RESUMEN
Background: Surgical risk prediction tools can facilitate shared decision-making and efficient allocation of perioperative resources. Such tools should be externally validated in target populations before implementation. Methods: Predicted risk of 30-day mortality was retrospectively derived for surgical patients at Royal Perth Hospital from 2014 to 2021 using the Surgical Outcome Risk Tool (SORT) and the related NZRISK (n=44 031, 53 395 operations). In a sub-population (n=31 153), the Physiology and Operative Severity Score for the enumeration of Mortality (POSSUM) and the Portsmouth variant of this (P-POSSUM) were matched from the Copeland Risk Adjusted Barometer (C2-Ai, Cambridge, UK). The primary outcome was risk score discrimination of 30-day mortality as evaluated by area-under-receiver operator characteristic curve (AUROC) statistics. Calibration plots and outcomes according to risk decile and time were also explored. Results: All four risk scores showed high discrimination (AUROC) for 30-day mortality (SORT=0.922, NZRISK=0.909, P-POSSUM=0.893; POSSUM=0.881) but consistently over-predicted risk. SORT exhibited the best discrimination and calibration. Thresholds to denote the highest and second-highest deciles of SORT risk (>3.92% and 1.52-3.92%) captured the majority of deaths (76% and 13%, respectively) and hospital-acquired complications. Year-on-year SORT calibration performance drifted towards over-prediction, reflecting a decrease in 30-day mortality over time despite an increase in the surgical population risk. Conclusions: SORT was the best performing risk score in predicting 30-day mortality after surgery. Categorising patients based on SORT into low, medium (80-90th percentile), and high risk (90-100th percentile) might guide future allocation of perioperative resources. No tools were sufficiently calibrated to support shared decision-making based on absolute predictions of risk.
RESUMEN
BACKGROUND: Several international centres have published their experiences with outpatient autologous stem cell transplantation (ASCT) as treatment of haematological malignancies. AIM: In this single-centre retrospective review, we aim to examine the outcomes of outpatient autograft and review healthcare resource utilisation in the pre-cytopenic period. METHODS: Patients undergoing ASCT in Royal Hobart Hospital, Tasmania between 2008 and 2018 had their records reviewed and key outcomes data collected based on whether they received inpatient/outpatient ASCT. An outpatient ASCT was defined as conditioning as an outpatient; patients could then be managed with an elective admission during the cytopenic period or admission only when clinically indicated. RESULTS: Of 231 ASCT performed, 135 (58%) were as outpatients: 59 used carmustine-etoposide-cytarabine-melphalan conditioning for lymphoma (BEAM-ASCT) and 76 used high-dose melphalan for myeloma and amyloidosis (MEL-ASCT). Approximately one-third of patients undergoing outpatient ASCT were admitted electively during nadir period; the majority of patients required minimal interventions prior to this time. The most common causes for unplanned hospitalisation (which occurred in 71 (80%) of the 89 planned outpatient transplants) were febrile neutropenia (39%) and mucositis (35%). Age was the only risk factor identified to increase risk of requiring unplanned hospitalisation. Use of oral antibiotic prophylaxis reduced febrile neutropenia rates among melphalan outpatient ASCT. Outpatient ASCT led to significantly reduced inpatient bed-days and overall cost (approximately A$13 000-A$16 000) compared with inpatient autografts, with no significant differences in engraftment, rates of febrile neutropenia, intensive care admissions or mortality. CONCLUSION: Outpatient autografts may save healthcare resources without compromising patient outcomes.