BMC Surgery (Sep 2021)

Application of an index derived from the area under a neutrophil curve as a predictor of surgical site infection after spinal surgery

  • Hiroyuki Inose,
  • Yutaka Kobayashi,
  • Shingo Morishita,
  • Yu Matsukura,
  • Masato Yuasa,
  • Takashi Hirai,
  • Toshitaka Yoshii,
  • Atsushi Okawa

DOI
https://doi.org/10.1186/s12893-021-01345-6
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 8

Abstract

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Abstract Background Patients with prolonged and intense neutrophilia after spinal surgery are at high risk of developing surgical site infection (SSI). To date, there is no standard method for the objective assessment of the intensity and duration of neutrophilia. Thus, this retrospective observational study aimed to test a new index (I-index), developed by combining the duration and intensity of neutrophilia, as a predictor of SSI. Methods I-index was calculated based on the postoperative neutrophil percentage. A total of 17 patients with SSI were enrolled as cases, and 51 patients without SSI were selected as controls. The groups were matched at a ratio of 1:3 by age, sex, and surgery type. The differences in the I-index were compared between the groups. Moreover, we checked the cumulative I-index (c-I-index), which we defined as the area under the neutrophil curve from postoperative day 1 until the first clinical manifestation of SSI in each case. Furthermore, a cutoff for SSI was defined using the receiver operating characteristic curve. Results The median I-index-7, I-index-14, and c-I-index were significantly higher in the SSI group than those in the control group. For a cutoff point of 42.1 of the I-index-7, the sensitivity and specificity were 0.706 and 0.882, respectively. For a cutoff point of 45.95 of the I-index-14, the sensitivity and specificity were 0.824 and 0.804, respectively. For a cutoff point of 45.95 of the c-I-index, the sensitivity and specificity were 0.824 and 0.804, respectively. Conclusion We devised a new indicator of infection, i.e., the I-Index and c-I-index, and confirmed its usefulness in predicting SSI.

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