Esophageal thermometry outperforms bladder and tympanic monitoring during targeted temperature management and shock in the ICU.

BACKGROUND: Accurate core temperature management is fundamental to intensive care unit (ICU) practice, yet the dynamic reliability of less-invasive surrogate metrics during critical illness remains under-investigated. This study evaluated the accuracy and potential confounders of esophageal, bladder, and tympanic thermometry against intravascular temperature. METHODS: A prospective longitudinal study was conducted in 22 ICU patients receiving concurrently multi-site core temperature monitoring. High-resolution temperature and hemodynamic data were extracted over up to 72 h. Absolute agreement and dynamic trending were assessed using Bland-Altman and four-quadrant analyses, with confounders evaluated via Spearman correlation matrices. RESULTS: Among 833 paired measurements, esophageal thermometry demonstrated near-perfect agreement with intravascular temperature (bias 0.11 °C; 95% limits of agreement [LoA] -0.19 to 0.41 °C; Lin's concordance correlation coefficient [CCC] = 0.957). In contrast, bladder and tympanic modalities showed wider 95% LoAs (-0.32 to 0.82 °C and -0.62 to 0.55 °C, respectively) and context-dependent reliability. During targeted temperature management (TTM), bladder temperature exhibited marked thermal lag (trending concordance rate, 50.2%), driven by cardiac output, where decreased cardiac output increased delays between core and bladder temperature during cooling and re-warming (r = -0.42, P < 0.05). Tympanic thermometry errors were independent of hemodynamic parameters, showing no correlation with cardiac index (r = 0.08, P = 0.218) or norepinephrine dosage (r = 0.13, P = 0.052). CONCLUSIONS: Esophageal thermometry is a highly reliable non-invasive surrogate for intravascular temperature. Conversely, bladder thermometry is susceptible to flow-dependent thermal inertia during shock and TTM. Meanwhile, tympanic measurements exhibit wide, hemodynamically-independent variability, rendering them unreliable for continuous monitoring.