Acute Kidney Injury in Trauma Patients Admitted to Critical Care: Development and Validation of a Diagnostic Prediction Model

Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures

BACKGROUND

The incidence of nonhip femoral fractures is gradually increasing, but few studies have explored the risk factors for in-hospital death in patients with nonhip femoral fractures in the ICU or developed mortality prediction models. Therefore, we chose to study this specific patient group, hoping to help clinicians improve the prognosis of patients.

METHODS

This is a retrospective study based on the data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to screen risk factors. The receiver operating characteristic (ROC) curve was drawn, and the areas under the curve (AUC), net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. The consistency between the actual probability and the predicted probability was assessed by the calibration curve and Hosmer-Lemeshow goodness of fit test (HL test). Decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit.

RESULTS

The LASSO regression analysis showed that heart rate, temperature, red blood cell distribution width, blood urea nitrogen, Glasgow Coma Scale (GCS), Simplified Acute Physiology Score II (SAPSII), Charlson comorbidity index and cerebrovascular disease were independent risk factors for in-hospital death in patients with nonhip femoral fractures. The AUC, IDI and NRI of our model in the training set and validation set were better than those of the GCS and SAPSII scoring systems. The calibration curve and HL test results showed that our model prediction results were in good agreement with the actual results (P = 0.833 for the HL test of the training set and P = 0.767 for the HL test of the validation set). DCA showed that our model had a better clinical net benefit than the GCS and SAPSII scoring systems.

CONCLUSION

In this study, the independent risk factors for in-hospital death in patients with nonhip femoral fractures were determined, and a prediction model was constructed. The results of this study may help to improve the clinical prognosis of patients with nonhip femoral fractures.

Safety and Metabolic Tolerance of Citrate Anticoagulation in Critically Ill Polytrauma Patients with Acute Kidney Injury Requiring an Early Continuous Kidney Replacement Therapy

For severe polytrauma patients with an early AKI requiring renal replacement therapy, anticoagulation remains a great challenge. Due to a high bleeding risk, hemodynamic instability, and increased lactate levels, continuous modality (CKRT) and citrate anticoagulation seem to be the most appropriate. However, their safety with regard to the potential risk of impaired citrate metabolism is not documented. A retrospective study of 60 severe polytrauma patients admitted to the emergency department between January 2000 and December 2021 was conducted; the patients requiring CKRT during the first 72 h were treated with citrate (n. 46, group Citrate) or with heparin (n. 14, group Heparin). Out of 60 patients, 31 survived (51.7%). According to logistic regression analysis, age and SOFA score were significant predictors of mortality. The incidence of rhabdomyolysis was more common in the survivors (77.4 vs. 51.7%), and Kaplan-Meyer analysis showed a better trend towards survival at 90 days for the group Citrate than the group Heparin (p 0.0956). In the group Citrate, hemorrhagic episodes were significantly less common (0.045 vs. 0.273 episodes/day, p < 0.001); the effective duration (h/day) of CKRT was longer; and the effective net ultrafiltration rate (mL/kg/h) and blood flow rate were lower. For severe polytrauma patients, early, soft CKRT with citrate anticoagulation at a low blood flow rate and circuit citratemia showed a better safety and hemodynamic stability, suggesting that citrate should be the first choice anticoagulant in this subset of patients.

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.

Risk Factors and Outcomes of Post-traumatic Acute Kidney Injury Requiring Renal Replacement Therapy: A Case-Control Study

Background

Acute kidney injury (AKI) following severe trauma is common. However, the requirement of renal replacement therapy (RRT) in these patients is rare and is associated with high morbidity and mortality. The primary objective of this study was to identify odds of risk factors, in particular, hypotension at presentation, for the requirement of RRT in patients with AKI following trauma.

Methods

We performed a case-control study involving patients who were admitted to the intensive care unit (ICU) at a level I trauma center for at least 24 hours. The primary outcome measure was a study of the odds of risk factors associated with the requirement of RRT in such patients. Univariate comparisons and multiple logistic regression analyses were done to identify other risk factors.

Results

The presence of crush injury, sepsis, and elevated serum creatinine (sCr) on arrival were identified to be independent risk factors for RRT requirement. Hypotension and exposure to radiocontrast or nephrotoxic antimicrobials were not found to be associated with the need for RRT. Acute kidney injury requiring RRT was associated with significantly increased ICU length of stay (15 days vs 5 days; p < 0.001) and higher mortality (83% vs 35%; p < 0.001).

Conclusion

The presence of crush injury, sepsis, and elevated sCr on presentation were identified to be independent risk factors while hypotension association was insignificant for AKI requiring RRT in our investigation.

How to cite this article

Soni KD, Singh A, Tyagi A, Singh Y, Aggarwal R, Trikha A. Risk Factors and Outcomes of Post-traumatic Acute Kidney Injury Requiring Renal Replacement Therapy: A Case-Control Study. Indian J Crit Care Med 2023;27(1):22-25.

Generalizability of an acute kidney injury prediction model across health systems

Delays in the identification of acute kidney injury (AKI) in hospitalized patients are a major barrier to the development of effective interventions to treat AKI. A recent study by Tomasev and colleagues at DeepMind described a model that achieved a state-of-the-art performance in predicting AKI up to 48 hours in advance.1 Because this model was trained in a population of US Veterans that was 94% male, questions have arisen about its reproducibility and generalizability. In this study, we aimed to reproduce key aspects of this model, trained and evaluated it in a similar population of US Veterans, and evaluated its generalizability in a large academic hospital setting. We found that the model performed worse in predicting AKI in females in both populations, with miscalibration in lower stages of AKI and worse discrimination (a lower area under the curve) in higher stages of AKI. We demonstrate that while this discrepancy in performance can be largely corrected in non-Veterans by updating the original model using data from a sex-balanced academic hospital cohort, the worse model performance persists in Veterans. Our study sheds light on the importance of reproducing artificial intelligence studies, and on the complexity of discrepancies in model performance in subgroups that cannot be explained simply on the basis of sample size.

A Transfer Learning Approach to Correct the Temporal Performance Drift of Clinical Prediction Models: Retrospective Cohort Study

Background

Clinical prediction models suffer from performance drift as the patient population shifts over time. There is a great need for model updating approaches or modeling frameworks that can effectively use the old and new data.

Objective

Based on the paradigm of transfer learning, we aimed to develop a novel modeling framework that transfers old knowledge to the new environment for prediction tasks, and contributes to performance drift correction.

Methods

The proposed predictive modeling framework maintains a logistic regression–based stacking ensemble of 2 gradient boosting machine (GBM) models representing old and new knowledge learned from old and new data, respectively (referred to as transfer learning gradient boosting machine [TransferGBM]). The ensemble learning procedure can dynamically balance the old and new knowledge. Using 2010-2017 electronic health record data on a retrospective cohort of 141,696 patients, we validated TransferGBM for hospital-acquired acute kidney injury prediction.

Results

The baseline models (ie, transported models) that were trained on 2010 and 2011 data showed significant performance drift in the temporal validation with 2012-2017 data. Refitting these models using updated samples resulted in performance gains in nearly all cases. The proposed TransferGBM model succeeded in achieving uniformly better performance than the refitted models.

Conclusions

Under the scenario of population shift, incorporating new knowledge while preserving old knowledge is essential for maintaining stable performance. Transfer learning combined with stacking ensemble learning can help achieve a balance of old and new knowledge in a flexible and adaptive way, even in the case of insufficient new data.

The Clinical Impact of Platelets on Post-Injury Serum Creatinine Concentration in Multiple Trauma Patients: A Retrospective Cohort Study

Background and objective: Platelets contribute to the immunological response after multiple trauma. To determine the clinical impact, this study analyzes the association between platelets and creatinine concentration as an indicator of kidney function in polytraumatized patients. Methods: We investigated all patients presenting an Injury Severity Score (ISS) ≥16 for a 2-year period at our trauma center. Platelet counts and creatinine concentrations were analyzed, and correlation analysis was performed within 10 days after multiple trauma. Results: 83 patients with a median ISS of 22 were included. Platelet count was decreased on day 3 (p ≤ 0.001) and increased on day 10 (p ≤ 0.001). Platelet count was elevated on day 10 in younger patients and diminished in severely injured patients (ISS ≥35) on day 1 (p = 0.012) and day 3 (p = 0.011). Creatinine concentration was decreased on day 1 (p = 0.003) and day 10 (p ≤ 0.001) in female patients. Age (p = 0.01), male sex (p = 0.004), and injury severity (p = 0.014) were identified as factors for increased creatinine concentration on day 1, whereas platelets (p = 0.046) were associated with decreased creatinine concentrations on day 5 after multiple trauma. Conclusions: Kinetics of platelet count and creatinine concentration are influenced by age, gender, and trauma severity. There was no clear correlation between platelet counts and creatinine concentration. However, platelets seem to have a modulating effect on creatinine concentrations in the vulnerable phase after trauma.

Admission serum myoglobin and the development of acute kidney injury after major trauma

BACKGROUND

Myoglobin and creatine kinase (CK) are both established markers of muscle injury but their hospital admission values have never been compared to predict post-traumatic acute kidney injury (AKI).

METHODS

An observational registry study of consecutive trauma patients admitted to a major regional trauma centre. The primary outcome was stage 1 or more AKI in the first 7 days after trauma. We assessed the association of hospital admission myoglobin or CK with development of AKI both alone and when added to two existing risk prediction models for post traumatic AKI.

RESULTS

Of the 857 trauma patients (median age 36 [25-52], 96% blunt trauma, median ISS of 20 [12-47]) included, 102 (12%) developed AKI. Admission myoglobin performed better than CK to predict AKI any stage with an AUC-ROC of 0.74 (95% CI 0.68-0.79) and 0.63 (95% CI 0.57-0.69), respectively (p < 0.001). Admission myoglobin also performed better than CK to predict AKI stage 2 or 3 [AUC-ROC of 0.79 (95% CI 0.74-0.84) and 0.74 (95% CI 0.69-0.79), respectively (p < 0.001)] with a best cutoff value of 1217 µg/L (sensitivity 74%, specificity 77%). Admission myoglobin added predictive value to two established models of AKI prediction and showed significant ability to reclassify subjects regarding AKI status, while admission CK did not. Decision curve analysis also revealed that myoglobin added net benefit to established predictive models. Admission myoglobin was better than CK at predicting development of significant rhabdomyolysis.

CONCLUSIONS

Admission myoglobin better predicts the development of AKI and severe rhabdomyolysis after major trauma. Admission myoglobin should be added in established predictive models of post-traumatic AKI to early identify high-risk patients.

Importance of duration of acute kidney injury after severe trauma: a cohort study

Background

Acute kidney injury (AKI) is common after severe trauma. AKI incidence and AKI stage have previously been shown to be associated with poor outcomes after trauma. However, AKI duration may also be important for outcomes after trauma, given that it is associated with long-term morbidity and mortality in general intensive care unit (ICU) and hospitalized patients. We hypothesized that duration of AKI is independently associated with poor outcomes after trauma.

Methods

A cohort study was conducted at a single, level 1 trauma center. Patients admitted to the ICU between 2009 and 2018 were included. Data were extracted from the trauma registry and electronic medical records. AKI within 7 days from presentation was defined according to the Kidney Disease Improving Global Outcomes guidelines. Multivariable analyses were performed to assess the association between AKI incidence, AKI stage, and AKI duration with outcomes including prolonged ICU and hospital length of stay, discharge to home, and mortality.

Results

Of 7049 patients included, 72% were male, the median age was 41 years (IQR 27–58), and 10% died. The AKI incidence was 45%, with 69% of these patients presenting with AKI on arrival. The majority (73%) of patients who suffered AKI recovered within 2 days. After adjustment in separate models, AKI incidence, AKI stage and AKI duration were each associated with prolonged hospitalization, an unfavorable discharge disposition, and mortality. AKI stage and duration were not used in the same model due to collinearity.

Conclusions

Post-traumatic AKI was common on arrival and frequently short lasting. Duration correlated with highest AKI stage, and both were separately associated with prolonged hospitalization, discharge destination other than home, and mortality on adjusted analyses. Given the high incidence of AKI on arrival, stage or duration may be better targets for future interventions and quality improvement initiatives to improve outcomes after post-traumatic AKI.

Level of evidence

III. Prognostic.

Prevalence and risk factors of acute kidney injury in polytrauma patients at Muhimbili Orthopedic Institute, Tanzania

Background

Polytrauma can lead to multi-organ dysfunction in addition to the local injuries. Acute kidney injury (AKI) is one of the most common causes and contributors to the high morbidity and mortality. Prevalence of acute kidney injury in trauma patients is as reported to be as high as 40.3%. Early detection and management leads to better outcomes. The prevalence of AKI among polytrauma patients remains unknown in our setting.

Methodology

A cross-sectional study involving all adults with polytrauma who presented at the emergency department at Muhimbili Orthopedic Institute (MOI) was designed. A score of ≥18 on the New Injury Severity Score (NISS) screening tool was used to identify polytrauma patients. The Kidney Disease Improving Global Outcomes (KDIGO) criteria was used to identify patient with polytrauma who developed acute kidney injury. Descriptive statistics were then obtained followed by hypothesis testing between variables with the chi squared test. Logistic regression models were used to determine factors associated with acute kidney injury.

Results

More than half (56.4%) of the patients were between 26 and 40 years and 92.3% of the polytrauma patients were males. Almost 2/5th (38.5%) of the polytrauma patients had acute kidney injury – half of these had stage 1 AKI, 33.3% had stage 2 AKI and the remaining 16.7% had stage 3 AKI. On multivariate logistic regression, it was found that patients who were older than 45 years (OR 8.53, CI 1.65–43.89, p = 0.01) and those patients with Systemic Inflammatory Response Syndrome (SIRS) (OR 21.83, CI 1.66–286.2, p = 0.019) had higher risk of acute kidney injury.

Conclusion

There is high prevalence of AKI among polytrauma patients. Elderly patients and those with SIRS were seen to have higher likelihood of AKI.

Urinary cell cycle arrest proteins urinary tissue inhibitor of metalloprotease 2 and insulin-like growth factor binding protein 7 predict acute kidney injury after severe trauma: A prospective observational study

BACKGROUND

Recognition and clinical diagnosis of acute kidney injury (AKI) after trauma is difficult. The majority of trauma patients do not have a known true baseline creatinine, which makes application of the guidelines set forth by the international guidelines difficult to apply. Use of alternative biomarkers of renal dysfunction in trauma patients may be beneficial. We hypothesized that urinary tissue inhibitor of metalloprotease 2 (TIMP-2) × insulin-like growth factor binding protein 7 (IGFBP-7) would accurately predict AKI development in severely injured trauma patients.

METHODS

A prospective observational study of adult (≥16 years old) trauma intensive care unit (ICU) patients was performed between September 2018 to March 2019. Urine was collected on ICU admission and was measured for TIMP-2 × IGFBP-7. Univariate, multivariable, and receiver operating characteristic curve analyses were performed using the optimal threshold generated by a Youden index.

MAIN RESULTS

Of 88 included patients, 75% were male, with a median injury severity score was 27 (interquartile range [IQR], 17-34), and age of 40 years (IQR, 28-54 years). Early AKI developed in 39 patients (44%), and of those, 7 (8%) required dialysis within 48 hours. Patients without early AKI had a TIMP-2 × IGFBP-7 of 0.17 U (IQR, 0.1-0.3 U), while patients with early AKI had a TIMP-2 × IGFBP-7 of 0.46 U (IQR, 0.17-1.29 U; p < 0.001). On multivariable analyses, TIMP-2 × IGFBP-7 was associated with AKI development (p = 0.02) and need for dialysis (p = 0.03). Using the optimal threshold 0.33 U to predict AKI, the area under the receiver operating characteristic curve was 0.731, with an accuracy of 0.75, sensitivity of 0.72, and specificity of 0.78.

CONCLUSION

Urinary TIMP-2 × IGFBP-7 measured on ICU admission accurately predicted 48-hour AKI and was independently associated with AKI and dialysis requirement after trauma and is a promising screening tool for treatment.

LEVEL OF EVIDENCE

Prognostic, prospective, observational study, level III.

Long-term outcomes following vehicle trauma related acute kidney injury requiring renal replacement therapy: a nationwide population study

Acute kidney injury (AKI) is a frequent complication of traumatic injury; however, long-term outcomes such as mortality and end-stage kidney disease (ESKD) have been rarely reported in this important patient population. We compared the long-term outcome of vehicle-traumatic and non-traumatic AKI requiring renal replacement therapy (AKI-RRT). This nationwide cohort study used data from the Taiwan National Health Insurance Research Database. Vehicle-trauma patients who were suffered from vehicle accidents developing AKI-RRT during hospitalization were identified, and matching non-traumatic AKI-RRT patients were identified between 2000 and 2010. The incidences of ESKD, 30-day, and long-term mortality were evaluated, and clinical and demographic associations with these outcomes were identified using Cox proportional hazards regression models. 546 vehicle-traumatic AKI-RRT patients, median age 47.6 years (interquartile range: 29.0–64.3) and 76.4% male, were identified. Compared to non-traumatic AKI-RRT, vehicle-traumatic AKI-RRT patients had longer length of stay in hospital [median (IQR):15 (5–34) days vs. 6 (3–11) days; p < 0.001). After propensity matching with non-traumatic AKI-RRT cases with similar demographic and clinical characteristics. Vehicle-traumatic AKI-RRT patients had lower rates of long-term mortality (adjusted hazard ratio (HR), 0.473; 95% CI, 0.392–0.571; p < 0.001), but similar rates of ESKD (HR, 1.166; 95% CI, 0.829–1.638; p = 0.377) and short-term risk of death (HR, 1.134; 95% CI, 0.894–1.438; p = 0.301) as non-traumatic AKI-RRT patients. In competing risk models that focused on ESKD, vehicle-traumatic AKI-RRT patients were associated with lower ESKD rates (HR, 0.552; 95% CI, 0.325–0.937; p = 0.028) than non-traumatic AKI-RRT patients. Despite severe injuries, vehicle-traumatic AKI-RRT patients had better long-term survival than non-traumatic AKI-RRT patients, but a similar risk of ESKD. Our results provide a better understanding of long-term outcomes after vehicle-traumatic AKI-RRT.

Clinical risk factors and inflammatory biomarkers of post-traumatic acute kidney injury in combat patients

BACKGROUND

Post-traumatic acute kidney injury has occurred in every major military conflict since its initial description during World War II. To ensure the proper treatment of combat casualties, early detection is critical. This study therefore aimed to investigate combat-related post-traumatic acute kidney injury in recent military conflicts, used machine learning algorithms to identify clinical and biomarker variables associated with the development of post-traumatic acute kidney injury, and evaluated the effects of post-traumatic acute kidney injury on wound healing and nosocomial infection.

METHODS

We conducted a retrospective clinical cohort review of 73 critically injured US military service members who sustained major combat-related extremity wounds and had collected injury characteristics, assayed serum and tissue biopsy samples for the expression of protein and messenger ribonucleic acid biomarkers. Bivariate analyses and random forest recursive feature elimination classification algorithms were used to identify associated injury characteristics and biomarker variables.

RESULTS

The incidence of post-traumatic acute kidney injury was 20.5%. Of that, 86% recovered baseline renal function and only 2 (15%) of the acute kidney injury group required renal replacement therapy. Random forest recursive feature elimination algorithms were able to estimate post-traumatic acute kidney injury with the area under the curve of 0.93, sensitivity of 0.91, and specificity of 0.91. Post-traumatic acute kidney injury was associated with injury severity score, serum epidermal growth factor, and tissue activin A type receptor 1, matrix metallopeptidase 10, and X-C motif chemokine ligand 1 expression. Patients with post-traumatic acute kidney injury exhibited poor wound healing and increased incidence of nosocomial infections.

CONCLUSION

The occurrence of acute kidney injury in combat casualties may be estimated using injury characteristics and serum and tissue biomarkers. External validations of these models are necessary to generalize for all trauma patients.

The incidence and associations of acute kidney injury in trauma patients admitted to critical care: A systematic review and meta-analysis

BACKGROUND

As more patients are surviving the initial effects of traumatic injury clinicians are faced with managing the systemic complications of severe tissue injury. Of these, acute kidney injury (AKI) may be a sentinel complication contributing to adverse outcomes.

OBJECTIVE

To establish the incidence of AKI in patients admitted to critical care after major trauma, to explore any risk factors and to evaluate the association of AKI with outcomes.

DATA SOURCES

Systematic search of MEDLINE, Excerpta Medica database and Cochrane library from January 2004 to April 2018.

STUDY SELECTION

Studies of adult major trauma patients admitted to critical care that applied consensus AKI criteria (risk injury failure loss end stage [RIFLE], AKI network, or kidney disease improving global outcomes) and reported clinical outcomes were assessed (PROSPERO Registration: CRD42017056781). Of the 35 full-text articles selected from the screening, 17 (48.6%) studies were included.

DATA EXTRACTION AND SYNTHESIS

We followed the PRISMA guidelines and study quality was assessed using the Newcastle-Ottawa score. The pooled incidence of AKI and relative risk of death were estimated using random-effects models.

MAIN OUTCOMES AND MEASURES

Incidence of AKI was the primary outcome. The secondary outcome was study-defined mortality.

RESULTS

We included 17 articles describing AKI outcomes in 24,267 trauma patients. The pooled incidence of AKI was 20.4% (95% confidence interval [CI], 16.5-24.9). Twelve studies reported the breakdown of stages of AKI with 55.7% of patients classified as RIFLE-R or stage 1, 30.3% as RIFLE-I or stage 2, and 14.0% as RIFLE-F or stage 3. The pooled relative risk of death with AKI compared was 3.6 (95% CI, 2.4-5.3). In addition, there was a concordant increase in odds of death among six studies that adjusted for multiple variables (adjusted odds ratio, 2.7; 95% CI, 1.9-3.8; p = <0.01).

CONCLUSION

Acute kidney injury is common after major trauma and associated with increased mortality. Future research is warranted to reduce the potential for harm associated with this subtype of AKI.

LEVEL OF EVIDENCE

Systematic review and meta-analysis, level III.

Trauma-associated acute kidney injury

PURPOSE OF REVIEW

A summary of recent research into the epidemiology, cause, management and outcomes of trauma-associated acute kidney injury (AKI). There is an increasing focus on subtypes of AKI to better target clinical management and future research.

RECENT FINDINGS

AKI associated with trauma occurs in 20-24% of patients admitted to ICU. On the basis of creatinine and/or urine output, AKI occurs in the first few days of traumatic illness. Although various associations have been identified, shock and high-volume blood transfusion are the most consistent risks for development of trauma-associated AKI. Short-term outcomes appear worse for patients with AKI, but extent of longer term kidney function recovery remains unknown. Recent research in the general critical care population is beginning to better inform AKI management; however, currently, preventive and supportive strategies remain the mainstay of AKI management after trauma.

SUMMARY

Well-designed, prospective research is required to better understand the phenotype, pathophysiology and recovery trajectory of trauma-associated AKI. Only then can potentially unique therapeutic targets be developed for this common subtype of AKI.

Is there an indication to utilize intravenous iron in acute trauma patients? Why, how, and when

PURPOSE OF REVIEW

Traumatic injury has been described as a growing pandemic which has significant implications for global health. In the trauma setting, anemia is a common occurrence and is frequently inadequately addressed. It is associated with significant morbidity and incurs great cost - both to the patient and to the health system. The cause is multifactorial, and the pathophysiology is incompletely understood. Appropriate care of the trauma patient is a multidisciplinary responsibility and a focused approach to anemia is vital. The recommendation for restrictive transfusion strategies and the potential benefit of intravenous iron (IVI) in the perioperative setting, make the intervention an attractive proposition in the anemic trauma patient.

RECENT FINDINGS

In an era where the importance of patient blood management is recognized, there is significant attention being given to both the implications and the appropriate management of anemia, in various settings. Advances have been made in the understanding of the mechanisms underlying the anemia associated with traumatic injury and the efficacy of current interventions is being explored. This increased understanding of the pathophysiology behind the condition has also facilitated the postulation of potential therapeutic targets for the future.

SUMMARY

Suboptimally managed anemia impacts on clinical outcome and contributes to the burden of costs associated with trauma. The cause of the anemia associated with trauma is multifactorial and should be addressed at several levels. The role of IVI in this setting is yet to be clearly defined.

Validation of acute kidney injury prediction scores in critically ill patients

Prediction of acute kidney injury (AKI) in critically ill patients allows prompt intervention that improves outcome. We aimed for external validation of two AKI prediction scores that can be bedside calculated. A prospective observational study included patients admitted to medical and surgical critical care units. Performance of two AKI prediction scores, Malhotra score and acute kidney injury prediction score (APS), was assessed for their ability to predict AKI. The best cutoff point for each score was determined by Youden index. Area under the receiving operation characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were used to assess performance of each score. Univariate and multivariate regression analyses were done to detect the predictability of AKI. Goodness-of-fit and kappa Cohen agreement tests were done to show whether the expected score results fit well and agree with the observed results. AKI prevalence was 37.6%. The best cutoff values were 5 and 4 for Malhotra score and APS, respectively. Area under the curve for Malhotra 5 was 0.712 and for APS 4 was 0.652 with nearly similar sensitivity and specificity. Regression analysis demonstrated that Malhotra 5 was the independent predictor of AKI. Goodness-of-fit test showed significant results denoting lack of fit between the scores and the actual results. Kappa test showed moderate agreement for Malhotra 5 and fair agreement for APS 4. Both scores showed moderate performance for AKI prediction. Malhotra 5 showed better performance compared to APS 4. Multicenter international study is warranted to develop a universal model that can predict AKI in critically ill patients.

Positive Fluid Balance and Association with Post-Traumatic Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is common in severely injured trauma patients and is associated with poor outcomes. A positive fluid balance is associated with AKI and poor long-term renal outcomes among general ICU and cardiac surgery patients. Currently, the optimal endpoint of resuscitation of severely injured trauma patients is unknown, which may result in excess fluid administration. We hypothesized that positive fluid balance is common after severe trauma and is associated with increased AKI development.

STUDY DESIGN

A cohort study of adult (≥16 years old) trauma patients requiring ICU admission from January 2017 to June of 2017 was conducted. Patients were excluded for early death, rhabdomyolysis, or previous history of end-stage renal disease or congestive heart failure. Acute kidney injury within 7 days of admission was defined according to Kidney Disease Improving Global Outcomes creatinine-based criteria. Univariate and multivariable analyses were performed.

RESULTS

Of 364 patients, 74% were male. The median age was 41 years (interquartile range [IQR] 27 to 59 years), and the median Injury Severity Score (ISS) was 18 (IQR 10 to 29). Positive fluid balance (>2 L) was observed in 49% of patients. Acute kidney injury was diagnosed in 105 (29%) patients. After adjustment, there was an increased risk of AKI with a positive fluid balance >2 L (relative risk [RR] 1.98 [95% CI 1.24 to 3.17]). Additionally, the risk of AKI incrementally increased by 1.22 with each liter fluid positive above a zero balance (95% CI 1.11 to 1.34).

CONCLUSIONS

Positive fluid balance in excess of 2 L at 48 hours occurs in half of severely injured trauma patients, and fluid positivity is independently and incrementally associated with AKI development. Fluid responsiveness should be investigated as an end point of post-traumatic resuscitation to prevent unnecessary fluid administration and subsequent AKI.

EFFECT OF COPAIBA OIL IN INTESTINAL MUCOSA OF RATS SUBMITTED TO HYPOVOLEMIC SHOCK

Background:

Hypovolemic shock is a common disease in polytrauma patients and may develop ischemia in various organs, increasing morbidity and mortality. The bowel is usually most affected by this condition.

Aim:

To evaluate the effects of copaiba oil on the intestinal mucosa’s injury of rats submitted to hypovolemic shock.

Method:

Fifteen rats were divided into three groups: sham - simulated surgery; ischemia - animals submitted to hypovolemic shock; and copaiba - animals submitted to hypovolemic shock previously treated with copaiba oil. Mean blood pressure, arterial blood gas after shock induction, degree of intestinal lesion and villus length were evaluated.

Results:

The sham presented the lowest values of lactate and PaCO₂ and the highest values of mean arterial pressure, pH and bicarbonate in relation to the other groups. The degree of mesenteric lesion was zero in the sham group; 3.00±1.00 in the ischemia group; and 3.00±0.71 in the copaiba group. The villus length was 173.60±8.42 in the sham, 142.77±8.33 in the ischemia and 143.01±9.57 in the copaiba group. There was a significant difference between the sham and the other groups (p<0.05); however, there not significant difference between groups Ischemia and copaiba.

Conclusion:

Administration of copaiba oil did not reduce the intestinal mucosa lesion of rats after hypovolemic shock.

Machine learning versus physicians' prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor

Background

Early diagnosis of acute kidney injury (AKI) is a major challenge in the intensive care unit (ICU). The AKIpredictor is a set of machine-learning-based prediction models for AKI using routinely collected patient information, and accessible online. In order to evaluate its clinical value, the AKIpredictor was compared to physicians’ predictions.

Methods

Prospective observational study in five ICUs of a tertiary academic center. Critically ill adults without end-stage renal disease or AKI upon admission were considered for enrollment. Using structured questionnaires, physicians were asked upon admission, on the first morning, and after 24 h to predict the development of AKI stages 2 or 3 (AKI-23) during the first week of ICU stay. Discrimination, calibration, and net benefit of physicians’ predictions were compared against the ones by the AKIpredictor.

Results

Two hundred fifty-two patients were included, 30 (12%) developed AKI-23. In the cohort of patients with predictions by physicians and AKIpredictor, the performance of physicians and AKIpredictor were respectively upon ICU admission, area under the receiver operating characteristic curve (AUROC) 0.80 [0.69–0.92] versus 0.75 [0.62–0.88] (n = 120, P = 0.25) with net benefit in ranges 0–26% versus 0–74%; on the first morning, AUROC 0.94 [0.89–0.98] versus 0.89 [0.82–0.97] (n = 187, P = 0.27) with main net benefit in ranges 0–10% versus 0–48%; after 24 h, AUROC 0.95 [0.89–1.00] versus 0.89 [0.79–0.99] (n = 89, P = 0.09) with main net benefit in ranges 0–67% versus 0–50%.

Conclusions

The machine-learning-based AKIpredictor achieved similar discriminative performance as physicians for prediction of AKI-23, and higher net benefit overall, because physicians overestimated the risk of AKI. This suggests an added value of the systematic risk stratification by the AKIpredictor to physicians’ predictions, in particular to select high-risk patients or reduce false positives in studies evaluating new and potentially harmful therapies. Due to the low event rate, future studies are needed to validate these findings.

Trial registration

ClinicalTrials.gov, NCT03574896 registration date: July 2nd, 2018

Electronic supplementary material

The online version of this article (10.1186/s13054-019-2563-x) contains supplementary material, which is available to authorized users.

Obese trauma patients have increased need for dialysis

PURPOSE

Obesity is a risk factor for the development of acute kidney injury but its effect on the need for dialysis in trauma has not been elucidated. Additionally, the contribution that obesity has towards risk of mortality in trauma is unclear. We hypothesized that patients with a higher body mass index (BMI) will have a higher risk for need of dialysis and mortality after trauma.

METHODS

This is a retrospective analysis using the National Trauma Data Bank. All patients ≥ 8 years old were grouped based on BMI: normal (18.5-24.99 kg/m²), obese (30-34.99 kg/m²), severely obese (35-39.99 kg/m²) and morbidly obese (≥ 40 kg/m²). The primary outcome was hemodialysis initiation. The secondary outcome was mortality during the index hospitalization.

RESULTS

From 988,988 trauma patients, 571,507 (57.8%) had a normal BMI, 233,340 (23.6%) were obese, 94,708 (9.6%) were severely obese, and 89,433 (9.0%) were morbidly obese. The overall rate of hemodialysis was 0.3%. After adjusting for covariates, we found that obese (OR 1.36, CI 1.22-1.52, p < 0.001), severely obese (OR 1.89, CI 1.66-2.15, p < 0.001) and morbidly obese (OR 2.04, CI 1.82-2.29, p < 0.001) patients had a stepwise increased need for hemodialysis after trauma. Obese patients had decreased (OR 0.92, CI 0.88-0.95, p < 0.001), severely obese had similar (OR 1.02, CI 0.97-1.08, p = 0.50) and morbidly obese patients had increased (OR 1.06, CI 1.01-1.12, p = 0.011) risk of mortality after trauma.

CONCLUSIONS

Obesity was associated with an increased risk for dialysis after trauma. Mortality risk was reduced in obese, similar in severely obese, and increased in morbidly obese trauma patients suggesting an inflection threshold BMI for risk of mortality in trauma.

Acute kidney injury in trauma patients admitted to the ICU: a systematic review and meta-analysis

PURPOSE

To perform a systematic review and meta-analysis of acute kidney injury (AKI) in trauma patients admitted to the intensive care unit (ICU).

METHODS

We conducted a systematic literature search of studies on AKI according to RIFLE, AKIN, or KDIGO criteria in trauma patients admitted to the ICU (PROSPERO CRD42017060420). We searched PubMed, Cochrane Database of Systematic Reviews, UpToDate, and NICE through 3 December 2018. Data were collected on incidence of AKI, risk factors, renal replacement therapy (RRT), renal recovery, length of stay (LOS), and mortality. Pooled analyses with random effects models yielded mean differences, OR, and RR, with 95% CI.

RESULTS

Twenty-four observational studies comprising 25,182 patients were included. Study quality (Newcastle-Ottawa scale) was moderate. Study heterogeneity was substantial. Incidence of post-traumatic AKI in the ICU was 24% (20-29), of which 13% (10-16) mild, 5% (3-7) moderate, and 4% (3-6) severe AKI. Risk factors for AKI were African American descent, high age, chronic hypertension, diabetes mellitus, high Injury Severity Score, abdominal injury, shock, low Glasgow Coma Scale (GCS) score, high APACHE II score, and sepsis. AKI patients had 6.0 (4.0-7.9) days longer ICU LOS and increased risk of death [RR 3.4 (2.1-5.7)] compared to non-AKI patients. In patients with AKI, RRT was used in 10% (6-15). Renal recovery occurred in 96% (78-100) of patients.

CONCLUSIONS

AKI occurred in 24% of trauma patients admitted to the ICU, with an RRT use among these of 10%. Presence of AKI was associated with increased LOS and mortality, but renal recovery in AKI survivors was good.

Trauma induced acute kidney injury

Background

Injured patients are at risk of developing acute kidney injury (AKI), which is associated with increased morbidity and mortality. The aim of this study is to describe the incidence, timing, and severity of AKI in a large trauma population, identify risk factors for AKI, and report mortality outcomes.

Methods

A prospective observational study of injured adults, who met local criteria for trauma team activation, and were admitted to a UK Major Trauma Centre. AKI was defined by the Kidney Disease Improving Global Outcomes (KDIGO) criteria. Multivariable logistic regression and Cox proportional hazard modelling was used to analyse parameters associated with AKI and mortality.

Results

Of the 1410 patients enrolled in the study, 178 (12.6%) developed AKI. Age; injury severity score (ISS); admission systolic blood pressure, lactate and serum creatinine; units of Packed Red Blood Cells transfused in first 24 hours and administration of nephrotoxic therapy were identified as independent risk factors for the development of AKI. Patients that developed AKI had significantly higher mortality than those with normal renal function (47/178 [26.4%] versus 128/1232 [10.4%]; OR 3.09 [2.12 to 4.53]; p<0.0001). After adjusting for other clinical prognostic factors, AKI was an independent risk factor for mortality.

Conclusions

AKI is a frequent complication following trauma and is associated with prolonged hospital length of stay and increased mortality. Future research is needed to improve our ability to rapidly identify those at risk of AKI, and develop resuscitation strategies that preserve renal function in trauma patients.

Prevalence and risk factors for acute kidney injury among trauma patients: a multicenter cohort study

Background

Organ failure, including acute kidney injury (AKI), is the third leading cause of death after bleeding and brain injury in trauma patients. We sought to assess the prevalence, the risk factors and the impact of AKI on outcome after trauma.

Methods

We performed a retrospective analysis of prospectively collected data from a multicenter trauma registry. AKI was defined according to the risk, injury, failure, loss of kidney function and end-stage kidney disease (RIFLE) classification from serum creatinine only. Prehospital and early hospital risk factors for AKI were identified using logistic regression analysis. The predictive models were internally validated using bootstrapping resampling technique.

Results

We included 3111 patients in the analysis. The incidence of AKI was 13% including 7% stage R, 3.7% stage I and 2.3% stage F. AKI incidence rose to 42.5% in patients presenting with hemorrhagic shock; 96% of AKI occurred within the 5 first days after trauma. In multivariate analysis, prehospital variables including minimum prehospital mean arterial pressure, maximum prehospital heart rate, secondary transfer to the trauma center and data early collected after hospital admission including injury severity score, renal trauma, blood lactate and hemorrhagic shock were independent risk factors in the models predicting AKI. The model had good discrimination with area under the receiver operating characteristic curve of 0.85 (0.82–0.88) to predict AKI stage I or F and 0.80 (0.77–0.83) to predict AKI of all stages. Rhabdomyolysis severity, assessed by the creatine kinase peak, was an additional independent risk factor for AKI when it was forced into the model (OR 1.041 (1.015–1.069) per step of 1000 U/mL, p < 0.001). AKI was independently associated with a twofold increase in ICU mortality.

Conclusions

AKI has an early onset and is independently associated with mortality in trauma patients. Its prevalence varies by a factor 3 according to the severity of injuries and hemorrhage. Prehospital and early hospital risk factors can provide good performance for early prediction of AKI after trauma. Hence, studies aiming to prevent AKI should target patients at high risk of AKI and investigate therapies early in the course of trauma care.

Electronic supplementary material

The online version of this article (10.1186/s13054-018-2265-9) contains supplementary material, which is available to authorized users.