A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Hospital discharge diagnostic and procedure codes for upper gastro-intestinal cancer: how accurate are they?

<p>Abstract</p> <p>Background</p> <p>Population-level health administrative datasets such as hospital discharge data are used increasingly to evaluate health services and outcomes of care. However information about the accuracy of Australian discharge data in identifying cancer, associated procedures and comorbidity is limited. The Admitted Patients Data Collection (APDC) is a census of inpatient hospital discharges in the state of New South Wales (NSW). Our aim was to assess the accuracy of the APDC in identifying upper gastro-intestinal (upper GI) cancer cases, procedures for associated curative resection and comorbidities at the time of admission compared to data abstracted from medical records (the ‘gold standard’).</p> <p>Methods</p> <p>We reviewed the medical records of 240 patients with an incident upper GI cancer diagnosis derived from a clinical database in one NSW area health service from July 2006 to June 2007. Extracted case record data was matched to APDC discharge data to determine sensitivity, positive predictive value (PPV) and agreement between the two data sources (κ-coefficient).</p> <p>Results</p> <p>The accuracy of the APDC diagnostic codes in identifying site-specific incident cancer ranged from 80-95% sensitivity. This was comparable to the accuracy of APDC procedure codes in identifying curative resection for upper GI cancer. PPV ranged from 42-80% for cancer diagnosis and 56-93% for curative surgery. Agreement between the data sources was >0.72 for most cancer diagnoses and curative resections. However, APDC discharge data was less accurate in reporting common comorbidities - for each condition, sensitivity ranged from 9-70%, whilst agreement ranged from κ = 0.64 for diabetes down to κ < 0.01 for gastro-oesophageal reflux disorder.</p> <p>Conclusions</p> <p>Identifying incident cases of upper GI cancer and curative resection from hospital administrative data is satisfactory but under-ascertained. Linkage of multiple population-health datasets is advisable to maximise case ascertainment and minimise false-positives. Consideration must be given when utilising hospital discharge data alone for generating comorbidity indices, as disease burden at the time of admission is under-reported.</p

Mortality after surgery in Europe: a 7 day cohort study

Background: Clinical outcomes after major surgery are poorly described at the national level. Evidence of heterogeneity between hospitals and health-care systems suggests potential to improve care for patients but this potential remains unconfirmed. The European Surgical Outcomes Study was an international study designed to assess outcomes after non-cardiac surgery in Europe.Methods: We did this 7 day cohort study between April 4 and April 11, 2011. We collected data describing consecutive patients aged 16 years and older undergoing inpatient non-cardiac surgery in 498 hospitals across 28 European nations. Patients were followed up for a maximum of 60 days. The primary endpoint was in-hospital mortality. Secondary outcome measures were duration of hospital stay and admission to critical care. We used χ² and Fisher’s exact tests to compare categorical variables and the t test or the Mann-Whitney U test to compare continuous variables. Significance was set at p&lt;0·05. We constructed multilevel logistic regression models to adjust for the differences in mortality rates between countries.Findings: We included 46 539 patients, of whom 1855 (4%) died before hospital discharge. 3599 (8%) patients were admitted to critical care after surgery with a median length of stay of 1·2 days (IQR 0·9–3·6). 1358 (73%) patients who died were not admitted to critical care at any stage after surgery. Crude mortality rates varied widely between countries (from 1·2% [95% CI 0·0–3·0] for Iceland to 21·5% [16·9–26·2] for Latvia). After adjustment for confounding variables, important differences remained between countries when compared with the UK, the country with the largest dataset (OR range from 0·44 [95% CI 0·19 1·05; p=0·06] for Finland to 6·92 [2·37–20·27; p=0·0004] for Poland).Interpretation: The mortality rate for patients undergoing inpatient non-cardiac surgery was higher than anticipated. Variations in mortality between countries suggest the need for national and international strategies to improve care for this group of patients.Funding: European Society of Intensive Care Medicine, European Society of Anaesthesiology