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.