Perioperative factors associated with pressure ulcer development after major surgery

Abstract

Background: Postoperative pressure ulcers are important indicators of perioperative care quality, and are serious and expensive complications during critical care. This study aimed to identify perioperative risk factors for postoperative pressure ulcers.

Methods: This retrospective case-control study evaluated 2,498 patients who underwent major surgery. Forty-three patients developed postoperative pressure ulcers and were matched to 86 control patients based on age, sex, surgery, and comorbidities.

Results: The pressure ulcer group had lower baseline hemoglobin and albumin levels, compared to the control group. The pressure ulcer group also had higher values for lactate levels, blood loss, and number of packed red blood cell (pRBC) units. Univariate analysis revealed that pressure ulcer development was associated with preoperative hemoglobin levels, albumin levels, lactate levels, intraoperative blood loss, number of pRBC units, Acute Physiologic and Chronic Health Evaluation II score, Braden scale score, postoperative ventilator care, and patient restraint. In the multiple logistic regression analysis, only preoperative low albumin levels (odds ratio [OR]: 0.21, 95% CI: 0.05-0.82; P < 0.05) and high lactate levels (OR: 1.70, 95% CI: 1.07-2.71; P < 0.05) were independently associated with pressure ulcer development. A receiver operating characteristic curve was used to assess the predictive power of the logistic regression model, and the area under the curve was 0.88 (95% CI: 0.79-0.97; P < 0.001).

Conclusions: The present study revealed that preoperative low albumin levels and high lactate levels were significantly associated with pressure ulcer development after surgery.

Keywords: Albumin; Lactate; Perioperative risk factors; Pressure ulcer.

Fig. 1. Patient flow chart.

Fig. 2. Kaplan-Meier survival curves of no pressure ulcer group (straight line, n = 86) and pressure ulcer group (dotted line, n = 43) postoperative pressure ulcer. Patient in the pressure ulcer group had a significantly lower survival rate (90-day predictive mortality rate, 33.6% vs. 4.7%; 1-year predictive mortality rate, 40.3% vs. 8.6%; both P < 0.001).

Fig. 3. Nomogram to predict the probability of postoperative pressure ulcer (Top). Points are obtained according to the prognostic contribution of parameters (Bottom). Points are translated to the probability of requiring postoperative pressure ulcer. Predictor points are found on the uppermost point scale that corresponds to each individual variable. The reader then manually sums the points, and the predicted values can be read at the bottom of the nomogram. The total projected on the bottom scale indicates the probability of postoperative pressure ulcer. For example, a patient is admitted to the ICU after major surgery. Preoperative laboratory data shows that albumin is 3.0 g/dl and lactate is 4.0 mmol/L. During the surgery, 20 units of packed RBC units are transfused. Postoperatively, he is transferred to ICU and needed a mechanical ventilator support for a while. At that time, Braden scale assessed by a nurse is 20. In this case, the incidence of postoperative pressure ulcer is expected as much as 60% by using this nomogram. Therefore, clinician and nursing practioners should be more concerned to prevent pressure ulcer for this patient.

Fig. 4. Internal validation of the nomogram to predict postoperative pressure ulcer. Predictive accuracy of the model (nomogram): the frequencies of predicted and actual incidence of postoperative pressure ulcer are plotted as observations. Logistic calibration for the training set: calibration plot P = 1; E, difference in predicted and calibrated probabilities between calibration and AUC; E average = 3.02%.