The impact of complications on prolonged length of hospital stay after resection in colorectal cancer: A retrospective study of Taiwanese patients

Herng-Chia Chiu, Yi-Chieh Lin, Hui-Min Hsieh, Hsin-Pao Chen, Hui-Li Wang, Jaw-Yuan Wang, Herng-Chia Chiu, Yi-Chieh Lin, Hui-Min Hsieh, Hsin-Pao Chen, Hui-Li Wang, Jaw-Yuan Wang

Abstract

Objectives To assess the impact of minor, major and individual complications on prolonged length of hospital stay in patients with colorectal cancer (CRC) after surgery using multivariate models. Methods This was a retrospective review of data from patients who underwent surgery for stage I-III CRC at two medical centres in southern Taiwan between 2005-2010. Information was derived from four databases. Multivariate logistic regression methods were used to assess the impact of complications on prolonged length of stay (PLOS) and prolonged postoperative length of stay (PPOLOS). Results Of 1658 study patients, 251 (15.1%) experienced minor or major postsurgical complications during hospitalizations. Minor and major complications were significantly associated with PLOS (minor, odds ratio [OR] 3.59; major, OR 8.82) and with PPOLOS (minor, OR 5.55; major, OR 10.00). Intestinal obstruction, anastomosis leakage, abdominal abscess and bleeding produced the greatest impact. Conclusions Minor and major complications were stronger predictors of prolonged hospital stay than preoperative demographic and disease parameters. Compared with the PLOS model, the PPOLOS model better predicted risk of prolonged hospital stay. Optimal surgical and medical care have major roles in surgical CRC patients.

Keywords: Complications; Taiwan; colorectal cancer; prolonged length of stay (PLOS); prolonged postoperative length of stay (PPOLOS).

Figures

Figure 1.
Figure 1.
Forest plot of the multivariate logistic regression model used for predicting the effect of minor and major complications on prolonged length of stay (PLOS). The model was adjusted for patient, disease-related and treatment-related characteristics and death index hospitalization. Due to space limitation, variables with 95% confidence intervals > 30 times are presented with an arrowhead in the right tale (i.e. abdominal abscess).
Figure 2.
Figure 2.
Forest plot of the multivariate logistic regression model used for predicting the effect of minor and major complications on prolonged postoperative length of stay (PPLOS). The model was adjusted for patient, disease-related and treatment-related characteristics and death index hospitalization. Due to space limitation, variables with 95% confidence intervals > 30 times are presented with an arrowhead in the right tale (i.e. intestinal obstruction, anastomosis leakage, abdominal abscess, and bleeding).

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