3 research outputs found
Application of short-term analysis of skin temperature variability in prediction of survival in patients with cirrhosis
BACKGROUND: : Liver cirrhosis is a complex disorder, involving several different organ
systems and physiological network disruption. Various physiological markers have
been developed for survival modelling in patients with cirrhosis. Reduction in heart
rate variability and skin temperature variability have been shown to predict
mortality in cirrhosis, with the potential to aid clinical prognostication. We have
recently reported that short-term skin temperature variability analysis can predict
survival independently of the severity of liver failure in cirrhosis. However, in
previous reports, 24-h skin temperature recordings were used, which are often
not feasible in the context of routine clinical practice. The purpose of this study
was to determine the shortest length of time from 24-h proximal temperature
recordings that can accurately and independently predict 12-month survival postrecording in patients with cirrhosis. METHODS: Forty individuals diagnosed with cirrhosis participated in this study and wireless temperature sensors (iButtons) were used to record patients’ proximal
skin temperature. From 24-h temperature recordings, different length of
recordings (30 min, 1, 2, 3 and 6 h) were extracted sequentially for
temperature variability analysis using the Extended Poincaré plot to quantify
both short-term (SD1) and long-term (SD2) variability. These patients were
then subsequently followed for a period of 12 months, during which data was
gathered concerning any cases of mortality. RESULTS: Cirrhosis was associated with significantly decreased proximal skin
temperature fluctuations among individuals who did not survive, across all
durations of daytime temperature recordings lasting 1 hour or more. Survival
analysis showcased 1-h daytime proximal skin temperature time-series to be
significant predictors of survival in cirrhosis, whereby SD2, was found to be
independent to the Model for End-Stage Liver Disease (MELD) score and thus,
the extent of disease severity. As expected, longer durations of time-series were
also predictors of mortality for the majority of the temperature variability indices. CONCLUSION: Crucially, this study suggests that 1-h proximal skin temperature
recordings are sufficient in length to accurately predict 12-month survival in
patients with cirrhosis, independent from current prognostic indicators used in
the clinic such as MELD
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Application of short-term analysis of skin temperature variability in prediction of survival in patients with cirrhosis
10.3389/fnetp.2023.1291491Frontiers in Network Physiology