Why the study?
Data were minimal for emergency laparotomy patients in Australia, prompting an assessment of the utility and applicability of the UK NELA model in an Australian tertiary centre.
Does the NELA prognostic model accurately predict hospital mortality in patients undergoing emergency laparotomy in an Australian tertiary centre?
Does the NELA prognostic model accurately predict hospital mortality in patients undergoing emergency laparotomy in an Australian tertiary centre?
The NELA prognostic model is a reliable screening tool for identifying high-risk patients requiring emergency laparotomy in an Australian setting, though it may overestimate mortality at very high predicted risks.
Supports NELA for risk stratification in Australian emergency laparotomy; leaves open need for local recalibration at high predicted risks.
The Royal College of Anaesthetists was commissioned by the United Kingdom Health Quality Partnership to conduct the National Emergency Laparotomy Audit of England and Wales (NELA), to compare outcomes of patients undergoing emergency laparotomy in order to promote quality improvement. Prior to 2016 there were minimal data for emergency laparotomy patients in Australia. The aim of this cohort study was to assess the utility and applicability of the NELA model in a tertiary centre in Western Australia. NELA-related data of patients who underwent emergency laparotomy, between June 2018 and May 2020, were merged with other administrative databases and clinical records. The discriminative ability and calibration of the model were assessed by the area under the receiver operating characteristic (AUROC) curve and calibration plot, respectively. Cox proportional hazards regression was used to assess whether the NELA-predicted risks were an independent predictor of hospital mortality. Of the 502 patients included, 168 (33.5%) patients had a NELA-predicted risk >10%, and of these, 93 (55.4%) were admitted to a critical care unit in a planned fashion immediately after surgery. The NELA model had a good ability to discriminate between survivors and non-survivors (AUROC 0.892, 95% confidence intervals 0.854 to 0.93, P <0.001). However, the model was not perfectly calibrated, with the predicted risks tending to overestimate the observed risks of mortality, especially when the predicted risks were >50%. A high NELA-predicted risk remained significantly associated with mortality after adjusting for other covariates, including sepsis and plasma lactate concentration, suggesting that it is a reliable screening tool for identifying high-risk patients requiring emergency laparotomy.
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Tran et al. (2022) studied this question.
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