Preoperative identification of neurosurgery patients with a high risk of in-hospital complications: a prospective cohort of 418 consecutive elective craniotomy patients.

OBJECT

Patients undergoing craniotomy are routinely assessed preoperatively, yet the role of these assessments in predicting outcome is poorly studied. This study aimed to identify preoperative factors predicting in-hospital outcome after cranial neurosurgery.

METHODS

The study cohort consisted of 418 consecutive adults undergoing elective craniotomy for any intracranial lesion. Apart from the age criteria (≥ 18 years), almost all patients were considered eligible for the study to increase external validity of the results. The studied preoperative assessments included various patient-related data, routine blood tests, American Society of Anesthesiologists (ASA) Physical Status Classification system, and a local modification of the ASA classification (Helsinki ASA classification). Adverse outcomes were in-hospital mortality, in-hospital systemic or infectious complications, and in-hospital CNS deficits. Resource use was defined as length of stay (LOS) in the intensive care unit and overall LOS in the hospital.

RESULTS

The in-hospital mortality rate was 1.0%. In-hospital systemic or infectious complications and permanent or transient CNS deficits occurred in 6.7% and 11.2% of the patients, respectively. Advanced age (≥ 60-65 years), elevated C-reactive protein level (> 3 mg/L), and high Helsinki ASA score (Class 4) were associated with in-hospital systemic and infectious complications, and a combination of these could identify one-fourth of the patients with postoperative complications. Moreover, this combination of preoperative assessment parameters was significantly associated with increased resource use.

CONCLUSIONS

In this first prospective and unselected cohort study of outcome after elective craniotomy, simple preoperative assessments identified patients with a high risk of in-hospital systemic or infectious complications as well as extended resource use. Presented risk assessment methods may be widely applicable, also in low-volume centers, as they are based on composite predictors and outcome events.