Objective: To assess the outcomes of appendicectomy in an acute care surgery (ACS) model compared with a traditional on‐call (Trad) model. Design: Retrospective historical control study comparing appendicectomy outcomes in the Trad period (April 2004 to March 2005) with outcomes in the ACS period (April 2006 to March 2007). Setting: The Prince of Wales Public Hospital, a metropolitan tertiary referral centre in Sydney. Patients: All adult patients undergoing appendicectomy during 1‐year periods before and after the introduction of the ACS model. Intervention: The introduction of an ACS model for managing all emergency general surgical presentations. Main outcome measure: Complication rate. Results: A total of 402 appendicectomies were performed, 176 during the Trad period and 226 during the ACS period. There was no perioperative mortality. The complication rate was lower in the ACS period than the Trad period (9.3% v 17.0%; P = 0.02). After the intervention, there was no significant change in the time from presentation to arrival in theatre or in length of stay, but the proportion of operations performed at night (24:00–08:00) was reduced from 26.1% to 15.0% (P = 0.006). The proportion of negative appendicectomies was reduced from 22.7% to 17.3%, but the change was not statistically significant (P = 0.08). There was no difference in perforation rate before and after the intervention (13.6% v 13.3%; P = 0.86). Conclusion: The ACS model provides a safe surgical environment for patients and is associated with a reduced complication rate. Under the ACS model, there was an increase in the number of patients treated conservatively overnight, but this did not lead to an overall increase in perforation rate or length of stay.

Background and aims:The serum/plasma proteome was explored for biomarkers to improve the diagnostic ability of CA19-9 in pancreatic adenocarcinoma (PC).Methods:A Training Set of serum samples from 20 resectable and 18 stage IV PC patients, 54 disease controls (DCs) and 68 healthy volunteers (HVs) were analysed by surface-enhanced laser desorption and ionisation time-of-flight mass spectrometry (SELDI-TOF MS). The resulting protein panel was validated on 40 resectable PC, 21 DC and 19 HV plasma samples (Validation-1 Set) and further by ELISA on 33 resectable PC, 28 DC and 18 HV serum samples (Validation-2 Set). Diagnostic panels were derived using binary logistic regression incorporating internal cross-validation followed by receiver operating characteristic (ROC) analysis.Results:A seven-protein panel from the training set PC vs DC and from PC vs HV samples gave the ROC area under the curve (AUC) of 0.90 and 0.90 compared with 0.87 and 0.91 for CA19-9. The AUC was greater (0.97 and 0.99, P<0.05) when CA19-9 was added to the panels and confirmed on the validation-1 samples. A simplified panel of apolipoprotein C-I (ApoC-I), apolipoprotein A-II (ApoA-II) and CA19-9 was tested on the validation-2 set by ELISA, in which the ROC AUC was greater than that of CA19-9 alone for PC vs DC (0.90 vs 0.84) and for PC vs HV (0.96 vs 0.90).Conclusions:A simplified diagnostic panel of CA19-9, ApoC-I and ApoA-II improves the diagnostic ability of CA19-9 alone and may have clinical utility.

Background frailty is a major contributor to poor health outcomes in older people, separate from age, sex and comorbidities. This population-based validation study evaluated the performance of the International Classification of Diseases, 10th revision, coded Hospital Frailty Risk Score (HFRS) in the prediction of adverse outcomes in an older surgical population and compared its performance against the commonly used Charlson Comorbidity Index (CCI). Methods hospitalisation and death data for all individuals aged ≥50 admitted for surgery to New South Wales hospitals (2013–17) were linked. HFRS and CCI scores were calculated using both 2- and 5-year lookback periods. To determine the influence of individual explanatory variables, several logistic regression models were fitted for each outcome of interest (30-day mortality, prolonged length of stay (LOS) and 28-day readmission). Area under the receiving operator curve (AUC) and Akaike information criterion (AIC) were assessed. Results of the 487,197 patients, 6.8% were classified as high HFRS, and 18.3% as high CCI. Although all models performed better than base model (age and sex) for prediction of 30-day mortality, there was little difference between CCI and HFRS in model discrimination (AUC 0.76 versus 0.75), although CCI provided better model fit (AIC 79,020 versus 79,910). All models had poor ability to predict prolonged LOS (AUC range 0.62–0.63) or readmission (AUC range 0.62–0.65). Using a 5-year lookback period did not improve model discrimination over the 2-year period. Conclusions adjusting for HFRS did not improve prediction of 30-mortality over that achieved by the CCI. Neither HFRS nor CCI were useful for predicting prolonged LOS or 28-day unplanned readmission.