Risk of postoperative acute kidney injury in patients undergoing orthopaedic surgery--development and validation of a risk score and effect of acute kidney injury on survival: observational cohort study

An explainable machine learning model to predict early and late acute kidney injury after major hepatectomy

BACKGROUND

Risk assessment models for acute kidney injury (AKI) after major hepatectomy that differentiate between early and late AKI are lacking. This retrospective study aimed to create a model predicting AKI through machine learning and identify features that contribute to the development of early and late AKI.

METHODS

Patients that underwent major hepatectomy were categorized into the No-AKI, Early-AKI (within 48 h) or Late-AKI group (between 48 h and 7 days). Modeling was done with 20 perioperative features and the performance of prediction models were measured by the area under the receiver operating characteristic curve (AUROCC). Shapley Additive Explanation (SHAP) values were utilized to explain the outcome of the prediction model.

RESULTS

Of the 1383 patients included in this study, 1229, 110 and 44 patients were categorized into the No-AKI, Early-AKI and Late-AKI group, respectively. The CatBoost classifier exhibited the greatest AUROCC of 0.758 (95% CI: 0.671-0.847) and was found to differentiate well between Early and Late-AKI. We identified different perioperative features for predicting each outcome and found 1-year mortality to be greater for Early-AKI.

CONCLUSIONS

Our results suggest that risk factors are different for Early and Late-AKI after major hepatectomy, and 1-year mortality is greater for Early-AKI.

Preoperative risk prediction models for acute kidney injury after noncardiac surgery: an independent external validation cohort study

BACKGROUND

Numerous models have been developed to predict acute kidney injury (AKI) after noncardiac surgery, yet there is a lack of independent validation and comparison among them.

METHODS

We conducted a systematic literature search to review published risk prediction models for AKI after noncardiac surgery. An independent external validation was performed using a retrospective surgical cohort at a large Chinese hospital from January 2019 to October 2022. The cohort included patients undergoing a wide range of noncardiac surgeries with perioperative creatinine measurements. Postoperative AKI was defined according to the Kidney Disease Improving Global Outcomes creatinine criteria. Model performance was assessed in terms of discrimination (area under the receiver operating characteristic curve, AUROC), calibration (calibration plot), and clinical utility (net benefit), before and after model recalibration through intercept and slope updates. A sensitivity analysis was conducted by including patients without postoperative creatinine measurements in the validation cohort and categorising them as non-AKI cases.

RESULTS

Nine prediction models were evaluated, each with varying clinical and methodological characteristics, including the types of surgical cohorts used for model development, AKI definitions, and predictors. In the validation cohort involving 13,186 patients, 650 (4.9%) developed AKI. Three models demonstrated fair discrimination (AUROC between 0.71 and 0.75); other models had poor or failed discrimination. All models exhibited some miscalibration; five of the nine models were well-calibrated after intercept and slope updates. Decision curve analysis indicated that the three models with fair discrimination consistently provided a positive net benefit after recalibration. The results were confirmed in the sensitivity analysis.

CONCLUSIONS

We identified three models with fair discrimination and potential clinical utility after recalibration for assessing the risk of acute kidney injury after noncardiac surgery.

Sex Bias in Prediction and Diagnosis of Cardiac Surgery Associated Acute Kidney Injury

Background

Female sex has been recognized as a risk factor for cardiac surgery associated acute kidney injury (CS-AKI). The current study sought to evaluate whether female sex is a risk factor for CS-AKI, or modifies the association of peri-operative change in serum creatinine with CS-AKI.

Methods

Observational study of adult patients undergoing cardiac surgery between 2000 and 2019 in a single U.S. center. The main variable of interest was registered patient sex, identified from electronic medical records. The main outcome was CS-AKI within 2 weeks of surgery.

Results

Of 58526 patients, 19353 (33%) were female; 12934 (22%) incurred AKI based on ≥ 0.3 mg/dL or ≥ 50% rise in serum creatinine (any AKI), 3320 (5.7%) had moderate to severe AKI, and 1018 (1.7%) required dialysis within 2 weeks of surgery. Female sex was associated with higher risk for AKI in models that were based on preoperative serum creatinine (OR, 1.35; 95% CI, 1.29-1.42), and lower risk with the use of estimated glomerular filtration, (OR, 0.90; 95% CI, 0.86-0.95). The risk for moderate to severe CS-AKI for a given immediate peri-operative change in serum creatinine was higher in female compared to male patients (p < .0001 and p < .0001 for non-linearity), and the association was modified by pre-operative kidney function (p < .0001 for interaction).

Conclusions

The association of patient sex with CS-AKI and its direction was dependent on the operational definition of pre-operative kidney function, and differential outcome misclassification due to AKI defined by absolute change in serum creatinine.

The prevalence of acute kidney injury in patients with community-acquired pneumonia who required mechanical ventilation

BACKGROUND

Community-acquired pneumonia (CAP) is a common reason for intensive care unit (ICU) admission and sepsis. Acute kidney injury (AKI) is a frequent complication of community-acquired pneumonia and is associated with increased short- and long-term morbidity and mortality and healthcare costs.

OBJECTIVE

Describe the prevalence of AKI in patients with CAP requiring mechanical ventilation and evaluate its association with inhospital mortality.

DESIGN

Retrospective cohort.

SETTING

Intensive care unit.

PATIENTS AND METHODS

We included patients with CAP on mechanical ventilation. Patients were categorized according to the development of AKI in the first 24 hours of ICU admission using the Kidney Disease Improving Global Outcomes (KDIGO) classification from no AKI, stage 1 AKI, stage 2 AKI, and stage 3 AKI.

MAIN OUTCOME MEASURES

The primary outcome was hospital mortality. Secondary outcomes were ICU mortality, hospital and ICU length of stay, ventilation duration, tracheostomy, and renal replacement therapy requirement.

RESULTS

Of 1536 patients included in the study, 829 patients (54%) had no AKI while 707 (46%) developed AKI. In-hospital mortality was 288/829 (34.8%) for patients with no AKI, 43/111 (38.7%) for stage 1 AKI, 86/216 (40%) for stage 2 AKI, and 196/380 (51.7%) for stage 3 AKI (P<.0001). Multivariate analysis revealed that stages 1, 2, or 3 AKI compared to no AKI were not independently associated with in-hospital mortality. Older age, vasopressor use; decreased Glasgow coma scale, PaO2/Fio2 ratio and platelet count, increased bilirubin, lactic acid and INR were associated with increased mortality while female sex was associated with reduced mortality.

CONCLUSION

Among mechanically ventilated patients with CAP, AKI was common and was associated with higher crude mortality. The higher mortality could not be attributed alone to AKI, but rather appeared to be related to multi-organ dysfunction.

LIMITATIONS

Single-center retrospective study with no data on baseline serum creatinine and the use of estimated baseline creatinine distributions based on the MDRD (Modification of Diet in Renal Disease)equation which may lead to an overestimation of AKI. Second, we did not have data on the microbiology of pneumonia, appropriateness of antibiotic therapy or the administration of other medications that have been demonstrated to be associated with AKI.

The epidemiology and outcomes of acute kidney injury following orthopaedic procedures: A retrospective cohort study

BACKGROUND

Acute kidney injury (AKI) is a serious complication following major surgery. This study examined the incidence and risk factors of AKI following orthopaedic surgeries in an Icelandic cohort, as well as the association between AKI and patient- and surgery-related factors.

METHODS

This retrospective cohort study comprised all patients 18 years and older who underwent orthopaedic surgeries at Landspitali - The National University Hospital in the years 2006-2018 with available serum creatinine (SCr) measurements adjacent to the surgery to stage AKI. AKI was defined according to SCr portion of the KDIGO criteria. Logistic regression was used to identify patient- and surgical factors related to progression of AKI and Poisson-regression was used to explore changes in incidence.

RESULTS

A total of 222 cases of AKI following 3208 surgeries (6.9%) were identified in the study period with a rise in the incidence by about 17% per year. Higher age (odds ratio (OR), 1.02, 95% confidence interval (CI), 1.01-1.04 per year) and underlying reduction in kidney function (OR 1.93 (1.30-2.81), 3.24 (2.08-4.96) and 4.08 (2.35-6.96) for estimated glomerular filtration rate (eGFR) of 30-59, 15-29 and <15 mL/min/1.73 m2 compared with eGFR >60 mL/min/1.73 m2 ) were associated with higher risk of AKI, but female sex was associated with decreased odds (OR = 0.73; 95% CI, 0.54-0.98). After correcting for age, sex, preoperative kidney function, emergency surgery and underlying comorbidities and frailty, there was an increased risk of long-term mortality in patients with AKI (HR 1.41, 95% CI 1.08-1.85), and patients who developed AKI also had accelerated progression of chronic kidney disease compared with patients who did not develop AKI.

CONCLUSIONS

The incidence of AKI following orthopaedic surgeries is increasing and is associated with adverse outcomes. It is important that elderly individuals and patients who have reduced kidney function receive adequate monitoring and surveillance in the perioperative period.

Development and external validation of multimodal postoperative acute kidney injury risk machine learning models

Objectives

To develop and externally validate machine learning models using structured and unstructured electronic health record data to predict postoperative acute kidney injury (AKI) across inpatient settings.

Materials and Methods

Data for adult postoperative admissions to the Loyola University Medical Center (2009-2017) were used for model development and admissions to the University of Wisconsin-Madison (2009-2020) were used for validation. Structured features included demographics, vital signs, laboratory results, and nurse-documented scores. Unstructured text from clinical notes were converted into concept unique identifiers (CUIs) using the clinical Text Analysis and Knowledge Extraction System. The primary outcome was the development of Kidney Disease Improvement Global Outcomes stage 2 AKI within 7 days after leaving the operating room. We derived unimodal extreme gradient boosting machines (XGBoost) and elastic net logistic regression (GLMNET) models using structured-only data and multimodal models combining structured data with CUI features. Model comparison was performed using the receiver operating characteristic curve (AUROC), with Delong's test for statistical differences.

Results

The study cohort included 138 389 adult patient admissions (mean [SD] age 58 [16] years; 11 506 [8%] African-American; and 70 826 [51%] female) across the 2 sites. Of those, 2959 (2.1%) developed stage 2 AKI or higher. Across all data types, XGBoost outperformed GLMNET (mean AUROC 0.81 [95% confidence interval (CI), 0.80-0.82] vs 0.78 [95% CI, 0.77-0.79]). The multimodal XGBoost model incorporating CUIs parameterized as term frequency-inverse document frequency (TF-IDF) showed the highest discrimination performance (AUROC 0.82 [95% CI, 0.81-0.83]) over unimodal models (AUROC 0.79 [95% CI, 0.78-0.80]).

Discussion

A multimodality approach with structured data and TF-IDF weighting of CUIs increased model performance over structured data-only models.

Conclusion

These findings highlight the predictive power of CUIs when merged with structured data for clinical prediction models, which may improve the detection of postoperative AKI.

Perioperative acute kidney injury: Current knowledge and the role of anaesthesiologists

Background

Among the different types of perioperative organ injury, acute kidney injury (AKI) occurs frequently and is consistently associated with increased rates of mortality and mortality. Despite development of many clinical trials to assess perioperative interventions, reliable means to prevent or reverse AKI are still lacking.

Objectives

This narrative review discusses recent literature on modifiable risk factors, current approaches to prevention and potential directions for future research.

Methods

A Pubmed search with the relevant keywords was done for articles published in the last 10 years.

Results

New insights into preoperative identification and optimisation, intraoperative strategies, including the choice of anaesthetic, haemodynamic and fluid management, have been made, with the aim of preventing perioperative AKI.

Conclusion

A patient-centric multidisciplinary approach is essential to protect kidney function of patients going for surgery. Much can be done by anaesthesiologists perioperatively, to reduce the risk of development of AKI, especially in susceptible patients. There is a need for further multicentred trials to enhance the currently generic perioperative recommendations.

The effect of intraoperative positive end expiratory pressure and tidal volume on postoperative acute kidney injury after orthopedic surgery

BACKGROUND

To test whether higher intraoperative PEEP levels and/or higher TV levels are associated with higher incidence of postoperative AKI within the first postoperative week, in adult patients having orthopedic surgeries under general anesthesia.

METHODS

We conducted a sub analysis of a non-randomized alternating intervention cross over study performed in patients undergoing orthopedic surgery under general anesthesia at Cleveland Clinic, Cleveland, OH. We included four different combinations of PEEP (5 or 8 cm H2 O) and TV (6 or 10 mL/kg of PBW) that alternated each week in the six orthopedic operating rooms. Our primary outcome was postoperative AKI defined by the KDIGO criteria with baseline creatinine as the closest preoperative value to the time of surgery obtained within 30 days and postoperative value as the highest creatinine value within 7 days after surgery. Secondary outcome was the maximum postoperative in-hospital creatinine level within seven postoperative days.

MAIN RESULTS

A total of 1933 patients were included in the analysis. The incidence of AKI was 6.8% in the study population and similar in high TV versus low TV group and high PEEP versus low PEEP group. Neither TV nor PEEP significantly impacted AKI incidence. The estimated odds ratio of AKI comparing TV = 6 mL/kg to TV = 10 mL/kg was 0.96 (97.5% CI: 0.63, 1.46; p = .811); while the estimated odds ratio of AKI comparing PEEP = 5cm H2 O to PEEP = 8cm H2 O was 0.92 (97.5% CI: 0.60, 1.39; p = .623). No interaction was found between TV and PEEP on AKI. Additionally, neither TV nor PEEP had a significant effect on the seven postoperative day creatinine levels.

CONCLUSION

Higher levels of PEEP or TV during mechanical ventilation in adult patients undergoing orthopedic surgeries under general anesthesia do not increase the odds of developing postoperative AKI within the narrow limits studied.

Construction and evaluation of a risk prediction model for pulmonary infection-associated acute kidney injury in intensive care units

Acute kidney injury (AKI) is one of the common complications of pulmonary infections. However, nomograms predicting the risk of early-onset AKI in patients with pulmonary infections have not been comprehensively researched. In this study, 3278 patients with pulmonary infection were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. These patients were randomly divided into training and validation cohorts, with the training cohort used for model building and the validation cohort used for validation. Independent risk factors for patients with pulmonary infection were determined using the least absolute shrinkage and selection operator (LASSO) method and forward stepwise logistic regression, which revealed that 11 independent risk factors for AKI in patients with pulmonary infections were congestive heart failure (CHF), hypertension, diabetes, transcutaneous oxygen saturation (SpO2), 24-h urine output, white blood cells (WBC), serum creatinine (Scr), prothrombin time (PT), potential of hydrogen (PH), vasopressor use, and mechanical ventilation (MV) use. The nomogram was then constructed and validated. The area under the receiver operating characteristic curve (AUC) values of the nomogram were 0.770 (95% CI = 0.789-0.807) in the training cohort and 0.724 (95% CI = 0.754-0.784) in the validation cohort. High AUC values indicated the good discriminative ability of the nomogram, while the calibration curves and Hosmer-Lemeshow test results indicated that the nomogram was well-calibrated. Improvements in net reclassification index (NRI) and integrated discrimination improvement (IDI) values indicate that our nomogram was superior to the Simplified Acute Physiology Score (SAPS) II scoring system, and the decision-curve analysis (DCA) curves indicate that the nomogram has good clinical application. We established a risk-prediction model for AKI in patients with pulmonary infection, which has good discriminative power and is superior to the SAPS II scoring system. This model can provide clinical reference information for patients with this type of disease in the intensive care unit.

Effect of intraoperative low vs. conventional tidal volume on the incidence of postoperative acute kidney injury after noncardiac surgery: a two-center randomized clinical trial

BACKGROUND

In adults undergoing noncardiac surgery, the correlation between intraoperative tidal volume and postoperative acute kidney injury (AKI) is unclear. This study aimed to investigate the effects of low tidal volume ventilation on the incidence of postoperative AKI compared with conventional tidal volume in adults undergoing noncardiac surgery.

METHODS

This was a two-center prospective randomized controlled trial on adult patients who underwent noncardiac surgery and had a mechanical ventilation of >60 min. Patients were randomized to receive either a tidal volume of 6 mL/kg pre-predicted body weight (PBW, low tidal volume) or a tidal volume of 10 mL/kg pre-predicted body weight (conventional tidal volume). The primary outcome was the incidence of AKI after non-cardiac surgery. Appropriate statistical methods were used for this study.

RESULTS

Among the 1982 randomized patients, 943 with low tidal volume and 958 with conventional tidal volume were evaluable for the primary outcome. Postoperative AKI occurred in 12 patients (1.3%) in the low tidal volume group and 11 patients (1.1%) in the conventional tidal volume group, with an odds ratio of 0.889 (95%CI, 0.391-2.03) and a relative risk of 0.999 ([95%CI, 0.989-1.01]; P=0.804). Postoperative serum creatinine levels increased in 284 (30.0%) patients with low tidal volume compared to 316 (32.0%) patients with conventional tidal volume (P=0.251). No difference in postoperative serum creatinine levels was found between the two groups (57.5 [49.0-68.2] μmol/L vs. 58.8[50.4-69.5] μmol/L, P=0.056).

CONCLUSIONS

Among adults undergoing noncardiac surgery, low tidal volume mechanical ventilation did not significantly reduce the incidence of postoperative AKI compared with conventional tidal volume.

Cardiometabolic disease and obesity patterns differentially predict acute kidney injury after total joint replacement: a retrospective analysis

BACKGROUND

Acute kidney injury (AKI) is a frequent yet understudied postoperative total joint arthroplasty complication. This study aimed to describe cardiometabolic disease co-occurrence using latent class analysis, and associated postoperative AKI risk.

METHODS

This retrospective analysis examined patients ≥18 years old undergoing primary total knee or hip arthroplasties within the US Multicenter Perioperative Outcomes Group of hospitals from 2008 to 2019. AKI was defined using modified Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Latent classes were constructed from eight cardiometabolic diseases including hypertension, diabetes, and coronary artery disease, excluding obesity. A mixed-effects logistic regression model was constructed for the outcome of any AKI and the exposure of interaction between latent class and obesity status adjusting for preoperative and intraoperative covariates.

RESULTS

Of 81 639 cases, 4007 (4.9%) developed AKI. Patients with AKI were more commonly older and non-Hispanic Black, with more significant comorbidity. A latent class model selected three groups of cardiometabolic patterning, labelled 'hypertension only' (n=37 223), 'metabolic syndrome (MetS)' (n=36 503), and 'MetS+cardiovascular disease (CVD)' (n=7913). After adjustment, latent class/obesity interaction groups had differential risk of AKI compared with those in 'hypertension only'/non-obese. Those 'hypertension only'/obese had 1.7-fold increased odds of AKI (95% confidence interval [CI]: 1.5-2.0). Compared with 'hypertension only'/non-obese, those 'MetS+CVD'/obese had the highest odds of AKI (odds ratio 3.1, 95% CI: 2.6-3.7), whereas 'MetS+CVD'/non-obese had 2.2 times the odds of AKI (95% CI: 1.8-2.7; model area under the curve 0.76).

CONCLUSIONS

The risk of postoperative AKI varies widely between patients. The current study suggests that the co-occurrence of metabolic conditions (diabetes mellitus, hypertension), with or without obesity, is a more important risk factor for acute kidney injury than individual comorbid diseases.

Characterization of Risk Prediction Models for Acute Kidney Injury: A Systematic Review and Meta-analysis

Importance

Despite the expansion of published prediction models for acute kidney injury (AKI), there is little evidence of uptake of these models beyond their local derivation nor data on their association with patient outcomes.

Objective

To systematically review published AKI prediction models across all clinical subsettings.

Data Sources

MEDLINE via PubMed (January 1946 to April 2021) and Embase (January 1947 to April 2021) were searched using medical subject headings and text words related to AKI and prediction models.

Study Selection

All studies that developed a prediction model for AKI, defined as a statistical model with at least 2 predictive variables to estimate future occurrence of AKI, were eligible for inclusion. There was no limitation on study populations or methodological designs.

Data Extraction and Synthesis

Two authors independently searched the literature, screened the studies, and extracted and analyzed the data following the Preferred Reporting Items for Systematic Review and Meta-analyses guideline. The data were pooled using a random-effects model, with subgroups defined by 4 clinical settings. Between-study heterogeneity was explored using multiple methods, and funnel plot analysis was used to identify publication bias.

Main Outcomes and Measures

C statistic was used to measure the discrimination of prediction models.

Results

Of the 6955 studies initially identified through literature searching, 150 studies, with 14.4 million participants, met the inclusion criteria. The study characteristics differed widely in design, population, AKI definition, and model performance assessments. The overall pooled C statistic was 0.80 (95% CI, 0.79-0.81), with pooled C statistics in different clinical subsettings ranging from 0.78 (95% CI, 0.75-0.80) to 0.82 (95% CI, 0.78-0.86). Between-study heterogeneity was high overall and in the different clinical settings (eg, contrast medium-associated AKI: I2 = 99.9%; P < .001), and multiple methods did not identify any clear sources. A high proportion of models had a high risk of bias (126 [84.4%]) according to the Prediction Model Risk Of Bias Assessment Tool.

Conclusions and Relevance

In this study, the discrimination of the published AKI prediction models was good, reflected by high C statistics; however, the wide variation in the clinical settings, populations, and predictive variables likely drives the highly heterogenous findings that limit clinical utility. Standardized procedures for development and validation of prediction models are urgently needed.

Insertion of a urinary catheter on admission lowers acute kidney injury incidence in patients with hip fractures

PURPOSE

Acute kidney injury (AKI) is a common adverse event in patients undergoing hip fracture repair surgery, increasing morbidity and mortality. Our study hypothesis was that routine insertion of a urinary catheter, on admission to the hospital or immediately before surgery, will reduce AKI incidence in hip fracture patients.

METHODS

Determined by alternating days of admission, a urinary catheter was inserted routinely on admission (catheter group) or as needed (non-catheter group) in 250 consecutive patients who presented with a hip fracture to our emergency department. The incidence of AKI according to the KDIGO criteria and morbidity and mortality were compared between the study groups.

RESULTS

The overall incidence of AKI was 11.6% (29/250). The catheter group (N = 122) had a significantly lower rate of AKI (6.6% vs. 16% p = 0.018). At 12-month follow-up, the overall mortality was 10.8% (27/250), in-hospital 7.4% (2/27), short-term (within 30 days) 7.4% (2/27), and long-term (30 days to 1 year) 85.8% (23/27). All in-hospital mortality occurred in the AKI group. Patients with no AKI had a better survival rate; however, the difference was not significant (p-value = 0.21). Mortality rate was lower in the catheter group but not significant (8.2% compared with 13.8% in the non-catheter group, p = 0.225). Post-operative respiratory and cardiac complications were more frequent in the AKI group (p = 0.02 and 0.043 accordingly).

CONCLUSIONS

Insertion of a urinary catheter upon admission or before surgery lowered AKI incidence significantly. Peri-operative AKI was associated with higher rates of post-operative complications and worse survival.

Acute Kidney Injury After General Thoracic Surgery: A Systematic Review and Meta-Analysis

INTRODUCTION

The clinical importance of postoperative acute kidney injury (AKI) in patients undergoing general thoracic surgery is unclear. We aimed to systematically review the incidence, risk factors, and prognostic implications of AKI as a complication after general thoracic surgery.

METHODS

We searched PubMed, EMBASE, and the Cochrane Library from January 2004 to September 2021. Observational or interventional studies that enrolled ≥50 patients undergoing general thoracic surgery and reported postoperative AKI defined using contemporary consensus criteria were included for meta-analysis.

RESULTS

Thirty-seven articles reporting 35 unique cohorts were eligible. In 29 studies that enrolled 58,140 consecutive patients, the pooled incidence of postoperative AKI was 8.0% (95% confidence interval [CI]: 6.2-10.0). The incidence was 3.8 (2.0-6.2) % after sublobar resection, 6.7 (4.1-9.9) % after lobectomy, 12.1 (8.1-16.6) % after bilobectomy/pneumonectomy, and 10.5 (5.6-16.7) % after esophagectomy. Considerable heterogeneity in reported incidences of AKI was observed across studies. Short-term mortality was higher (unadjusted risk ratio: 5.07, 95% CI: 2.99-8.60) and length of hospital stay was longer (weighted mean difference: 3.53, 95% CI: 2.56-4.49, d) in patients with postoperative AKI (11 studies, 28,480 patients). Several risk factors for AKI after thoracic surgery were identified.

CONCLUSIONS

AKI occurs frequently after general thoracic surgery and is associated with increased short-term mortality and length of hospital stay. For patients undergoing general thoracic surgery, AKI may be an important postoperative complication that needs early risk evaluation and mitigation.

Reducing incidence of postoperative acute kidney injury in trauma and orthopaedics patients: a quality improvement project

BACKGROUND

Acute kidney injury (AKI) is a common postoperative complication which increases morbidity and mortality. This quality improvement project aimed to implement measures targeting known risk factors to decrease the incidence of postoperative AKI in trauma and orthopaedics (T&O) patients.

METHODS

Data were collected across three six-month to 7-month cycles between 2017 and 2020, analysing all elective and emergency T&O operated patients within a single NHS Trust (n=714, 1008 and 928, respectively). Patients who developed a postoperative AKI were identified using biochemical criteria and data were collected on known AKI risk factors, including use of nephrotoxic medications, and patient outcomes. In the final cycle, the same variables were collected for patients without AKI. Between cycles, measures implemented included: preoperative and postoperative medication reconciliation aiming to stop nephrotoxic medications, orthogeriatrician review of high-risk patients and junior doctor teaching on fluid therapy. Statistical analysis was undertaken to determine the incidence of postoperative AKI across cycles, prevalence of risk factors and impact on length of hospital stay and postoperative mortality.

RESULTS

There was a statistically significant decrease in postoperative AKI incidence from 4.27% (43 of 1008 patients) in cycle 2 to 2.05% (19 of 928) in cycle 3 (p=0.006), with a notable decrease in use of nephrotoxic medications. Significant predictors for the development of postoperative AKI included use of diuretics and receiving multiple nephrotoxic drug classes. Development of postoperative AKI significantly increased length of hospital stay by 7.11 days on average (95% CI: 4.84 to 9.38 days, p<0.001) and risk of 1-year postoperative mortality (OR 3.22, 95% CI: 1.03 to 10.55, p=0.046).

CONCLUSION

This project demonstrates that a multifaceted approach targeting modifiable risk factors can reduce incidence of postoperative AKI in T&O patients, which may lead to reduced length of hospital stay and postoperative mortality.

Construction and Validation of a Nomogram for Predicting Acute Kidney Injury After Hip Fracture Surgery

Background

Acute kidney injury (AKI), characterized by sudden impairment of kidney function, is an uncommon complication following hip fracture surgery that is associated with increased morbidity and mortality. We constructed a nomogram to stratify patients according to risk of AKI after hip fracture surgery to guide clinicians in the implementation of timely interventions.

Methods

Patients who received hip fracture surgery from January 2015 to December 2021 were retrospectively identified and divided into a training set (n=448, surgery from January 2015 to December 2019) and a validation set (n=200, surgery from January 2020 to December 2021). Univariate and multivariate logistic regression were used to identify risk factors for AKI after surgery in the training set. A nomogram was constructed based the risk factors for AKI, and was evaluated by receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).

Results

The mean age was 82.0±6.22 years-old and the prevalence of post-surgical AKI was 13.3%. Age, American Society of Anesthesiologists (ASA) score, the preexistence of chronic kidney disease (CKD), cemented surgery and the decrease of hemoglobin on the first day after surgery were identified as independent risk factors of AKI after hip fracture surgery, and a predictive nomogram was established based on the multivariable model. The predictive nomogram had good discrimination ability (training set: AUC: 0.784, 95% CI: 0.720-0.848; validation set: AUC: 0.804, 95% CI: 0.704-0.903), and showed good validation ability and clinical usefulness based on a calibration plot and decision curve analysis.

Conclusion

A nomogram that incorporated five risk factors including age, ASA score, preexisting CKD, cemented surgery and the decrease of hemoglobin on the first day after surgery had good predictive performance and discrimination. Use of our results for early stratification and intervention has the potential to improve the outcomes of patients receiving hip fracture surgery. Future large, multicenter cohorts are needed to verify the model's performance.

Incidence, severity, risk factors and outcomes of acute kidney injury in older adults: systematic review and meta-analysis

OBJECTIVES

Old age was identified as a strong risk factor for acute kidney injury (AKI). Our objectives were to provide estimates of AKI, risk factors and outcomes in patients ≥ 75 years for whom data are scarce.

METHODS

Observational studies and randomized controlled trials between 2005 and 2021 with patients of mean or median age ≥ 75 years, reporting AKI according to current definitions. Data on AKI incidence, risk factors and mortality were analyzed separately in unselected (UC) and acute heart failure (AHF) cohorts.

RESULTS

Twenty-six observational studies and 4 randomized controlled trials with 51,111 UC and 25,414 AHF patients were included. Ages averaged 79.4 and 79.8 years, respectively. Pooled risk ratios (RRs) of AKI rates were 26.29% (95% confidence intervals (CI) 13.20-41.97) (UC) and 24.21% (95% CI 20.03-28.65) (AHF). In both cohorts, AKI was associated with decreased estimated glomerular filtration rate at baseline, chronic kidney disease (UC: RR 1.80 (95% CI 1.15-2.80), AHF: RR 1.51 (95% CI 1.26-1.95) and hypertension (UC: RR 1.30 (95% CI 1.09-1.56), AHF: RR 1.07 (95% CI 1.05-1.09). RRs of AKI in patients on renin-angiotensin-inhibitors were 0.87 (95% CI 0.78-0.97) and 0.88 (95% CI 0.78-0.98) in UC and AHF, respectively. AKI was consistently associated with increased risk of in-hospital mortality (UC: RR 3.15 (95% CI 2.28-4.35), AHF: RR 4.28 (95% CI 2.53-7.24).

CONCLUSION

AKI is frequent in patients ≥ 75 years. While reduced renal function at baseline, CKD and hypertension were associated with AKI development, renin-angiotensin-inhibitors may be protective. Older AKI patients showed higher short-term mortality rates.

Postoperative Acute Kidney Injury

Postoperative AKI is a common complication of major surgery and is associated with significant morbidity and mortality. The Kidney Disease Improving Global Outcomes AKI definition allows consensus classification and identification of postoperative AKI through changes in serum creatinine and/or urine output. However, such conventional diagnostic criteria may be inaccurate in the postoperative period, suggesting a potential to refine diagnosis by application of novel diagnostic biomarkers. Risk factors for the development of postoperative AKI can be thought of in terms of preoperative, intraoperative, and postoperative factors and, as such, represent areas that may be targeted perioperatively to minimize the risk of AKI. The treatment of postoperative AKI remains predominantly supportive, although application of management bundles may translate into improved outcomes.

Acute kidney injury after hip fracture surgery in patients over 80 years of age

BACKGROUND

The aim of the study is to determine the rate of acute kidney injury (AKI) after hip fracture surgery over the age of 80 and to investigate the factors associated with AKI.

METHODS

From January 2015 to January 2020, 589 patients who underwent surgery of hip fractures at our institution were retrospectively reviewed. Serum creatinine (sCr) was analysed daily pre- and postoperatively during the hospital stay. Patients were divided into groups; AKI and non-AKI based on KDIGO (Kidney Disease Global Outcomes) criteria. The incidence, risk factors, and mortality of postoperative AKI were investigated.

RESULTS

Out of 589 patients, 58 developed an AKI (9.8%). Smoking (p: 0.004), pre and postoperative low albumin level (p < 0.05), pre- and postoperative high potassium level (p < 0.05), pre- and postoperative high urea levels (p < 0.05), high amount of intra-operative bleeding (p: 0.003) and prolonged surgery time (p: 0.003) were found to be risk factors associated with AKI. Although the mortality rate was higher in the AKI group, it was not statistically significant (p > 0.05).

CONCLUSION

AKI is a temporary but common complication following hip fracture surgery, which can also be predicted if risk factors are adequately observed. It typically increases the length of hospital stays, mortality and morbidity.

LEVEL OF EVIDENCE

Level III evidence, Retrospective comparative study.

Impact of a prescriber and patient educational intervention on discharge analgesia prescribing and hospital readmission rates following elective unilateral total hip and knee arthroplasty

Introduction

Pain management after elective, unilateral total hip and knee arthroplasty (THA and TKA) should use a multimodal approach. At discharge, challenges include ensuring correct prescribing practices to optimise analgesia and rationalise opioid use as well as ensuring patients are adequately educated to take these medications safely and effectively in the community. This audit cycle reports on a prescriber and patient education intervention using printed guidelines, educational outreach and prescription standardisation along with a patient information sheet to address the high unplanned readmission rate following THA and TKA at our institution.

Methods

Two cohorts of patients were identified before (2016) and after (2019) the introduction of the educational package. The primary outcome was the unplanned hospital readmission rate in the 42 days following discharge. Secondary outcomes were the compliance with the set prescribing standards and the prescription of strong opioid medications (morphine or oxycodone) on discharge.

Results

There was a reduction in the readmission rate from 20.4% to 10.0% (p=0.004). Readmission rates for pain and constipation were also reduced. The prescribing of tramadol (p<0.001) and non-steroidal anti-inflammatory drugs (p<0.001) both increased while the number of patients who received a strong opioid at discharge decreased (p<0.001) as did the number of patients who received a sustained release strong opioid (p<0.001).

Conclusion

We have observed significant improvement in discharge prescribing which coincided with a reduction in unplanned readmissions after elective TKA and THA. Our approach used prescriber guidelines, education and standardisation with printed information for patients to enhance understanding and recall.

Improving Postoperative Acute Kidney Injury Rates Following Primary Total Joint Arthroplasty

BACKGROUND

Perioperative hip and knee arthroplasty complications remain a significant clinical and financial burden. Our institution has shifted to developing protocols to decrease these perioperative complications. This study focuses on acute kidney injury (AKI) rate status post primary total joint arthroplasty (TJA). Current literature demonstrates a 2%-15% incidence of AKI following TJA. However, there is a paucity of published literature on protocols that have effectively reduced AKI rates following TJA. The purpose of this study is to evaluate the effect that our institutionally developed perioperative renal protocol had on the postoperative AKI rates.

METHODS

A retrospective cohort study was performed. Patient demographics, baseline creatinine, and postoperative creatinine values during the patient's hospitalization were collected and analyzed. The preintervention cohort data contained all patients at our institution who underwent a primary TJA from November 1, 2016 to January 1, 2018. The postintervention cohort included all primary TJA patients from July 1, 2018 to February 2, 2020. AKI was defined using the AKI Network classification system comparing baseline and postoperative creatinine values. A multivariate analysis was performed to determine the statistical significance of our results.

RESULTS

Before intervention 1013 patients underwent a primary TJA with 68 patients developing an AKI postoperatively. After intervention 2169 patients underwent primary TJA with 90 patients developing an AKI (6.71% vs 4.15%; P = .0015, odds ratio = 0.59, 95% confidence interval = 0.42-0.82).

CONCLUSION

This study demonstrated that implementation of a perioperative renal protocol can significantly reduce AKI rates. A reduction in AKI rates following TJA will result in improved outcomes and secondarily decrease the financial impact of postoperative complications seen following TJA.

Development and Validation of a Personalized Model With Transfer Learning for Acute Kidney Injury Risk Estimation Using Electronic Health Records

IMPORTANCE

Acute kidney injury (AKI) is a heterogeneous syndrome prevalent among hospitalized patients. Personalized risk estimation and risk factor identification may allow effective intervention and improved outcomes.

OBJECTIVE

To develop and validate personalized AKI risk estimation models using electronic health records (EHRs), examine whether personalized models were beneficial in comparison with global and subgroup models, and assess the heterogeneity of risk factors and their outcomes in different subpopulations.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study analyzed EHR data from 1 tertiary care hospital and used machine learning and logistic regression to develop and validate global, subgroup, and personalized risk estimation models. Transfer learning was implemented to enhance the personalized model. Predictor outcomes across subpopulations were analyzed, and metaregression was used to explore predictor interactions. Adults who were hospitalized for 2 or more days from November 1, 2007, to December 31, 2016, were included in the analysis. Patients with moderate or severe kidney dysfunction at admission were excluded. Data were analyzed between August 28, 2019, and May 8, 2022.

EXPOSURES

Clinical and laboratory variables in the EHR.

MAIN OUTCOMES AND MEASURES

The main outcome was AKI of any severity, and AKI was defined using the Kidney Disease: Improving Global Outcomes serum creatinine criteria. Performance of the models was measured with area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve, and calibration.

RESULTS

The study cohort comprised 76 957 inpatient encounters. Patients had a mean (SD) age of 55.5 (17.4) years and included 42 159 men (54.8%). The personalized model with transfer learning outperformed the global model for AKI estimation in terms of AUROC among general inpatients (0.78 [95% CI, 0.77-0.79] vs 0.76 [95% CI, 0.75-0.76]; P < .001) and across the high-risk subgroups (0.79 [95% CI, 0.78-0.80] vs 0.75 [95% CI, 0.74-0.77]; P < .001) and low-risk subgroups (0.74 [95% CI, 0.73-0.75] vs 0.71 [95% CI, 0.70-0.72]; P < .001). The AUROC improvement reached 0.13 for the high-risk subgroups, such as those undergoing liver transplant and cardiac surgery. Moreover, the personalized model with transfer learning performed better than or comparably with the best published models in well-studied AKI subgroups. Predictor outcomes varied significantly between patients, and interaction analysis uncovered modifiers of the predictor outcomes.

CONCLUSIONS AND RELEVANCE

Results of this study demonstrated that a personalized modeling with transfer learning is an improved AKI risk estimation approach that can be used across diverse patient subgroups. Risk factor heterogeneity and interactions at the individual level highlighted the need for agile, personalized care.

Preoperative NT-proBNP and LVEF for the prediction of acute kidney injury after noncardiac surgery: a single-centre retrospective study

BACKGROUND

Acute kidney injury (AKI) is one of the most common postoperative complications in noncardiac surgical patients, has an important impact on prognosis and is difficult to predict. Whether preoperative N-terminal pro-brain natriuretic peptide (NT-proBNP) concentrations and left ventricular ejection fraction (LVEF) levels can predict postoperative AKI in noncardiac surgical patients is unclear.

METHODS

We included 3,314 patients who underwent noncardiac surgery and had measurements of preoperative NT-proBNP concentrations and LVEF levels at a tertiary academic hospital in China between 2008 and 2018. Multiple logistic regression analysis was used to construct a postoperative AKI risk prediction model for this cohort. Then, NT-proBNP concentrations and LVEF levels were included in the abovementioned model as independent variables, and the predictive ability of these two models was compared.

RESULTS

Postoperative AKI occurred in 223 (6.72%) patients within 1 week after surgery. Preoperative NT-proBNP concentrations and LVEF levels were independent predictors of AKI after adjustment for clinical variables. The area under the receiver operating characteristic curve (AUROC) of the AKI risk predictive model established with clinical baseline variables was 0.767 (95% CI: 0.732, 0.802). When NT-proBNP concentrations and LVEF levels were added to the base model, the AUROC was 0.811 (95% CI: 0.779, 0.843). The addition of NT-proBNP concentrations and LVEF levels improved reclassification by 22.9% (95% CI 10.5-34.4%) for patients who developed postoperative AKI and by 36.3% (95% CI 29.5-43.9%) for those who did not, resulting in a significant overall improvement in net reclassification (NRI: 0.591, 95% CI 0.437-0.752, P < 0.000). The integral discrimination improvement was 0.100 (95% CI: 0.075, 0.125, P < 0.000).The final postoperative AKI prediction model was constructed, and had a good discriminative ability and fitted to the dataset.

CONCLUSIONS

Preoperative NT-proBNP concentrations and LVEF levels were independently associated with the risk of AKI after noncardiac surgery, and they could improve the predictive ability of logistic regression models based on conventional clinical risk factors.

TRIAL REGISTRATION

The protocol was preregistered in the Chinese Clinical Trial Registry ( ChiCTR1900024056 ).

Changes in perioperative red cell transfusion practice over time in patients undergoing surgery for upper gastrointestinal and liver cancer: a retrospective cohort study at a single tertiary centre

OBJECTIVES

Optimum transfusion trigger for adults undergoing cancer surgery is uncertain. Published guidelines recommend restrictive transfusion strategies in hospitalised adults. We aimed to measure the red cell transfusion rate and haemoglobin trigger in patients undergoing cancer surgery and how closely practice reflected published guidelines.

DESIGN

Retrospective cohort study.

SETTING

Single tertiary centre.

PARTICIPANTS

Adult patients undergoing surgery for upper gastrointestinal or liver malignancy.

EXPOSURE

Postguideline change (2015-2017) versus preguideline change (2011-2012).

OUTCOME MEASURES

Primary: transfusion rate, secondary: transfusion trigger. Multivariable logistic regression was used to assess factors and adjust for confounders affecting our outcome measures.

RESULTS

1578 surgical records were identified for 1520 patients. 946/1530 (62%) patients had preoperative anaemia. The transfusion rate decreased from 23% in 2011-2012 to 14% in 2015-2017. This change remained significant after adjusting for other variables associated with transfusion rates. Mean pretransfusion haemoglobin in those who were transfused was 78±13 g/L in 2011-2012 and 80±15 g/L in 2015-2017. This change in haemoglobin transfusion triggers was not significant.

CONCLUSION

Transfusion rate has decreased over the study period in patients undergoing surgery for malignancy and is consistent with a restrictive transfusion strategy.

Application of Machine Learning Algorithms to Predict Acute Kidney Injury in Elderly Orthopedic Postoperative Patients

Objective

There has been a worldwide increment in acute kidney injury (AKI) incidence among elderly orthopedic operative patients. The AKI prediction model provides patients’ early detection a possibility at risk of AKI; most of the AKI prediction models derive, however, from the cardiothoracic operation. The purpose of this study is to predict the risk of AKI in elderly patients after orthopedic surgery based on machine learning algorithm models.

Methods

We organized a retrospective study being comprised of 1000 patients with postoperative AKI undergoing orthopedic surgery from September 2016, to June, 2021. They were divided into training (80%;n=799) and test (20%;n=201) sets.We utilized nine machine learning (ML) algorithms and used intraoperative information and preoperative clinical features to acquire models to predict AKI. The performance of the model was evaluated according to the area under the receiver operating characteristic (AUC), sensitivity, specificity and accuracy. Select the optimal model and establish the nomogram to make the prediction model visualization. The concordance statistic (C-statistic) and calibration curve were used to discriminate and calibrate the nomogram respectively.

Results

In predicting AKI, nine ML algorithms posted AUC of 0.656–1.000 in the training cohort, with the randomforest standing out and AUC of 0.674–0.821 in the test cohort, with the logistic regression model standing out. Thus, we applied the logistic regression model to establish nomogram. The nomogram was comprised of ten variables: age, body mass index, American Society of Anesthesiologists, hypoproteinemia, hypertension, diabetes, anemia, duration of low mean arterial pressure, mean arterial pressure, transfusion.The calibration curves showed good agreement between prediction and observation in both the training and test sets.

Conclusion

By including intraoperative and preoperative risk factors, ML algorithm can predict AKI and logistic regression model performing the best. Our prediction model and nomogram that are based on this ML algorithm can help lead decision-making for strategies to inhibit AKI over the perioperative duration.

A comparative study of 21,194 UKAs and 49,270 HTOs for the risk of unanticipated events in mid-age patients from the national claims data in South Korea

Background

Both high tibial osteotomy (HTO) and unicompartmental knee arthroplasty (UKA) are well-established treatments for medial knee osteoarthritis (OA). However, over the past 20 years, results of comparisons of long-term survival rates and outcomes have remained controversial. Furthermore, in patients at the boundary age, from 50 to 70 years, considering age as a treatment indication, selecting a surgical method is difficult. Therefore, we aimed to investigate conversion rates to total knee arthroplasty (TKA) and perioperative adverse outcomes between the two surgical methods in mid-age patients.

Methods

We extracted data from the Korean National Health Insurance claims database. A total of 70,464 patients aged between 50 and 70 years, considered as mid-age patients were included in the final study population. We used a multivariable Cox proportional hazard regression model, adjusting for potential confounders such as age, sex, insurance type, region of residence, hospital type, comorbidities, and the Charlson comorbidity Index (CCI).

Results

Of the 70,464 patients, 21,194 were treated with UKA and 49,270 were treated with HTO. HTO showed a higher risk of revision than UKA at five, and 10 years and during the whole observation period. The incidence of deep vein thromboembolism, and surgical site infection was significantly higher in UKA than in HTO.

Conclusions

It is important to choose an appropriate surgical method considering that UKA has better results in terms of long-term survival rates but may have a higher incidence of various complications.

A web-based machine-learning algorithm predicting postoperative acute kidney injury after total knee arthroplasty

PURPOSE

Acute kidney injury (AKI) is a deleterious complication after total knee arthroplasty (TKA). The purposes of this study were to identify preoperative risk factors and develop a web-based prediction model for postoperative AKI, and assess how AKI affected the progression to ESRD.

METHOD

The study included 5757 patients treated in three tertiary teaching hospitals. The model was developed using data on 5302 patients from two hospitals and externally validated in 455 patients from the third hospital. Eighteen preoperative variables were collected and feature selection was performed. A gradient boosting machine (GBM) was used to predict AKI. A tenfold-stratified area under the curve (AUC) served as the metric for internal validation. Calibration was performed via isotonic regression and evaluated using a calibration plot. End-stage renal disease (ESRD) was followed up for an average of 41.7 months.

RESULTS

AKI develops in up to 10% of patients undergoing TKA, increasing the risk of progression to ESRD. The ESRD odds ratio of AKI patients (compared to non-AKI patients) was 9.8 (95% confidence interval 4.3-22.4). Six key predictors of postoperative AKI were selected: higher preoperative levels of creatinine in serum, the use of general anesthesia, male sex, a higher ASA class (> 3), use of a renin-angiotensin-aldosterone system inhibitor, and no use of tranexamic acid (all p < 0.001). The predictive performance of our model was good (area under the curve 0.78 [95% CI 0.74-0.81] in the developmental cohort and improved in the external validation cohort (0.89). Our model can be accessed at https://safetka.net .

CONCLUSIONS

A web-based predictive model for AKI after TKA was developed using a machine-learning algorithm featuring six preoperative variables. The model is simple and has been validated to improve both short- and long-term prognoses of TKA patients. Postoperative AKI may lead to ESRD, which surgeons should strive to avoid.

LEVEL OF EVIDENCE

Diagnostic level II.

The incidence, risk factors and outcomes of acute kidney injury in critically ill patients undergoing emergency surgery: a prospective observational study

BACKGROUND

Without sufficient evidence in postoperative acute kidney injury (AKI) in critically ill patients undergoing emergency surgery, it is meaningful to explore the incidence, risk factors, and prognosis of postoperative AKI.

METHODS

A prospective observational study was conducted in the general intensive care units (ICUs) from January 2014 to March 2018. Variables about preoperation, intraoperation and postoperation were collected. AKI was diagnosed using the Kidney Disease: Improving Global Outcomes criteria.

RESULTS

Among 383 critically ill patients undergoing emergency surgery, 151 (39.4%) patients developed postoperative AKI. Postoperative reoperation, postoperative Acute Physiology and Chronic Health Evaluation (APACHE II) score, and postoperative serum lactic acid (LAC) were independent risk factors for postoperative AKI, with the adjusted odds ratio (ORadj) of 1.854 (95% confidence interval [CI], 1.091-3.152), 1.059 (95%CI, 1.018-1.102), and 1.239 (95%CI, 1.047-1.467), respectively. Compared with the non-AKI group, duration of mechanical ventilation, renal replacement therapy, ICU and hospital mortality, ICU and hospital length of stay, total ICU and hospital costs were higher in the AKI group.

CONCLUSIONS

Postoperative reoperation, postoperative APACHE II score, and postoperative LAC were independent risk factors of postoperative AKI in critically ill patients undergoing emergency surgery.

Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure

Background: Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence. Methods: Six hundred and fifty patients with ADHF were enrolled in this study. Data for each patient were collected from medical records. We took three different approaches of variable selection to derive four multivariable logistic regression model. We selected six candidate predictors that led to a relatively stable outcome in different models to derive the final prediction model. The prediction model was verified through the use of the C-Statistics and calibration curve. Results: Acute kidney injury occurred in 42.8% of the patients. Advanced age, diabetes, previous renal dysfunction, high baseline creatinine, high B-type natriuretic peptide, and hypoalbuminemia were the strongest predictors for AKI. The prediction model showed moderate discrimination C-Statistics: 0.766 (95% CI, 0.729-0.803) and good identical calibration. Conclusion: In this study, we developed a prediction model and nomogram to estimate the risk of AKI among patients with ADHF. It may help clinical physicians detect AKI and manage it promptly.

Surgical trauma is associated with renal immune cell activation in rats: A microarray study

Acute kidney injury (AKI) is a common perioperative complication that is associated with increased mortality. This study investigates the renal gene expression in male Long-Evans rats after prolonged anesthesia and surgery to detect molecular mechanisms that could predispose the kidneys to injury upon further insults. Healthy and streptozotocin diabetic rats that underwent autoregulatory investigation in an earlier study were compared to rats that were sacrificed quickly for mRNA quantification in the same study. Prolonged surgery caused massive changes in renal mRNA expression by microarray analysis, which was validated by quantitative real-time PCR with good correlation. Furthermore, bioinformatics analysis using gene ontology and pathway analysis identified biological processes involved in immune system activation, such as immune system processes (p = 1.3 × 10-80 ), immune response (p = 1.3 × 10-60 ), and regulation of cytokine production (p = 1.7 × 10-52 ). PCR analysis of specific cell type markers indicated that the gene activation in kidneys was most probably macrophages, while granulocytes and T cell appeared less activated. Immunohistochemistry was used to quantify immune cell infiltration and showed no difference between groups indicating that the genetic activation depends on the activation of resident cells, or infiltration of a relatively small number of highly activated cells. In follow-up experiments, surgery was performed on healthy rats under standard and sterile condition showing similar expression of immune cell markers, which suggests that the inflammation was indeed caused by the surgical trauma rather than by bacterial infection. In conclusion, surgical trauma is associated with rapid activation of immune cells, most likely macrophages in rat kidneys.

Sleep, Pain, and Cognition: Modifiable Targets for Optimal Perioperative Brain Health

The prevention of perioperative neurocognitive disorders is a priority for patients, families, clinicians, and researchers. Given the multiple risk factors present throughout the perioperative period, a multicomponent preventative approach may be most effective. The objectives of this narrative review are to highlight the importance of sleep, pain, and cognition on the risk of perioperative neurocognitive disorders and to discuss the evidence behind interventions targeting these modifiable risk factors. Sleep disruption is associated with postoperative delirium, but the benefit of sleep-related interventions is uncertain. Pain is a risk factor for postoperative delirium, but its impact on other postoperative neurocognitive disorders is unknown. Multimodal analgesia and opioid avoidance are emerging as best practices, but data supporting their efficacy to prevent delirium are limited. Poor preoperative cognitive function is a strong predictor of postoperative neurocognitive disorder, and work is ongoing to determine whether it can be modified to prevent perioperative neurocognitive disorders.

Impact of postoperative acute kidney injury in patients undergoing major gastrointestinal surgery on 1-year survival and renal outcomes: a national multicentre cohort study

Background

The intermediate-term impact of acute kidney injury (AKI) in patients after major gastrointestinal and liver surgery has not been well characterized. This study aimed to evaluate the 1-year mortality rate and renal outcomes associated with postoperative AKI in a national prospective cohort.

Methods

This prospective multicentre, observational cohort with 1-year postoperative follow-up included adults undergoing major gastrointestinal and liver surgery across the UK and Ireland between 23 September and 18 November 2015. AKI was defined according to Kidney Disease Improving Global Outcomes (KDIGO) criteria. The primary outcome was death at 1-year after surgery, and the secondary outcome was Major Adverse Kidney Events (MAKE-365). Cox proportionate and multilevel logistic regression were used to account for case mix.

Results

Of 5745 patients across 173 centres, 1-year follow-up data was completed for 3504 patients (62.2 per cent, 126 centres), with attrition largely explained by centre non-participation (63.1 per cent). Some 13.6 per cent (475 of 3504) patients developed AKI by 7 days after surgery (stage 1: 9.2 per cent; stage 2/3: 4.3 per cent). At 1 year, 10.8 per cent (378 patients) experienced a MAKE-365 endpoint (303 patients had died, 61 had renal replacement therapy and 78 had renal dysfunction). Patients who experienced AKI by 7 days after surgery had a higher hazard of death at 1 year for KDIGO stage 1 (hazard ratio 1.50 (95 per cent c.i. 1.08 to 2.08), P = 0.016) and KDIGO stage 2/3 (hazard ratio 2.96 (95 per cent c.i. 2.02 to 4.33), P < 0.001). Both KDIGO stage 1 (odds ratio 2.09 (95 per cent c.i. 1.50 to 2.92), P < 0.001) and stage 2/3 (odds ratio 9.26 (95 per cent c.i. 6.31 to 13.59), P < 0.001) AKI were independently associated with MAKE-365.

Conclusion

AKI events within 7 days after gastrointestinal or liver surgery are associated with significantly worse survival and renal outcomes at 1 year.

External Validation of a Prediction Model for Acute Kidney Injury Following Noncardiac Surgery

IMPORTANCE

The Simple Postoperative AKI Risk (SPARK) index is a prediction model for postoperative acute kidney injury (PO-AKI) in patients undergoing noncardiac surgery. External validation has not been performed.

OBJECTIVE

To externally validate the SPARK index.

DESIGN, SETTING, AND PARTICIPANTS

This single-center retrospective cohort study included adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011. Those with obstetric or urological surgery, estimated glomerular filtration rate (eGFR) of less than 15 mL/min/1.73 m2, preoperative dialysis, or an expected surgical duration of less than 1 hour were excluded. The study was conducted at Nara Medical University Hospital. Data analysis was conducted from January to July 2021.

EXPOSURES

Risk factors for AKI included in SPARK index.

MAIN OUTCOMES AND MEASURES

PO-AKI, defined as an increase in serum creatinine of at least 0.3 mg/dL within 48 hours or 150% compared with preoperative baseline value or urine output of less than 0.5 mL/kg/h for at least 6 hours within 1 week after surgery, and critical AKI, defined as either AKI stage 2 or greater and/or any AKI connected to postoperative death or requiring kidney replacement therapy before discharge. The discrimination and calibration of the SPARK index were examined with area under the receiver operating characteristic curves (AUC) and calibration plots, respectively.

RESULTS

Among 5135 participants (2410 [46.9%] men), 303 (5.9%) developed PO-AKI, and 137 (2.7%) developed critical AKI. Compared with the SPARK cohort, participants in our cohort were older (median [IQR] age, 56 [44-66] years vs 63 [50-73] years), had lower baseline eGFR (median [IQR], 82.1 [71.4-95.1] mL/min/1.73 m2 vs 78.2 [65.6-92.2] mL/min/1.73 m2), and had a higher prevalence of comorbidities (eg, diabetes: 3956 of 51 041 [7.8%] vs 802 [15.6%]). The incidence of PO-AKI and critical AKI increased as the scores on the SPARK index increased. For example, 10 of 593 participants (1.7%) in SPARK class A, indicating lowest risk, experienced PO-AKI, while 53 of 332 (16.0%) in SPARK class D, indicating highest risk, experienced PO-AKI. However, AUCs for PO-AKI and critical AKI were 0.67 (95% CI, 0.63-0.70) and 0.62 (95% CI, 0.57-0.67), respectively, and the calibration was poor (PO-AKI: y = 0.24x + 3.28; R2 = 0.86; critical AKI: y = 0.20x + 2.08; R2 = 0.51). Older age, diabetes, expected surgical duration, emergency surgery, renin-angiotensin-aldosterone system blockade use, and hyponatremia were not associated with PO-AKI in our cohort, resulting in overestimation of the predicted probability of AKI in our cohort.

CONCLUSIONS AND RELEVANCE

In this study, the incidence of PO-AKI increased as the scores on the SPARK index increased. However, the predicted probability might not be accurate in cohorts with older patients with more comorbidities.

Perioperative acute kidney injury and urine output in lower limb arthroplasties

BACKGROUND

This study aimed to evaluate the occurrence and perioperative risk factors of acute kidney injury (AKI) in primary elective hip and knee and emergency hip arthroplasty patients. We also aimed to assess the effect of urine output (UOP) as a diagnostic criterion in addition to serum creatinine (sCr) levels. We hypothesized that emergency arthroplasties are prone to AKI and that UOP is an underrated marker of AKI.

METHODS

This retrospective, register-based study assessed 731 patients who underwent primary elective knee or hip arthroplasty and 170 patients who underwent emergency hip arthroplasty at Oulu University Hospital, Finland, between January 2016 and February 2017.

RESULTS

Of the elective patients, 18 (2.5%) developed AKI. The 1-year mortality rate was 1.5% in elective patients without AKI and 11.1% in those with AKI (P = .038). Of the emergency patients, 24 (14.1%) developed AKI. The mortality rate was 16.4% and 37.5% in emergency patients without and with AKI, respectively (P = .024). In an AKI subgroup analysis of the combined elective and emergency patients, the mortality rate was 31.3% (n = 5) in the sCr group (n = 16), 23.5% (n = 4) in the UOP group (n = 17), and 22.2% (n = 2) in AKI patients who met both the sCr and UOP criteria (n = 9).

CONCLUSION

Emergency hip arthroplasty is associated with an increased risk of AKI. Since AKI increases mortality in both elective and emergency arthroplasty, perioperative oliguria should also be considered as a diagnostic criterion for AKI. Focusing solely on sCr may overlook many cases of AKI.

The obesity paradox and orthopedic surgery

The Obesity Paradox describes the counterintuitive finding that although obesity contributes to the development of chronic conditions such as chronic kidney disease and cardiovascular disease, obesity seems to improve mortality in patients with these diseases. This paradox has also been sited in the critical care literature in regard to acute kidney injury, obesity and mortality. This study's objective is to examine the impact of obesity and post-surgical acute kidney injury on hospital length of stay and 2-year mortality after orthopedic surgery.We reviewed the electronic medical records of all adult elective orthopedic surgery patients over 2 years in a large academic hospital. The 1783 patients who met inclusion criteria were divided into obese (body mass index, BMI ≥ 30, n = 1123) and non-obese groups (BMI <30, n = 660). Demographics, medications, comorbidities, and perioperative variables were included in multivariable logistic regression analyses with acute kidney injury, length of hospital stay, and two-year mortality as primary outcomes. Outcomes were analyzed for the entire group, the obese cohort and the non-obese cohort.Acute kidney injury developed in 5% of the post-surgical orthopedic patients. Obesity increased the likelihood of developing acute kidney injury post orthopedic surgery (odds ratio [OR] = 1.82; 95% Confidence interval [CI] 1.05-3.15, P = .034). Acute kidney injury increased length of stay by 1.3 days and increased the odds of two-year mortality (OR = 2.08; 95% CI 1.03-4.22, P = .041). However, obese patients had a decreased likelihood of two-year mortality (OR = 0.53; 95% CI 0.33-0.84, P = .009).In adult orthopedic surgery patients, obesity increased the risk of acute kidney injury. Patients who developed an acute kidney injury had longer hospital stays and higher two-year mortality. Paradoxically, obesity decreased two-year mortality.

Obesity, Angiotensin-Blocking Drugs, and Acute Kidney Injury in Orthopedic Surgery

Postoperative acute kidney injury occurs in 7% to 11% of orthopedic surgeries. The effect of preoperative angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) on the development of postoperative acute kidney injury remains controversial. Adipose tissue has its own independently regulated angiotensin system. The primary aim of this study was to examine the effects of obesity and preoperative ACEIs and ARBs on postoperative acute kidney injury. Charts were reviewed of adult elective orthopedic surgery patients during a 2-year period when patients were instructed to take their ACEI or ARB on the morning of surgery. The patients were divided into an obese cohort (body mass index [BMI] ≥30 kg/m²) and a nonobese cohort (BMI <30 kg/m²). A multivariable model was created for the outcome of acute kidney injury, using obesity as a primary predictor and adjusting for demographics, medications, comorbidities, and intraoperative parameters in a logistic regression analysis. Obesity increased the likelihood of developing acute kidney injury after orthopedic surgery (odds ratio [OR], 1.86; 95% CI, 1.07-3.22; P=.028). For every 5-unit increase in BMI, the odds of acute kidney injury were 1.43 (95% CI, 1.26-1.62; P<.001). When receiving ACEIs or ARBs, only the nonobese patients had a statistically increased likelihood of postoperative acute kidney injury (OR, 3.30; 95% CI, 1.12-9.70; P=.030). Obesity is an independent risk factor for postoperative acute kidney injury. Obesity appears to influence the effect that preoperative ACEIs and ARBs have on postoperative acute kidney injury. [Orthopedics. 2021;44(2):e253-e258.].

Acute kidney injury in patients undergoing elective primary lower limb arthroplasty

Purpose

Recent research has outlined the increasing incidence of acute kidney injury (AKI) and its effect on morbidity/mortality. There is evidence that current rates are significantly under-reported nationally, with uncertainty about pre-operative factors that might influence AKI reduction and the impact on other healthcare outcomes such as mortality and later Chronic Kidney Disease (CKD) development. We set out to help address these current deficiencies in the literature.

Methods

A retrospective cohort study was undertaken using data collected from patients undergoing elective primary lower limb arthroplasty within our institution from 01/10/16–31/09/17 with a 2-year follow-up.

Results

53/782 (6.8%) patients had an AKI during the study time period. This was associated with a longer inpatient stay (p < 0.001). There was no significant difference in 30-day mortality (p = 0.134), 30-day readmission (p = 1.00) or later CKD development (p = 0.63). Independent predictors of AKI were as follows: Diabetes (OR 2.49; 95%CI 1.15–5.38; p = 0.021), CKD (OR 4.59; 95%CI 2.37–8.92; p < 0.001) and Male sex (OR 2.61; 95%CI 1.42–4.78; p = 0.002).

Conclusions

AKI in those undergoing hip and knee arthroplasty remains under-reported at a national level. AKI development was associated with an increased length of stay, but not long-term healthcare outcomes. This may be due to the mechanism of AKI development or the low absolute numbers of AKI suffered. We have identified three pre-operative factors (Diabetes, CKD & Male Sex) that were independently predictive of AKI. Targeted interventions may reduce the risk of AKI after lower limb arthroplasty.

Pre-operative N-terminal pro-B-type natriuretic peptide for prediction of acute kidney injury after noncardiac surgery: A retrospective cohort study

BACKGROUND

Acute kidney injury (AKI) is associated with poor outcomes after noncardiac surgery. Whether pre-operative N-terminal pro-B-type natriuretic peptide (NT-proBNP) predicts AKI after noncardiac surgery is unclear.

OBJECTIVE

To investigate the predictive role of pre-operative NT-proBNP on postoperative AKI.

DESIGN

Retrospective cohort study.

SETTING

Nanfang Hospital, Southern Medical University, China.

PATIENTS

Adult patients who had a serum creatinine and NT-proBNP measurement within 30 pre-operative days and at least one serum creatinine measurement within 7 days after noncardiac surgery between February 2008 and May 2018 were identified.

MAIN OUTCOME MEASURES

The primary outcome was postoperative AKI, defined by the kidney disease: improving global outcomes creatinine criteria.

RESULTS

In all, 6.1% (444 of 7248) of patients developed AKI within 1 week after surgery. Pre-operative NT-proBNP was an independent predictor of AKI after adjustment for clinical variables (OR comparing top to bottom quintiles 2.29, 95% CI, 1.47 to 3.65, P < 0.001 for trend; OR per 1-unit increment in natural log transformed NT-proBNP 1.27, 95% CI, 1.16 to 1.39). Compared with clinical variables alone, the addition of NT-proBNP improved model fit, modestly improved the discrimination (change in area under the curve from 0.764 to 0.773, P = 0.005) and reclassification (continuous net reclassification improvement 0.210, 95% CI, 0.111 to 0.308, improved integrated discrimination 0.0044, 95% CI, 0.0016 to 0.0072) of AKI and non-AKI cases, and achieved higher net benefit in decision curve analysis.

CONCLUSIONS

Pre-operative NT-proBNP concentrations provided predictive information for AKI in a cohort of patients undergoing noncardiac surgery, independent of and incremental to conventional risk factors. Prospective studies are required to confirm this finding and examine its clinical impact.

TRIAL REGISTRATION

Chinese Clinical Trial Registry, ChiCTR1900024056. www.chictr.org.cn/showproj.aspx?proj=40385.

Male Patients may be More Vulnerable to Acute Kidney Injury After Colorectal Surgery in an Enhanced Recovery Program: A Propensity Score Matching Analysis

BACKGROUND

Although many reports have shown that enhanced recovery after surgery (ERAS) programs improve the perioperative outcomes of patients undergoing colorectal surgery, the prevalence of early acute kidney injury (AKI) after surgery in such patients requires attention. Protective roles of the female sex in terms of chronic kidney disease and progression of ischemic renal injury have been described in many studies. We thus explored whether a sex difference was evident in terms of postoperative AKI in a colorectal ERAS setting.

METHODS

From January 2017 to August 2019, 453 patients underwent laparoscopic colorectal cancer resection in an enhanced recovery program. Of these, 217 female patients were propensity score (PS)-matched with 236 male patients. Then, 215 patients of either sex were compared in terms of postoperative renal function and complications.

RESULTS

Among the PS-matched patients, the incidence of AKI was significantly higher in male than female patients (24.2% vs. 9.8%, P < 0.001). Male patients also exhibited a greater reduction in the postoperative estimated glomerular filtration rate, compared with female patients. The male sex was associated with an approximately threefold increase in the risk of AKI. The rate of surgical complications was significantly higher in male than female patients.

CONCLUSIONS

Caution must be taken to prevent postoperative AKI in patients (particularly males) participating in colorectal ERAS programs. The mechanism underlying the sex difference remains unclear. Additional studies are required to determine whether male patients require perioperative management that differs from that of females, to prevent postoperative AKI.

External Validation of the Acute Kidney Injury Risk Prediction Score for Critically Ill Surgical Patients Who Underwent Major Non-Cardiothoracic Surgery

Background: Acute kidney injury (AKI) is a common complication encountered in an intensive care unit (ICU). In 2020, the AKI prediction score was developed specifically for critically ill surgical patients who underwent major non-cardiothoracic surgeries. This study aimed to externally validate the AKI prediction score in terms of performance and clinical utility. Methods: External validation was carried out in a prospective cohort of patients admitted to the ICU of the Faculty of Medicine Vajira Hospital between September 2014 and September 2015. The endpoint was AKI within seven days following ICU admission. Discriminative ability was based on the area under the receiver operating characteristic curves (AuROC). Calibration and clinical usefulness were evaluated. Results: A total of 201 patients were included in the analysis. AKI occurred in 37 (18.4%) patients. The discriminative ability dropped from good in the derivation cohort, to acceptable in the validation cohort (0.839 (95%CI 0.825–0.852) vs. 0.745 (95%CI 0.652–0.838)). No evidence of lack-of-fit was identified (p = 0.754). The score had potential clinical usefulness across the range of threshold probability from 10 to 50%. Conclusions: The AKI prediction score showed an acceptable discriminative performance and calibration with potential clinical usefulness for predicting AKI risk in surgical patients who underwent major non-cardiothoracic surgery.

Development and Validation of a Prediction Model for Survival in Diabetic Patients With Acute Kidney Injury

OBJECTIVE

We aimed to analyze the risk factors affecting all-cause mortality in diabetic patients with acute kidney injury (AKI) and to develop and validate a nomogram for predicting the 90-day survival rate of patients.

METHODS

Clinical data of diabetic patients with AKI who were diagnosed at The First Affiliated Hospital of Guangxi Medical University from April 30, 2011, to April 30, 2021, were collected. A total of 1,042 patients were randomly divided into a development cohort and a validation cohort at a ratio of 7:3. The primary study endpoint was all-cause death within 90 days of AKI diagnosis. Clinical parameters and demographic characteristics were analyzed using Cox regression to develop a prediction model for survival in diabetic patients with AKI, and a nomogram was then constructed. The concordance index (C-index), receiver operating characteristic curve, and calibration plot were used to evaluate the prediction model.

RESULTS

The development cohort enrolled 730 patients with a median follow-up time of 87 (40-98) days, and 86 patients (11.8%) died during follow-up. The 90-day survival rate was 88.2% (644/730), and the recovery rate for renal function in survivors was 32.9% (212/644). Multivariate analysis showed that advanced age (HR = 1.064, 95% CI = 1.043-1.085), lower pulse pressure (HR = 0.964, 95% CI = 0.951-0.977), stage 3 AKI (HR = 4.803, 95% CI = 1.678-13.750), lower 25-hydroxyvitamin D3 (HR = 0.944, 95% CI = 0.930-0.960), and multiple organ dysfunction syndrome (HR = 2.056, 95% CI = 1.287-3.286) were independent risk factors affecting the all-cause death of diabetic patients with AKI (all p < 0.01). The C-indices of the prediction cohort and the validation cohort were 0.880 (95% CI = 0.839-0.921) and 0.798 (95% CI = 0.720-0.876), respectively. The calibration plot of the model showed excellent consistency between the prediction probability and the actual probability.

CONCLUSION

We developed a new prediction model that has been internally verified to have good discrimination, calibration, and clinical value for predicting the 90-day survival rate of diabetic patients with AKI.

Postoperative acute kidney injury in adult non-cardiac surgery: joint consensus report of the Acute Disease Quality Initiative and PeriOperative Quality Initiative

Postoperative acute kidney injury (PO-AKI) is a common complication of major surgery that is strongly associated with short-term surgical complications and long-term adverse outcomes, including increased risk of chronic kidney disease, cardiovascular events and death. Risk factors for PO-AKI include older age and comorbid diseases such as chronic kidney disease and diabetes mellitus. PO-AKI is best defined as AKI occurring within 7 days of an operative intervention using the Kidney Disease Improving Global Outcomes (KDIGO) definition of AKI; however, additional prognostic information may be gained from detailed clinical assessment and other diagnostic investigations in the form of a focused kidney health assessment (KHA). Prevention of PO-AKI is largely based on identification of high baseline risk, monitoring and reduction of nephrotoxic insults, whereas treatment involves the application of a bundle of interventions to avoid secondary kidney injury and mitigate the severity of AKI. As PO-AKI is strongly associated with long-term adverse outcomes, some form of follow-up KHA is essential; however, the form and location of this will be dictated by the nature and severity of the AKI. In this Consensus Statement, we provide graded recommendations for AKI after non-cardiac surgery and highlight priorities for future research.

The Relationship between AKI and CKD in Patients with Type 2 Diabetes: An Observational Cohort Study

BACKGROUND

There are few observational studies evaluating the risk of AKI in people with type 2 diabetes, and even fewer simultaneously investigating AKI and CKD in this population. This limits understanding of the interplay between AKI and CKD in people with type 2 diabetes compared with the nondiabetic population.

METHODS

In this retrospective, cohort study of participants with or without type 2 diabetes, we used electronic healthcare records to evaluate rates of AKI and various statistical methods to determine their relationship to CKD status and further renal function decline.

RESULTS

We followed the cohort of 16,700 participants (9417 with type 2 diabetes and 7283 controls without diabetes) for a median of 8.2 years. Those with diabetes were more likely than controls to develop AKI (48.6% versus 17.2%, respectively) and have preexisting CKD or CKD that developed during follow-up (46.3% versus 17.2%, respectively). In the absence of CKD, the AKI rate among people with diabetes was nearly five times that of controls (121.5 versus 24.6 per 1000 person-years). Among participants with CKD, AKI rate in people with diabetes was more than twice that of controls (384.8 versus 180.0 per 1000 person-years after CKD diagnostic date, and 109.3 versus 47.4 per 1000 person-years before CKD onset in those developing CKD after recruitment). Decline in eGFR slope before AKI episodes was steeper in people with diabetes versus controls. After AKI episodes, decline in eGFR slope became steeper in people without diabetes, but not among those with diabetes and preexisting CKD.

CONCLUSIONS

Patients with diabetes have significantly higher rates of AKI compared with patients without diabetes, and this remains true for individuals with preexisting CKD.

Perioperative Renoprotection: General Mechanisms and Treatment Approaches

In the perioperative setting, acute kidney injury (AKI) is a frequent complication, and AKI itself is associated with adverse outcomes such as higher risk of chronic kidney disease and mortality. Various risk factors are associated with perioperative AKI, and identifying them is crucial to early interventions addressing modifiable risk and increasing monitoring for nonmodifiable risk. Different mechanisms are involved in the development of postoperative AKI, frequently picturing a multifactorial etiology. For these reasons, no single renoprotective strategy will be effective for all surgical patients, and efforts have been attempted to prevent kidney injury in different ways. Some renoprotective strategies and treatments have proven to be useful, some are no longer recommended because they are ineffective or even harmful, and some strategies are still under investigation to identify the best timing, setting, and patients for whom they could be beneficial. With this review, we aim to provide an overview of recent findings from studies examining epidemiology, risk factors, and mechanisms of perioperative AKI, as well as different renoprotective strategies and treatments presented in the literature.

Acute kidney injury risk in orthopaedic trauma patients pre and post surgery using a biomarker algorithm and clinical risk score

Acute kidney injury (AKI) after major trauma is associated with increased mortality. The aim of this study was to assess if measurement of blood biomarkers in combination with clinical characteristics could be used to develop a tool to assist clinicians in identifying which orthopaedic trauma patients are at risk of AKI. This is a prospective study of 237 orthopaedic trauma patients who were consecutively scheduled for open reduction and internal fixation of their fracture between May 2012 and August 2013. Clinical characteristics were recorded, and 28 biomarkers were analysed in patient blood samples. Post operatively a combination of H-FABP, sTNFR1 and MK had the highest predictive ability to identify patients at risk of developing AKI (AUROC 0.885). Three clinical characteristics; age, dementia and hypertension were identified in the orthopaedic trauma patients as potential risks for the development of AKI. Combining biomarker data with clinical characteristics allowed us to develop a proactive AKI clinical tool, which grouped patients into four risk categories that were associated with a clinical management regime that impacted patient care, management, length of hospital stay, and efficient use of hospital resources.