Predicting Hospital-Acquired Acute Kidney Injury—A Case-Controlled Study

Drawz, Paul; Miller, R. Tyler; Sehgal, Ashwini R.

doi:10.1080/08860220802356515

Cited by 26 publications

(22 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A summary of the observed and predicted frequency of hAKI with each quintile of risk is shown ( Figure 2B). (29) 278 (23) 266 (22) 203 (16) 199 (16) 156 (13) 149 (12) 113 (9) 85 7Medication (n, %): 25298 (24) 285 (23) 223 (18) 196 (16) 159 (13) 94 (8) 76 (6) 51 (4) Observations (median, IQR): Unknown 309 (27) 278 (24) 286 (25) 263 232 012 (12) 31 3228 (29) 26 (27) 0 (0) 322 (28) 252 (22) 219 (19) 176 (15) 179 (16) 128 (11) 136 (12) 106 (9) 76 746 4638 3926 (27) 47 ( 262 (23) 258 (23) 205 (18) 179 (16) 150 (13) 47 ( 25280 (25) 284 (25)<...>…”

Section: Outcomes and Data Collectionmentioning

confidence: 99%

“…AKI in this group can be divided into those who have already sustained AKI at hospital admission (community-acquired AKI, cAKI) and those who sustain AKI during their hospital stay (hospital-acquired AKI, hAKI); efforts to reduce AKI risk at time of hospital admission will have direct relevance only to hAKI (6). There are many well-described factors that increase the risk of AKI including age, presence of co-morbidities, sepsis, previous AKI and certain prescribing patterns, but these have not been extensively studied in the specific setting of acutely unwell medical patients (7,8). Moreover, international AKI guidelines, including those from the National Institute for Health and Care Excellence (NICE, CG169), state that patients with acute illness and who have one or more of these factors should be regarded as being at higher risk (9).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Risk prediction for acute kidney injury in acute medical admissions in the UK

Blackburn

Gunda²,

Lopez

et al. 2018

QJM: An International Journal of Medicine

View full text Add to dashboard Cite

Background Acute Kidney Injury (AKI) is associated with adverse outcomes; identifying patients who are at risk of developing AKI in hospital may lead to targeted prevention. This approach is advocated in national guidelines but is not well studied in acutely unwell medical patients. We therefore aimed to undertake a UK-wide study in acute medical units (AMUs) with the following aims: to define the proportion of acutely unwell medical patients who develop hospital-acquired AKI (hAKI); to determine risk factors associated with the development of hAKI; and to assess the feasibility of using these risk factors to develop an AKI risk prediction score. Methods In September 2016, a prospective multicentre cohort study across 72 UK AMUs was undertaken. Data were collected from all patients who presented over a 24-hour period. Chronic dialysis, community-acquired AKI (cAKI) and those with fewer than two creatinine measurements were subsequently excluded. The primary outcome was the development of h-AKI. Results 2,446 individuals were admitted to the AMUs of the 72 participating centres. 384 patients (16%) sustained AKI of whom 287 (75%) were cAKI and 97 (25%) were hAKI. After exclusions, 1,235 participants remained in whom chronic kidney disease (OR 3.08, 95% CI 1.96-4.83), diuretic prescription (OR 2.33, 95% CI 1.5-3.65), a lower haemoglobin concentration and an elevated serum bilirubin were independently associated with development of hAKI. Multivariable model discrimination was moderate (c-statistic 0.75), and this did not support the development of a robust clinical risk prediction score. Mortality was higher in those with hAKI (adjusted OR 5.22; 95% CI 2.23-12.20). Conclusion AKI in AMUs is common and associated with worse outcomes, with the majority of cases community acquired. The smaller proportion of hAKI cases, only moderate discrimination of prognostic risk factor modelling and the resource implications of widespread application of an AKI clinical risk score across all AMU admissions suggests that this approach is not currently justified. More targeted risk assessment or automated methods of calculating individual risk may be more appropriate alternatives.

show abstract

Section: Outcomes and Data Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk prediction for acute kidney injury in acute medical admissions in the UK

Blackburn

Gunda²,

Lopez

et al. 2018

QJM: An International Journal of Medicine

View full text Add to dashboard Cite

show abstract

“…The nephrotoxic potential of these drugs, diuretics, NSAIDs, ARBs and ACE inhibitors, is well known. Drawz et al developed a predictive score for hospital-acquired AKI, classifying the use of these drugs as a risk factor with an OR of 2 22. Different authors have recommended that the use of NSAIDs should be avoided in patients with kidney disease stages 4 or 5 23.…”

Section: Discussionmentioning

confidence: 99%

Improvement of drug prescribing in acute kidney injury with a nephrotoxic drug alert system

et al. 2017

View full text Add to dashboard Cite

ObjectiveElectronic alert systems have shown their capacity for improving the detection of acute kidney injury (AKI). The aim of this study was to design and implement a clinical decision support system (CDSS) for improving drug selection and reducing nephrotoxic drug use in patients with AKI.MethodsThe study was designed as an intervention study comparing a pre and post cohort of patients admitted during April 2014 and April 2015, respectively (phase I and phase II). The intervention was a CDSS which provided kidney function and nephrotoxic drug information. Furthermore, an interruptive alert was designed to detect patients suffering an AKI event while taking a nephrotoxic drug and to see if the dose was then reduced or the drug was discontinued by the physicians.ResultsOne-third of the inpatients were included in the analysis because they met the inclusion criteria (1004 and 1002 patients in phases I and II, respectively). 735 and 761 of them received at least one nephrotoxic alert (73% vs 76%; p=0.763). 65 and 88 patients suffered AKI during admission (6.5% vs 8.8%; p=0.051). In phase I, patients received 384 nephrotoxic alerts (55%) with 78 (20%) of them provoking a change or discontinuation of the nephrotoxic drug. In phase II this value increased to 154 out of 526 (29%) after implementation of the CDSS (p<0.01).ConclusionsA CDSS with interruptive alerts that inform of the development of AKI in real time in patients with nephrotoxic drug prescription has a positive impact on the judicious use of these drugs.

show abstract

“…The many risk factors that exist at the ICU stage for donors, including hypotension, pulmonary disease, liver failure, sepsis, hypovolemia, heart failure, bleach injection, and many medications (for example, ACE inhibitors, vasopressors, aminoglycosides, and NSAIDs), can lead to development of AKI. [29][30][31][32][33][34] Kidney donors could potentially present with all of these risk factors. It should also be mentioned that AKI is relatively common in patients with traumatic brain injury (TBI), with an incidence of 9.2%.…”

Section: Discussionmentioning

confidence: 99%

Untitled

Stolyar

Budkar²,

Solodushkin³

et al. 2015

Exp Clin Transplant

View full text Add to dashboard Cite

Objectives: We analyzed different donor characteristics to determine those that significantly affect patient and graft outcomes after kidney transplant. Materials and Methods:We conducted a retrospective analysis of patients who had received kidney transplants at our institution between 1990 and 2011 from deceased-donors. We tracked this patients until the end of 2014. Using univariate and multivariate analyses, we analyzed the following outcomes: patient status, graft status, chronic allograft nephropathy, and delayed graft function. Results: In 342 recipients, univariate analysis revealed donor-associated predictors of transplant outcomes. Recipients of kidneys from older donors showed longer time to creatinine normalization (P = .047). We found a partial correlation between donor diagnosis and the number of dialyses after surgery (excluding the effect of donor age), with patients receiving kidneys from donors who had cerebrovascular events having higher risk of delayed graft function (P = .03). Donors with shorter stays in intensive care units resulted in longer graft survival (P = .02), and vasopressor use by donors was associated with delayed graft function in recipients (P = .018). Low serum sodium levels in donors predicted worse survival of recipients and transplants (P = .015 and P = .048). The number of hemodialysis procedures after transplant was correlated with the donor's creatinine level (P = .027). Insufficient daily dieresis of donor predicted worse graft survival (P = .04). Correlation analysis showed that a higher P CO2 level in donors was significantly associated with longer creatinine normalization time after kidney transplant (P = .001). Cox regression analysis detected 2 significant independent predictors of graft outcomes: duration of perfusion of donor kidney (P = .016) and length of intensive care unit stay of donor (P = .032), with improved prognosis associated with longer perfusion time and shorter time in intensive care unit. Conclusions:The kidney donor has a direct effect on patient life expectancy and renal graft success after transplant.

show abstract

Predicting Hospital-Acquired Acute Kidney Injury—A Case-Controlled Study

Cited by 26 publications

References 38 publications

Risk prediction for acute kidney injury in acute medical admissions in the UK

Risk prediction for acute kidney injury in acute medical admissions in the UK

Improvement of drug prescribing in acute kidney injury with a nephrotoxic drug alert system

Untitled

Contact Info

Product

Resources

About