Back

Wavelet analysis reveals non-stationary cardiovascular rhythms associated with delirium and deep sedation in ICU patients

Sreekanth, J.; Salgado-Baez, E.; Edel, A.; Gruenewald, E.; Piper, S. K.; Spies, C.; Balzer, F.; Boie, S. D.

2026-04-23 health informatics
10.64898/2026.04.22.26351455 medRxiv
Show abstract

Routine ICU data offers valuable insights into daily physiological rhythms. While traditional methods assume these cycles maintain fixed periods and amplitudes, their inherent variability requires dynamic estimation of instantaneous trends. Wavelet transform effectively resolves circadian oscillations, especially for frequently measured vital parameters. We present novel extensions to the Continuous Wavelet Transform (CWT) power spectral analysis to better detect and segment subtle temporal patterns. Using this approach, we uncover hidden circadian patterns in cardiovascular vitals such as Heart Rate (HR) and Mean Blood Pressure (MBP) measured over five days in a retrospective cohort of 855 ICU patients. By quantifying non-stationary rhythms, we identified diurnal and semi-diurnal oscillations varying in period and power according to delirium and deep sedation. Notably, HR exhibits a clear diurnal and semi-diurnal rhythm when delirium is absent. Overall, our framework supports the CWT as a powerful tool for analyzing complex physiological signals, particularly vital signs. Crucially, our findings suggest that cardiovascular rhythm disruption can be associated with ICU-related delirium and deep sedation.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Scientific Reports
○ 3612 papers in training set
Top 0.1%
31.1%
Similar papers in this journal
2
eBioMedicine
○ 183 papers in training set
Top 0.4%
5.5%
Similar papers in this journal
3
npj Digital Medicine
○ 118 papers in training set
Top 1%
5.2%
Similar papers in this journal
4
Critical Care
○ 15 papers in training set
Top 0.1%
4.3%
Similar papers in this journal
5
iScience
○ 1154 papers in training set
Top 4%
4.0%
Similar papers in this journal
50% of probability mass above
6
Journal of Medical Internet Research
◐ 87 papers in training set
Top 0.7%
3.4%
7
PLOS ONE
● 5266 papers in training set
Top 34%
3.4%
8
Nature Communications
○ 5641 papers in training set
Top 35%
3.2%
9
Computers in Biology and Medicine
○ 128 papers in training set
Top 1%
3.2%
10
Physiological Measurement
○ 14 papers in training set
Top 0.2%
2.4%
11
Frontiers in Neuroscience
○ 256 papers in training set
Top 2%
2.4%
12
Neurophotonics
● 42 papers in training set
Top 0.2%
2.1%
13
Critical Care Explorations
○ 14 papers in training set
Top 0.2%
2.0%
14
Frontiers in Physiology
○ 106 papers in training set
Top 1%
1.7%
15
Communications Biology
○ 993 papers in training set
Top 18%
1.4%
16
PLOS Computational Biology
● 1863 papers in training set
Top 16%
1.3%
17
Experimental Neurology
○ 61 papers in training set
Top 0.8%
1.3%
18
Advanced Science
○ 286 papers in training set
Top 7%
1.1%
19
Cell Reports Medicine
○ 153 papers in training set
Top 3%
1.1%
20
PLOS Digital Health
● 106 papers in training set
Top 4%
1.0%
21
Annals of Neurology
○ 64 papers in training set
Top 1%
1.0%
22
JAMIA Open
◐ 42 papers in training set
Top 2%
0.8%
23
CHEST
○ 14 papers in training set
Top 0.4%
0.8%
24
Journal of Infection
○ 78 papers in training set
Top 1%
0.8%
25
Communications Medicine
○ 113 papers in training set
Top 4%
0.8%
26
eClinicalMedicine
○ 77 papers in training set
Top 3%
0.6%
27
Frontiers in Microbiology
○ 427 papers in training set
Top 9%
0.6%
28
eLife
● 5828 papers in training set
Top 70%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.