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Abstract: SA-PO148

Using Standardised Monitoring of Physiological Parameters (National Early Warning Score) to Predict AKI

Session Information

Category: Acute Kidney Injury

  • 102 AKI: Clinical, Outcomes, and Trials

Authors

  • Riding, Alexandra, East and North Herts NHS Trust, Stevenage, United Kingdom
  • Berresford, Kate, East and North Herts NHS Trust, Stevenage, United Kingdom
  • Morlidge, Clare, East and North Herts NHS Trust, Stevenage, United Kingdom
  • Mathavakkannan, Suresh, East and North Herts NHS Trust, Stevenage, United Kingdom
  • Findlay, Andrew, East and North Herts NHS Trust, Stevenage, United Kingdom
Background

Acute kidney injury (AKI) affects approximately 16% of inpatients, particularly the elderly and confers an increased length of hospital stay, medical intervention and mortality (Holmes et al, CJASN, 2016 and Kerr et al, NDT, 2014). Risk factors are well established and yet we cannot reliably identify susceptible patients before abnormal serum creatinine results, though this forms the basis of national AKI e-alert systems.
In 2012, The Royal College of Physicians endorsed a National Early Warning Score (NEWS) to identify deteriorating and acutely unwell patients. The score is based on the physiological parameters of respiratory rate, oxygen saturation, systolic blood pressure, pulse rate, conscious level and temperature, with higher scores triggering urgent or immediate medical escalation. The utility of clinical early warning scores in predicting AKI severity and patient outcome has been variable (Kovacs et al, BJS, 2016; Potter et al, JICS, 2017 and Faisal et al, Clin Med, 2018).

We predicted that those with high NEWS (>4) might correlate to AKI stage and form a useful pathway to highlight and appropriately escalate this patient group.

Methods

Retrospective data were collected on hospitalized patients (Jan-March 2019), identified by elevated serum creatinine results (as per national AKI reporting guidance). Highest NEWS within 5 days of AKI alert was recorded. Data sources were patient records and computerized reporting systems.

Results

140 patients were identified (complete data for 138). NEWS is shown according to AKI stage in the table. Higher NEWS (>4) was unaffected by AKI stage (p= 0.75, 2-way ANOVA).

Conclusion

Those with stage 2 and 3 AKI did not trigger significantly higher NEWS. Whilst NEWS remains an important discriminator in escalating acutely unwell patients, it did not predict AKI or its severity. Biomarkers of AKI are in development, but clinically relevant discriminators remain elusive. Further parameters are urgently required to refine AKI alert algorithms for clinical use.

NEWS according to AKI stage
AKI stage (n=patients)NEWS 0-4 (%)NEWS 5-6 (%)NEWS 7+ (%)
1 (63)38 (60)11 (17)14 (22)
2 (52)24 (46)10 (19)18 (35)
3 (23)10 (43)8 (35)5 (22)