Background Postoperative delirium is a common complication in surgical patients, and is associated with a multitude of negative outcomes, including mortality, dementia, and increased healthcare costs. Therefore, a better understanding of what factors contribute to postoperative delirium, especially those that can be easily obtained, is important.

Methods We conducted a retrospective cohort study using patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Adult patients undergoing procedures in abdominal surgery who did not have pre-existing delirium were included in the study. Overall, we included 8022 procedures across 7212 patients. For each admission, we extracted values obtained from common blood tests, the Charlson and Elixhauser comorbidity score, and patient demographic information. We used stepwise logistic regression to identify predictive factors of postoperative delirium in this cohort.

Results The model isolated factors well known to be associated with postoperative delirium, such as age, comorbidity (as represented by the Elixhauser comorbidity score), and Parkinson’s disease. The model also selected variables that are less studied, such as minimum preoperative platelets and maximum preoperative sodium levels. We hypothesize that the former is associated with postoperative delirium as a surrogate marker for inflammation as an acute phase reactant, and the second due to it being a marker for cerebral edema and altered neurotransmission.

Conclusion Preoperative blood tests contain valuable information that can be used alongside patient demographics and past medical history to better predict the risk of postoperative delirium.

The authors have declared no competing interest.

This study did not receive any funding

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The data analyzed in this study were obtained from the MIMIC-IV database (version 3.1). Access to MIMIC-IV requires completion of human subjects research training and data use agreement through PhysioNet. Due to data use restrictions, the raw clinical data cannot be publicly shared by the authors, but qualified researchers may request access directly from PhysioNet (https://physionet.org/content/mimiciv/3.1/) under the same terms.

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The data analyzed in this study were obtained from the MIMIC-IV database (version 3.1). Access to MIMIC-IV requires completion of human subjects research training and data use agreement through PhysioNet. Due to data use restrictions, the raw clinical data cannot be publicly shared by the authors, but qualified researchers may request access directly from PhysioNet (https://physionet.org/content/mimiciv/3.1/) under the same terms.

https://physionet.org/content/mimiciv/3.1/