COS-Speech: Protocol to develop a core outcome set for dysarthria after stroke for use in clinical practice and research

BACKGROUND: Dysarthria after stroke is when speech intelligibility is impaired, and this occurs in half of all stroke survivors. Dysarthria often leads to social isolation, poor psychological well-being and can prevent return to work and social lives. Currently, a variety of outcome measures are used in clinical research and practice when monitoring recovery for people who have dysarthria. When research studies use different measures, it is impossible to compare results from trials and delays our understanding of effective clinical treatments. The aim of this study is to develop a core outcome set (COS) to agree what aspects of speech recovery should be measured for dysarthria after stroke (COS-Speech) in research and clinical practice. METHODS: The COS-Speech study will include five steps: (1) development of a long list of possible outcome domains of speech that should be measured to guide the survey; (2) recruitment to the COS-Speech study of three key stakeholder groups in the UK and Australia: stroke survivors, communication researchers and speech and language therapists/pathologists; (3) two rounds of the Delphi survey process; (4) a consensus meeting to agree the speech outcomes to be measured and a follow-up consensus meeting to match existing instruments/measures (from parallel systematic review) to the agreed COS-Speech; (5) dissemination of COS-Speech. DISCUSSION: There is currently no COS for dysarthria after stroke for research trials or clinical practice. The findings from this research study will be a minimum COS, for use in all dysarthria research studies and clinical practice looking at post-stroke recovery of speech. These findings will be widely disseminated using professional and patient networks, research and clinical forums as well as using a variety of academic papers, videos, accessible writing such as blogs and links on social media. TRIAL REGISTRATION: COS-Speech is registered with the Core Outcome Measures in Effectiveness Trials (COMET) database, October 2021 https://www.comet-initiative.org/Studies/Details/1959. In addition, “A systematic review of the psychometric properties and clinical utility of instruments measuring dysarthria after stroke” will inform the consensus meeting to match measures to COS-Speech. The protocol for the systematic reviews registered with the International Prospective Register of Systematic Reviews. PROSPERO registration number: CRD42022302998. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-022-06958-7

Adverse drug reactions and off-label and unlicensed medicines in children: a nested case control study of inpatients in a pediatric hospital

Off-label and unlicensed (OLUL) prescribing has been prevalent in pediatric practice. Using data from a prospective cohort study of adverse drug reactions (ADRs) among pediatric inpatients, we aimed to test the hypothesis that OLUL status is a risk factor for ADRs

Incidence, characteristics and risk factors of adverse drug reactions in hospitalized children - a prospective observational cohort study of 6,601 admissions

Adverse drug reactions (ADRs) are an important cause of harm in children. Current data are incomplete due to methodological differences between studies: only half of all studies provide drug data, incidence rates vary (0.6% to 16.8%) and very few studies provide data on causality, severity and risk factors of pediatric ADRs. We aimed to determine the incidence of ADRs in hospitalized children, to characterize these ADRs in terms of type, drug etiology, causality and severity and to identify risk factors

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods

BACKGROUND: In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years DISCUSSION: The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. SUMMARY: The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level

Detecting failure of climate predictions

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055

2,000-year-long temperature and hydrology reconstructions from the Indo-Pacific warm pool

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature 460 (2009): 1113-1116, doi:10.1038/nature08233.Northern Hemisphere surface temperature reconstructions suggest that the late twentieth century was warmer than any other time during the past 500 years and possibly any time during the past 1,300 years. These temperature reconstructions are based largely on terrestrial records from extra-tropical or highelevation sites; however, global average surface temperature changes closely follow those of the global tropics, which are 75% ocean. In particular, the tropical Indo- Pacific warm pool (IPWP) represents a major heat reservoir that both influences global atmospheric circulation and responds to remote northern latitude forcings. Here we present a decadally resolved continuous sea surface temperature (SST) reconstruction from the IPWP that spans the past two millennia and overlaps the instrumental record, enabling both a direct comparison of proxy data to the instrumental record and an evaluation of past changes in the context of twentieth century trends. Our record from the Makassar Strait, Indonesia, exhibits trends that are similar to a recent Northern Hemisphere temperature reconstruction. Reconstructed SST was, however, within error of modern values during the Medieval Warm Period from about AD 1000 to AD 1250, towards the end of the Medieval Warm Period. SSTs during the Little Ice Age (approximately ad 1550–1850) were variable, and 0.5 to 1°C colder than modern values during the coldest intervals. A companion reconstruction of δ18O of sea water—a sea surface salinity and hydrology indicator— indicates a tight coupling with the East Asian monsoon system and remote control of IPWP hydrology on centennial–millennial timescales, rather than a dominant influence from local SST variation.This work was financially supported by the US NSF and the Ocean Climate Change Institute of WHOI

Effect of the US-Mexico border region in cardiovascular mortality: ecological time trend analysis of Mexican border and non-border municipalities from 1998 to 2012

Abstract Background An array of risk factors has been associated with cardiovascular diseases, and developing nations are becoming disproportionately affected by such diseases. Cardiovascular diseases have been reported to be highly prevalent in the Mexican population, but local mortality data is poor. The Mexican side of the US-Mexico border has a culture that is closely related to a developed nation and therefore may share the same risk factors of cardiovascular diseases. We wanted to explore if there was higher cardiovascular mortality in the border region of Mexico compared to the rest of the nation. Methods We conducted a population based cross-sectional time series analysis to estimate the effects of education, insurance and municipal size in Mexican border (n = 38) and non-border municipalities (n = 2360) and its association with cardiovascular age-adjusted mortality rates between the years 1998–2012. We used a mixed effect linear model with random effect estimation and repeated measurements to compare the main outcome variable (mortality rate), the covariates (education, insurance and population size) and the geographic delimiter (border/non-border). Results Mortality due to cardiovascular disease was consistently higher in the municipalities along the US-Mexico border, showing a difference of 78 · 5 (95% CI 58 · 7-98 · 3, p < 0 · 001) more cardiovascular deaths after adjusting for covariates. Larger municipal size and higher education levels showed a reduction in cardiovascular mortality of 12 · 6 (95% CI 11 · 4-13 · 8, p < 0 · 001) deaths and 8 · 6 (95% CI 5 · 5-11 · 8, p < 0 · 001) deaths respectively. Insurance coverage showed an increase in cardiovascular mortality of 3 · 6 (95% CI 3 · 1-4 · 0, p < 0 · 001) deaths per decile point increase. There was an increase in cardiovascular mortality of 0 · 3 (95% CI −0 · 001-0 · 6, p = 0 · 050) deaths per year increase in the non-border but a yearly reduction of 2 · 9 (95% CI 0 · 75-5.0, p = 0 · 008) deaths in the border over the time period of 1998–2012. Conclusion We observed that the Mexican side of the US-Mexico border region is disproportionately affected by cardiovascular disease mortality as compared to the non-border region of Mexico. This was not explained by education, population density, or insurance coverage. Proximity to the US culture and related diet and habits can be explanations of the increasing mortality trend

DPEP1 Inhibits Tumor Cell Invasiveness, Enhances Chemosensitivity and Predicts Clinical Outcome in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide. To identify biologically relevant genes with prognostic and therapeutic significance in PDAC, we first performed the microarray gene-expression profiling in 45 matching pairs of tumor and adjacent non-tumor tissues from resected PDAC cases. We identified 36 genes that were associated with patient outcome and also differentially expressed in tumors as compared with adjacent non-tumor tissues in microarray analysis. Further evaluation in an independent validation cohort (N = 27) confirmed that DPEP1 (dipeptidase 1) expression was decreased (T: N ratio ∼0.1, P<0.01) in tumors as compared with non-tumor tissues. DPEP1 gene expression was negatively correlated with histological grade (Spearman correlation coefficient = −0.35, P = 0.004). Lower expression of DPEP1 in tumors was associated with poor survival (Kaplan Meier log rank) in both test cohort (P = 0.035) and validation cohort (P = 0.016). DPEP1 expression was independently associated with cancer-specific mortality when adjusted for tumor stage and resection margin status in both univariate (hazard ratio = 0.43, 95%CI = 0.24–0.76, P = 0.004) and multivariate analyses (hazard ratio = 0.51, 95%CI = 0.27–0.94, P = 0.032). We further demonstrated that overexpression of DPEP1 suppressed tumor cells invasiveness and increased sensitivity to chemotherapeutic agent Gemcitabine. Our data also showed that growth factor EGF treatment decreased DPEP1 expression and MEK1/2 inhibitor AZD6244 increased DPEP1 expression in vitro, indicating a potential mechanism for DPEP1 gene regulation. Therefore, we provide evidence that DPEP1 plays a role in pancreatic cancer aggressiveness and predicts outcome in patients with resected PDAC. In view of these findings, we propose that DPEP1 may be a candidate target in PDAC for designing improved treatments