models for simplification and propose a novel augmentation to these in which we explicitly penalize the decoder for producing 'jargon' terms; we find that this yields improvements over baselines in terms of readability.
PubMed: 35663507
DOI: 10.18653/v1/2021.naacl-main.395 -
Journal of Ethnobiology and... Nov 2013The shifting baseline syndrome is a concept from ecology that can be analyzed in the context of ethnobotanical research. Evidence of shifting baseline syndrome can be... (Review)
Review
BACKGROUND
The shifting baseline syndrome is a concept from ecology that can be analyzed in the context of ethnobotanical research. Evidence of shifting baseline syndrome can be found in studies dealing with intracultural variation of knowledge, when knowledge from different generations is compared and combined with information about changes in the environment and/or natural resources.
METHODS
We reviewed 84 studies published between 1993 and 2012 that made comparisons of ethnobotanical knowledge according to different age classes. After analyzing these studies for evidence of the shifting baseline syndrome (lower knowledge levels in younger generations and mention of declining abundance of local natural resources), we searched within these studies for the use of the expressions "cultural erosion", "loss of knowledge", or "acculturation".
RESULTS
The studies focused on different groups of plants (e.g. medicinal plants, foods, plants used for general purposes, or the uses of specific important species). More than half of all 84 studies (57%) mentioned a concern towards cultural erosion or knowledge loss; 54% of the studies showed evidence of the shifting baseline syndrome; and 37% of the studies did not provide any evidence of shifting baselines (intergenerational knowledge differences but no information available about the abundance of natural resources).
DISCUSSION AND CONCLUSIONS
The general perception of knowledge loss among young people when comparing ethnobotanical repertoires among different age groups should be analyzed with caution. Changes in the landscape or in the abundance of plant resources may be associated with changes in ethnobotanical repertoires held by people of different age groups. Also, the relationship between the availability of resources and current plant use practices rely on a complexity of factors. Fluctuations in these variables can cause changes in the reference (baseline) of different generations and consequently be responsible for differences in intergenerational knowledge. Unraveling the complexity of changes in local knowledge systems in relation to environmental changes will allow the identification of more meaningful information for resource conservation.
Topics: Acculturation; Ethnobotany; Health Knowledge, Attitudes, Practice; Humans; Intergenerational Relations; Knowledge; Phytotherapy
PubMed: 24229063
DOI: 10.1186/1746-4269-9-75 -
Research Synthesis Methods Nov 2020Meta-analysis of individual participant data (IPD) is considered the "gold-standard" for synthesizing clinical study evidence. However, gaining access to IPD can be a... (Meta-Analysis)
Meta-Analysis
Meta-analysis of individual participant data (IPD) is considered the "gold-standard" for synthesizing clinical study evidence. However, gaining access to IPD can be a laborious task (if possible at all) and in practice only summary (aggregate) data are commonly available. In this work we focus on meta-analytic approaches of comparative studies where aggregate data are available for continuous outcomes measured at baseline (pre-treatment) and follow-up (post-treatment). We propose a method for constructing pseudo individual baselines and outcomes based on the aggregate data. These pseudo IPD can be subsequently analysed using standard analysis of covariance (ANCOVA) methods. Pseudo IPD for continuous outcomes reported at two timepoints can be generated using the sufficient statistics of an ANCOVA model, i.e., the mean and standard deviation at baseline and follow-up per group, together with the correlation of the baseline and follow-up measurements. Applying the ANCOVA approach, which crucially adjusts for baseline imbalances and accounts for the correlation between baseline and change scores, to the pseudo IPD, results in identical estimates to the ones obtained by an ANCOVA on the true IPD. In addition, an interaction term between baseline and treatment effect can be added. There are several modeling options available under this approach, which makes it very flexible. Methods are exemplified using reported data of a previously published IPD meta-analysis of 10 trials investigating the effect of antihypertensive treatments on systolic blood pressure, leading to identical results compared with the true IPD analysis and of a meta-analysis of fewer trials, where baseline imbalance occurred.
Topics: Algorithms; Analysis of Variance; Blood Pressure Determination; Clinical Trials as Topic; Computer Simulation; Data Interpretation, Statistical; Humans; Hypertension; Models, Statistical; Outcome Assessment, Health Care; Research Design; Sleep Apnea, Obstructive; Systole; Treatment Outcome
PubMed: 32643264
DOI: 10.1002/jrsm.1434 -
International Journal of Computer... May 2021: Tracking of tools and surgical activity is becoming more and more important in the context of computer assisted surgery. In this work, we present a data generation...
PURPOSE
: Tracking of tools and surgical activity is becoming more and more important in the context of computer assisted surgery. In this work, we present a data generation framework, dataset and baseline methods to facilitate further research in the direction of markerless hand and instrument pose estimation in realistic surgical scenarios.
METHODS
: We developed a rendering pipeline to create inexpensive and realistic synthetic data for model pretraining. Subsequently, we propose a pipeline to capture and label real data with hand and object pose ground truth in an experimental setup to gather high-quality real data. We furthermore present three state-of-the-art RGB-based pose estimation baselines.
RESULTS
: We evaluate three baseline models on the proposed datasets. The best performing baseline achieves an average tool 3D vertex error of 16.7 mm on synthetic data as well as 13.8 mm on real data which is comparable to the state-of-the art in RGB-based hand/object pose estimation.
CONCLUSION
: To the best of our knowledge, we propose the first synthetic and real data generation pipelines to generate hand and object pose labels for open surgery. We present three baseline models for RGB based object and object/hand pose estimation based on RGB frames. Our realistic synthetic data generation pipeline may contribute to overcome the data bottleneck in the surgical domain and can easily be transferred to other medical applications.
Topics: Algorithms; Calibration; Deep Learning; Hand; Humans; Imaging, Three-Dimensional; Operating Rooms; Orthopedics; Reproducibility of Results; Surgery, Computer-Assisted
PubMed: 33881732
DOI: 10.1007/s11548-021-02369-2 -
Ecological Applications : a Publication... Jun 2021Loss of knowledge about historical environmental conditions and species' abundances threatens how new generations potentially perceive their environment and take action....
Loss of knowledge about historical environmental conditions and species' abundances threatens how new generations potentially perceive their environment and take action. The intergenerational shift in perceptions of environmental thresholds is a phenomenon frequently termed shifting baseline syndrome (SBS). The goals of this study were (1) to determine relationships between ordinal scores (e.g., few, many) and quantitative measures (e.g., estimates of population size) used by members of a Māori community in New Zealand to score indicators for understanding the abundance of forest resources, and (2) to then analyze these relationships according to people's age to detect the effects of SBS and the rate that this shift was occurring for each indicator. We detected consistent relationships between the ordinal scores and quantitative measures for six forest indicators provided by community members. However, there was only a high degree of confidence about the direction of the age effect for three abundance indicators (Kererū [New Zealand Pigeon], Hemiphaga novaeseelandiae, 15% increase [CI = 5.1-27.1%] in flock size for any given ordinal category for each decade increase in age; long-finned eel, Anguilla dieffenbachia, 30% decrease [CI = -45.1% to -11.3%] in the distance (m) walked along a riverbank between observations of an eel for any given ordinal category for each decade increase in age; and Australian brush-tailed possum, Trichosurus vulpecula, 27% decrease [CI = -38.9% to -13.9%] in the distance (m) walked through forest between observations of possum sign for any given ordinal category for each decade increase in age), but the effect was statistically strong for all three. The decoupling of indigenous peoples and local communities (IPLC) from their traditional lands and biodiversity by an array of political, environmental, social and economic drivers and feedback mechanisms have contributed to and exacerbated the conditions for SBS. However, the protection of customary practices to engage with the environment, including the harvest of natural resources, community-based environmental monitoring initiatives, and cultural immersion education programs offer opportunities for IPLC to mitigate the often deleterious effects of SBS.
Topics: Animals; Australia; Biodiversity; Conservation of Natural Resources; Forests; Humans; New Zealand
PubMed: 33560524
DOI: 10.1002/eap.2301 -
SSM - Population Health Jun 2022Excess mortality has been used to measure the impact of COVID-19 over time and across countries. But what baseline should be chosen? We propose two novel approaches: an...
What should be the baseline when calculating excess mortality? New approaches suggest that we have underestimated the impact of the COVID-19 pandemic and previous winter peaks.
Excess mortality has been used to measure the impact of COVID-19 over time and across countries. But what baseline should be chosen? We propose two novel approaches: an alternative retrospective baseline derived from the lowest weekly death rates achieved in previous years and a within-year baseline based on the average of the 13 lowest weekly death rates within the same year. These baselines express normative levels of the lowest feasible target death rates. The excess death rates calculated from these baselines are not distorted by past mortality peaks and do not treat non-pandemic winter mortality excesses as inevitable. We obtained weekly series for 35 industrialized countries from the Human Mortality Database for 2000-2020. Observed, baseline and excess mortalities were measured by age-standardized death rates. We assessed weekly and annual excess death rates driven by the COVID-19 pandemic in 2020 and those related to seasonal respiratory infections in earlier years. There was a distinct geographic pattern with high excess death rates in Eastern Europe followed by parts of the UK, and countries of Southern and Western Europe. Some Asia-Pacific and Scandinavian countries experienced lower excess mortality. In 2020 and earlier years, the alternative retrospective and the within-year excess mortality figures were higher than estimates based on conventional metrics. While the latter were typically negative or close to zero in years without extraordinary epidemics, the alternative estimates were substantial. Cumulation of this "usual" excess over 2-3 years results in human losses comparable to those caused by COVID-19. Challenging the view that non-pandemic seasonal winter mortality is inevitable would focus attention on reducing premature mortality in many countries. As SARS-CoV-2 is unlikely to be the last respiratory pathogen with the potential to cause a pandemic, such measures would also strengthen global resilience in the face of similar threats in the future.
PubMed: 35573866
DOI: 10.1016/j.ssmph.2022.101118 -
BMC Medical Informatics and Decision... Oct 2023There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support...
BACKGROUND
There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of inconsistent methods of estimating baseline serum creatinine (sCr) may result in a poor understanding of these models' effectiveness in clinical practice. Until now, the performance of such models with different baselines has not been compared on a single dataset. Additionally, AKI prediction models are known to have a high rate of false positive (FP) events regardless of baseline methods. This warrants further exploration of FP events to provide insight into potential underlying reasons.
OBJECTIVE
The first aim of this study was to assess the variance in performance of ML models using three methods of baseline sCr on a retrospective dataset. The second aim was to conduct an error analysis to gain insight into the underlying factors contributing to FP events.
MATERIALS AND METHODS
The Intensive Care Unit (ICU) patients of the Medical Information Mart for Intensive Care (MIMIC)-IV dataset was used with the KDIGO (Kidney Disease Improving Global Outcome) definition to identify AKI episodes. Three different methods of estimating baseline sCr were defined as (1) the minimum sCr, (2) the Modification of Diet in Renal Disease (MDRD) equation and the minimum sCr and (3) the MDRD equation and the mean of preadmission sCr. For the first aim of this study, a suite of ML models was developed for each baseline and the performance of the models was assessed. An analysis of variance was performed to assess the significant difference between eXtreme Gradient Boosting (XGB) models across all baselines. To address the second aim, Explainable AI (XAI) methods were used to analyse the XGB errors with Baseline 3.
RESULTS
Regarding the first aim, we observed variances in discriminative metrics and calibration errors of ML models when different baseline methods were adopted. Using Baseline 1 resulted in a 14% reduction in the f1 score for both Baseline 2 and Baseline 3. There was no significant difference observed in the results between Baseline 2 and Baseline 3. For the second aim, the FP cohort was analysed using the XAI methods which led to relabelling data with the mean of sCr in 180 to 0 days pre-ICU as the preferred sCr baseline method. The XGB model using this relabelled data achieved an AUC of 0.85, recall of 0.63, precision of 0.54 and f1 score of 0.58. The cohort size was 31,586 admissions, of which 5,473 (17.32%) had AKI.
CONCLUSION
In the absence of a widely accepted method of baseline sCr, AKI prediction studies need to consider the impact of different baseline methods on the effectiveness of ML models and their potential implications in real-world implementations. The utilisation of XAI methods can be effective in providing insight into the occurrence of prediction errors. This can potentially augment the success rate of ML implementation in routine care.
Topics: Humans; Creatinine; Retrospective Studies; Models, Statistical; Prognosis; Acute Kidney Injury
PubMed: 37814311
DOI: 10.1186/s12911-023-02306-0 -
Conservation Biology : the Journal of... Aug 2022Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different...
Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different human-pressure baselines of PAs, thereby potentially over- or underestimating PA effectiveness. We developed a framework that considers both human-pressure baseline and change in human pressure over time and assessed the effectiveness of 338 PAs in China from 2010 to 2020. The initial state of human pressure on PAs was taken as the baseline, and changes in human pressure index (HPI) were further analyzed under different baselines. We used the random forest models to identify the management measures that most improved effectiveness in resisting human pressure for the PAs with different baselines. Finally, the relationships between the changes in the HPI and the changes in natural ecosystems in PAs were analyzed with different baselines. Of PAs with low HPI baselines, medium HPI baselines, and high HPI baselines, 76.92% (n=150), 11.11% (n=12), and 22.86% (n=8) , respectively, showed positive effects in resisting human pressure. Overall, ignoring human-pressure baselines somewhat underestimated the positive effects of PAs, especially for those with low initial human pressure. For PAs with different initial human pressures, different management measures should be taken to improve effectiveness and reduce threats to natural ecosystems. We believe our framework is useful for assessing the effectiveness of PAs globally, and we recommend it be included in the Convention on Biological Diversity Post-2020 Strategy.
Topics: Biodiversity; China; Conservation of Natural Resources; Ecosystem; Humans
PubMed: 34989447
DOI: 10.1111/cobi.13887