Richard Venn

Identifying the patient at risk of acute kidney injury: a predictive scoring system for the development of acute kidney injury in acute medical patients.

Background: Acute kidney injury (AKI) in hospitalized patients has significant implications in terms of morbidity and mortality, length of hospital stay and associated costs. To date, no interventions are proven to prevent the development of AKI but this is hampered in part by the lack of early recognition of patients at risk. We aimed to determine whether a simple system could be devised from both physiological and demographic data in order to identify individuals at increased risk from the development of inpatient AKI. Method: Our observational, population-based single-centred study took place in an 870-bed associated university hospital. All patients admitted to the acute medical admissions unit on the Worthing site of the Western Sussex Hospitals Trust during the study period were included. Results: Multivariate logistic regression analysis demonstrated that age, respiratory rate and disturbed consciousness together with a history of chronic kidney disease, diabetes mellitus, congestive cardiac failure and liver disease were associated with an increased risk of developing AKI within 7 days of admission. We derived a simple scoring system to identify acute medical patients at greater risk of developing AKI. Conclusions: The incidence of AKI complicating inpatient admissions remains high, however with the application of the derived AKI prediction score it is hoped that early recognition will translate to improved outcomes.

A validation of the National Early Warning Score to predict outcome in patients with COPD exacerbation

Background The National Early Warning Score (NEWS), proposed as a standardised track and trigger system, may perform less well in acute exacerbation of COPD (AECOPD). This study externally validated NEWS and modifications (Chronic Respiratory Early Warning Score (CREWS) and Salford-NEWS) in AECOPD. Methods An observational cohort study (2012–2014, two UK acute medical units (AMUs)), compared AECOPD (2361 admissions, 942 individuals, International Statistical Classification of Diseases and Related Health Problems-10 J40–J44 codes) with AMU patients (37u2005109 admissions, 20u2005415 individuals). Outcome In-hospital mortality prediction was done by admission NEWS, CREWS and Salford-NEWS assessed by discrimination (area under receiver operating characteristic curves (AUROCs)) and calibration (plots and Hosmer-Lemeshow (H-L) goodness-of-fit). Results Median admission NEWS in AECOPD was 4 (IQR 2–6) versus 1 (0–3) in AMUs (p≤0.001), despite mortality of 4.5% in both. AECOPD AUROCs were NEWS 0.74 (95% CI 0.66 to 0.82), CREWS 0.72 (0.63 to 0.80) and Salford-NEWS 0.62 (0.53 to 0.70). AMU NEWS AUROC was 0.77 (0.75 to 0.78). At threshold NEWS=5 for AECOPD (44% of admissions), positive predictive value (PPV) of death was 8% (5 to 11) and negative predictive value (NPV) was 98% (97 to 99) versus AMU patients PPV of 17% (16 to 19) and NPV of 97% (97 to 97). For NEWS in AECOPD H-L p value=0.202. Conclusion This first validation of the NEWS in AECOPD found modest discrimination to predict mortality. Lower specificity of NEWS in patients with AECOPD versus other AMU patients reflects acute and chronic respiratory physiological disturbance (including hypoxia), with resultant low PPV at NEWS=5. CREWS and Salford-NEWS, adjusting for chronic hypoxia, increased the specificity and PPV but there was no gain in discrimination.

Predicting AKI in emergency admissions: an external validation study of the acute kidney injury prediction score (APS)

Objectives Hospital-acquired acute kidney injury (HA-AKI) is associated with a high risk of mortality. Prediction models or rules may identify those most at risk of HA-AKI. This study externally validated one of the few clinical prediction rules (CPRs) derived in a general medicine cohort using clinical information and data from an acute hospitals electronic system on admission: the acute kidney injury prediction score (APS). Design, setting and participants External validation in a single UK non-specialist acute hospital (2013–2015, 12u2005554 episodes); four cohorts: adult medical and general surgical populations, with and without a known preadmission baseline serum creatinine (SCr). Methods Performance assessed by discrimination using area under the receiver operating characteristic curves (AUCROC) and calibration. Results HA-AKI incidence within 7u2005days (kidney disease: improving global outcomes (KDIGO) change in SCr) was 8.1% (n=409) of medical patients with known baseline SCr, 6.6% (n=141) in those without a baseline, 4.9% (n=204) in surgical patients with baseline and 4% (n=49) in those without. Across the four cohorts AUCROC were: medical with known baseline 0.65 (95% CIs 0.62 to 0.67) and no baseline 0.71 (0.67 to 0.75), surgical with baseline 0.66 (0.62 to 0.70) and no baseline 0.68 (0.58 to 0.75). For calibration, in medicine and surgical cohorts with baseline SCr, Hosmer-Lemeshow p values were non-significant, suggesting acceptable calibration. In the medical cohort, at a cut-off of five points on the APS to predict HA-AKI, positive predictive value was 16% (13–18%) and negative predictive value 94% (93–94%). Of medical patients with HA-AKI, those with an APS ≥5 had a significantly increased risk of death (28% vs 18%, OR 1.8 (95% CI 1.1 to 2.9), p=0.015). Conclusions On external validation the APS on admission shows moderate discrimination and acceptable calibration to predict HA-AKI and may be useful as a severity marker when HA-AKI occurs. Harnessing linked data from primary care may be one way to achieve more accurate risk prediction.

Exertional Heat Stroke – The Athlete's Nemesis

Heat stroke represents the extreme end of a spectrum of heat-related illnesses. It can occur in endurance athletes. Its incidence is probably under-reported. Patients present confused, drowsy or comatose, with a raised core temperature, but often a falsely reassuring peripheral temperature. Treatment is centred on reducing the core temperature as rapidly as possible and appropriate supportive management. Even with prompt treatment, it is associated with multi-organ dysfunction and death. Patients are often misdiagnosed, or diagnosed late. This is probably exacerbated by a wide differential diagnosis, the need for a core temperature measurement to reach the diagnosis and clinicians being unfamiliar with the disease. The need for immediate recognition, and immediate treatment compounds the problem. Survivors may experience long-term neurological disability and may be at risk of a further episode. Patients should return to sport gradually and only when they feel well. Its epidemiology, pathophysiology and clinical management are reviewed.

Systematic review of prognostic prediction models for acute kidney injury (AKI) in general hospital populations

Objective Critically appraise prediction models for hospital-acquired acute kidney injury (HA-AKI) in general populations. Design Systematic review. Data sources Medline, Embase and Web of Science until November 2016. Eligibility Studies describing development of a multivariable model for predicting HA-AKI in non-specialised adult hospital populations. Published guidance followed for data extraction reporting and appraisal. Results 14u2009046 references were screened. Of 53 HA-AKI prediction models, 11 met inclusion criteria (general medicine and/or surgery populations, 474u2009478 patient episodes) and five externally validated. The most common predictors were age (n=9 models), diabetes (5), admission serum creatinine (SCr) (5), chronic kidney disease (CKD) (4), drugs (diuretics (4) and/or ACE inhibitors/angiotensin-receptor blockers (3)), bicarbonate and heart failure (4 models each). Heterogeneity was identified for outcome definition. Deficiencies in reporting included handling of predictors, missing data and sample size. Admission SCr was frequently taken to represent baseline renal function. Most models were considered at high risk of bias. Area under the receiver operating characteristic curves to predict HA-AKI ranged 0.71–0.80 in derivation (reported in 8/11 studies), 0.66–0.80 for internal validation studies (n=7) and 0.65–0.71 in five external validations. For calibration, the Hosmer-Lemeshow test or a calibration plot was provided in 4/11 derivations, 3/11 internal and 3/5 external validations. A minority of the models allow easy bedside calculation and potential electronic automation. No impact analysis studies were found. Conclusions AKI prediction models may help address shortcomings in risk assessment; however, in general hospital populations, few have external validation. Similar predictors reflect an elderly demographic with chronic comorbidities. Reporting deficiencies mirrors prediction research more broadly, with handling of SCr (baseline function and use as a predictor) a concern. Future research should focus on validation, exploration of electronic linkage and impact analysis. The latter could combine a prediction model with AKI alerting to address prevention and early recognition of evolving AKI.

A comparison of the non-invasive ultrasonic cardiac output monitor (USCOM) with the oesophageal Doppler monitor during major abdominal surgery

Background Perioperative interventions, targeted to increase global blood flow defined by explicit measured goals, reduce postoperative complications. Consequently, reliable non-invasive estimation of the cardiac output could have far-reaching benefit. Methods This study compared a non-invasive Doppler device – the ultrasonic cardiac output monitor (USCOM) – with the oesophageal Doppler monitor (ODM), on 25 patients during major abdominal surgery. Stroke volume was determined by USCOM (SVUSCOM) and ODM (SVODM) pre and post fluid challenges. Results Au2009≥u200910% change (Δ) SVUSCOM had a sensitivity of 94% and specificity of 88% to detect au2009≥u200910% Δ SVODM; the area under the receiver operating curve was 0.94 (95% CI 0.90–0.99). Concordance was 98%, using an exclusion zone of <10% Δ SVODM. 135 measurements gave median SVUSCOM 80u2009ml (interquartile range 65–93u2009ml) and SVODM 86u2009ml (69–100u2009ml); mean bias was 5.9u2009ml (limits of agreement −20 to +30u2009ml) and percentage error 30%. Conclusions Following fluid challenges SVUSCOM showed good concordance and accurately discriminated a change ≥10% in SVODM.

An external validation study of a clinical prediction rule for medical patients with suspected bacteraemia

Objective The objective of this study was to externally validate a clinical prediction rule (CPR)—the ‘Shapiro criteria’—to predict bacteraemia in an acute medical unit (AMU). Methods Prospectively collected data, retrospectively evaluated over 11u2005months in an AMU in the UK. From 4810 admissions, 635 patients (13%) had blood cultures (BCs) performed. The 100 cases of true bacteraemia were compared with a randomly selected sample of 100 control cases where BCs were sterile. Results To predict bacteraemia (at a cut-off score of two points), the Shapiro criteria had a sensitivity of 97% (95% CIs 91% to 99%), specificity 37% (28% to 47%), positive likelihood ratio 1.54 (1.3 to 1.8) and a negative likelihood ratio of 0.08 (0.03 to 0.25). The area under the receiver operating curve was 0.80 (0.74 to 0.86), and the Hosmer–Lemeshow p value was 0.45. Conclusions A cut-off score of two points on the Shapiro criteria had high sensitivity to predict bacteraemia in a study of acute general medical admissions. Application of the rule in patients being considered for a BC could identify those at low risk of bacteraemia. Though the model demonstrated good discrimination, the lengthy number of variables (13) and difficulty automating the CPR may limit its use.

NHS reorganisations: who's kicking whom, who's protesting?: Where are the medical voices raised in protest: fit for the future?

EDITOR—Greener asks whether the medical profession approves of the governments reforms.1 We are consultants in acute medicine in West Sussex, a part of the Kent, Surrey, and Sussex Strategic Health Authority, which has recently attracted considerable interest about the possible restructuring of services. Not least are proposals to reduce the workload from primary care, which we are assured are supported by general practitioners. We conducted a simple survey to …

The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients

Background Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-acquired AKI (HA-AKI) and improve associated outcomes. Methods and findings A controlled before-and-after study included 30,295 acute medical admissions to two adult non-specialist hospital sites in the South of England (two ten-month time periods, 2014–16); all included patients stayed at least one night and had at least two serum creatinine tests. In the second period at the intervention site a CPR flagged those at risk of AKI and an alert was generated for those with AKI; both alerts incorporated care bundles. Patients were followed-up until death or hospital discharge. Primary outcome was change in incident HA-AKI. Secondary outcomes in those developing HA-AKI included: in-hospital mortality, AKI progression and escalation of care. On difference-in-differences analysis incidence of HA-AKI reduced (odds ratio [OR] 0.990, 95% CI 0.981–1.000, P = 0.049). In-hospital mortality in HA-AKI cases reduced on difference-in-differences analysis (OR 0.924, 95% CI 0.858–0.996, P = 0.038) and unadjusted analysis (27.46% pre vs 21.67% post, OR 0.731, 95% CI 0.560–0.954, P = 0.021). Mortality in those flagged by the CPR significantly reduced (14% pre vs 11% post intervention, P = 0.008). Outcomes for community-acquired AKI (CA-AKI) cases did not change. A number of process measures significantly improved at the intervention site. Limitations include lack of randomization, and generalizability will require future investigation. Conclusions In acute medical admissions a multi-modal intervention, including an electronically integrated CPR alongside an e-alert for those developing HA-AKI improved in-hospital outcomes. CA-AKI outcomes were not affected. The study provides a template for investigations utilising electronically generated prediction modelling. Further studies should assess generalisability and cost effectiveness. Trial registration Clinicaltrials.org NCT03047382.

NEWS 2 – too little evidence to implement?

ABSTRACT The Royal College of Physicians (RCP) recently published the National Early Warning Score 2 (NEWS2), aiming to improve safety for patients with hypercapnic respiratory failure by suggesting a separate oxygen saturation (SpO2) parameter scoring system for such patients. A previously published study of patients (n=2,361 admissions) with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) demonstrated alternative scoring systems at admission did not outperform the original NEWS. Applying NEWS2 SpO2 parameters to this previously described cohort would have resulted in 44% (n=27/62) of patients who scored ≥7 points on the original NEWS and subsequently died being placed in a lower call-out threshold. NEWS2 loses the benefits of a unified, standardised scoring system and we suggest prospective research in this area before applying this adjustment.