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Existing Predictive Models for Postoperative Pulmonary Complications Perform Poorly in a Head and Neck Surgery Population

  • Systems-Level Quality Improvement
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Abstract

Postoperative pulmonary complications (PPCs) are common following major surgical procedures. Risk stratification tools have been developed to identify patients at risk for PPCs. While otolaryngology cases were included in the development of common predictive tools, they comprised small percentages in each tool. It is unclear how these tools perform in patients undergoing major head and neck surgery with free flap reconstruction. This retrospective review studied all free flap reconstructions in head and neck surgery over a 12-year period at a single institution in the southeastern US. Baseline demographic and medical information were included for each case. All cases were reviewed for development of major PPCs, including pneumonia and respiratory failure. The cohort underwent risk stratification using the ARISCAT and Gupta pulmonary risk indices. Performance of these predictive models for head and neck surgery was determined through receiver-operator curve comparison. 794 patients were identified with a median age of 62 years (IQR 41–83). Sixty-five percent were male. Forty-three (5.4%) developed pneumonia, 23 patients developed respiratory failure (2.9%), and 38 patients developed both (4.8%), resulting in a total PPC proportion of 13.1% (n = 104). Both ARISCAT and Gupta pulmonary risk indices demonstrated low discrimination to predict PPCs in head and neck free flap reconstruction, with areas under the curve of 0.60 and 0.65, respectively. Two major indices for prediction of postoperative pulmonary complications do not accurately identify risk in patients undergoing major head and neck surgery. Further studies are needed to develop predictive tools for PPCs in this high-risk population.

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Funding

The authors did not receive any funding specifically for this work. Dr. Freundlich receives ongoing grant support from a KL2 from the Vanderbilt Faculty Research Scholars.

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Author notes

  1. C. Burton Wood and Justin R. Shinn contributed equally to this work.

Authors and Affiliations

  1. Department of Otolaryngology–Head and Neck Surgery, Vanderbilt University Medical Center, 1215 21st Avenue South, Nashville, TN, USA

    C. Burton Wood, Justin R. Shinn, Priyesh N. Patel & Sarah L. Rohde

  2. Vanderbilt University School of Medicine, Nashville, TN, USA

    Andrew B. Rees

  3. Department of Anesthesiology, Vanderbilt University Medical Center, 1215 21st Avenue South, Nashville, TN, USA

    Robert E. Freundlich & Matthew D. McEvoy

  4. Department of Biomedical Informatics, Vanderbilt University Medical Center, 1215 21st Avenue South, Nashville, TN, USA

    Derek K. Smith

  5. Department of Oral and Maxillofacial Surgery, Vanderbilt University Medical Center, 1215 21st Avenue South, Nashville, TN, USA

    Derek K. Smith

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  1. C. Burton Wood
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  2. Justin R. Shinn
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Correspondence to C. Burton Wood.

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None of the authors have any conflicts of interest applicable to this study.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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The need for informed consent was waived by the local institutional review board given the retrospective nature of the study.

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Wood, C.B., Shinn, J.R., Rees, A.B. et al. Existing Predictive Models for Postoperative Pulmonary Complications Perform Poorly in a Head and Neck Surgery Population. J Med Syst 43, 312 (2019). https://doi.org/10.1007/s10916-019-1435-x

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  • DOI: https://doi.org/10.1007/s10916-019-1435-x

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