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dc.titleApplication of short-term analysis of skin temperature variability in prediction of survival in patients with cirrhosis
dc.contributor.authorAbid, Noor-Ul-Hoda
dc.contributor.authorLum Cheng In, Travis
dc.contributor.authorBottaro, Matteo
dc.contributor.authorShen, Xinran
dc.contributor.authorHernaez Sanz, Iker
dc.contributor.authorYoshida, Satoshi
dc.contributor.authorFormentin, Chiara
dc.contributor.authorMontagnese, Sara
dc.contributor.authorMani, Ali R
dc.identifier.citationAbid, Noor-Ul-Hoda, Lum Cheng In, Travis, Bottaro, Matteo, Shen, Xinran, Hernaez Sanz, Iker, Yoshida, Satoshi, Formentin, Chiara, Montagnese, Sara, Mani, Ali R (2024-01-05). Application of short-term analysis of skin temperature variability in prediction of survival in patients with cirrhosis. Frontiers in Network Physiology 3. ScholarBank@NUS Repository.
dc.description.abstract<jats:p><jats:bold>Background:</jats:bold> 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 post-recording in patients with cirrhosis.</jats:p><jats:p><jats:bold>Methods:</jats:bold> 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.</jats:p><jats:p><jats:bold>Results:</jats:bold> 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.</jats:p><jats:p><jats:bold>Conclusion:</jats:bold> 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.</jats:p>
dc.publisherFrontiers Media SA
dc.description.sourcetitleFrontiers in Network Physiology
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