The Efficacy of Renal Replacement Therapy for Rewarming of Patients in Severe Accidental Hypothermia—Systematic Review of the Literature

Abstract

Background: Renal replacement therapy (RRT) can be used to rewarm patients in deep hypothermia. However, there is still no clear evidence for the effectiveness of RRT in this group of patients. This systematic review aims to summarize the rewarming rates during RRT in patients in severe hypothermia, below or equal to 32 °C. Methods: This systematic review was registered in the PROSPERO International Prospective Register of Systematic Reviews (identifier CRD42021232821). We searched Embase, Medline, and Cochrane databases using the keywords hypothermia, renal replacement therapy, hemodialysis, hemofiltration, hemodiafiltration, and their abbreviations. The search included only articles in English with no time limit, up until 30 June 2021. Results: From the 795 revised articles, 18 studies including 21 patients, were selected for the final assessment and data extraction. The mean rate of rewarming calculated for all studies combined was 1.9 °C/h (95% CI 1.5–2.3) and did not differ between continuous (2.0 °C/h; 95% CI 0.9–3.0) and intermittent (1.9 °C/h; 95% CI 1.5–2.3) methods (p > 0.9). Conclusions: Based on the reviewed literature, it is currently not possible to provide high-quality recommendations for RRT use in specific groups of patients in accidental hypothermia. While RRT appears to be a viable rewarming strategy, the choice of rewarming method should always be determined by the specific clinical circumstances, the available resources, and the current resuscitation guidelines.

Early prediction of hypothermia in pediatric intensive care units using machine learning

“…An early therapy decision can help ICU management to initiate therapy such as rewarming to mitigate the risk of hypothermia ( Giesbrecht, 2001 ). The GBM-model performed best at 30 min lead-time and the performances declined during the higher lead times, however, a 30-min window can provide sufficient time for early therapy such as rewarming ( Mendrala et al, 2021 ). Our pipeline produced equal and superior results for the prospective validation, where an AUC of 79.7% was achieved for a lead-time of 30 min to 4 h. Our models were trained on a heterogeneous set of the population having different comorbidities are shown in Supplementary Table S1 , enabling our prediction system to generalize to a wide range of Intensive care patients.…”