Serum Procalcitonin Level Predicts Acute Kidney Injury After Traumatic Brain Injury

Correlation of preoperative inflammatory factors and emotional disorders with postoperative delirium in patients with craniocerebral trauma

BACKGROUND

Traumatic brain injury (TBI) imposes a substantial societal and familial burden due to its high disability and fatality rates, rendering it a serious public health problem. Some patients with TBI have poor treatment outcomes and are prone to postoperative delirium (POD), which affects their quality of life. Anxiety has been linked to increased POD incidence in some studies, while others have found no correlation.

AIM

To investigate the correlation of POD risk factors, preoperative inflammatory factors, and mood disorders in patients with TBI.

METHODS

We retrospectively collected data on the treatment of 80 patients with TBI from November 2021 to September 2023. Patients were grouped as POD and non-POD, according to their POD status, and the general data of the two groups were compared. Inflammatory factor levels were detected preoperatively, and the Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA) were used to investigate the risk factors associated with POD in these patients. Logistic regression was used to identify the independent risk factors.

RESULTS

Twenty-one patients (26.25%) developed POD, including 7, 10, and 4 cases of the excitatory, inhibitory, and mixed types, respectively. There were 59 cases (73.75%) in the non-POD group. Compared with the non-POD group, the POD group had a significantly higher proportion of patients with low Glasgow Coma Scale (GCS) scores before admission, unilateral mydriasis, preoperative hemorrhagic shock, intraventricular hemorrhage (IVH), and postoperative hyperglycemic hyperosmolar disease (P < 0.05). In the POD group, interleukin-6 (IL-6), human tumor necrosis factor-α (TNF-α), myeloperoxidase levels, HAMA, and HAMD scores were higher than those in the non-POD group (all P < 0.05). Logistic multivariate analysis showed that GCS score at admission, IVH, IL-6, TNF-α, HAMA, and HAMD were independent risk factors for POD in patients with TBI (P < 0.05).

CONCLUSION

Low GCS score at admission, IVH, elevated IL-6 and TNF-α, other inflammatory indicators, anxiety, and depression, can increase the risk of POD in patients with TBI after surgery.

Association of hyperchloremia and acute kidney injury in pediatric patients with moderate and severe traumatic brain injury

PURPOSE

Acute kidney injury (AKI) is an established complication of adult traumatic brain injury (TBI) and known risk factor for mortality. Evidence demonstrates an association between hyperchloremia and AKI in critically ill adults but studies in children are scarce. Given frequent use of hypertonic saline in the management of pediatric TBI, we believe the incidence of hyperchloremia will be high and hypothesize that it will be associated with development of AKI.

METHODS

Single-center retrospective cohort study was completed at an urban, level 1 pediatric trauma center. Children > 40 weeks corrected gestational age and < 21 years of age with moderate or severe TBI (presenting GCS < 13) admitted between January 2016 and December 2021 were included. Primary study outcome was presence of AKI (defined by pediatric Kidney Disease: Improving Global Outcomes criteria) within 7 days of hospitalization and compared between patients with and without hyperchloremia (serum chloride ≥ 110 mEq/L).

RESULTS

Fifty-two children were included. Mean age was 5.75 (S.D. 5.4) years; 60% were male (31/52); and mean presenting GCS was 6 (S.D. 2.9). Thirty-seven patients (71%) developed hyperchloremia with a mean peak chloride of 125 (S.D. 12.0) mEq/L and mean difference between peak and presenting chloride of 16 (S.D. 12.7) mEq/L. Twenty-three patients (44%) developed AKI; of those with hyperchloremia, 62% (23/37) developed AKI, while among those without hyperchloremia, 0% (0/15) developed AKI (difference 62%, 95% CI 42-82%, p < 0.001). Attributable risk of hyperchloremia leading to AKI was 62.2 (95% CI 46.5-77.8, p = 0.0015).

CONCLUSION

Hyperchloremia is common in the management of pediatric TBI and is associated with development of AKI. Risk appears to be associated with both the height of serum chloride and duration of hyperchloremia.

A Machine Learning Approach for the Prediction of Severe Acute Kidney Injury Following Traumatic Brain Injury

BACKGROUND

Acute kidney injury (AKI), a prevalent non-neurological complication following traumatic brain injury (TBI), is a major clinical issue with an unfavorable prognosis. This study aimed to develop and validate machine learning models to predict severe AKI (stage 3 or greater) incidence in patients with TBI.

METHODS

A retrospective cohort study was conducted by using two public databases: the Medical Information Mart for Intensive Care IV (MIMIC)-IV and the eICU Collaborative Research Database (eICU-CRD). Recursive feature elimination was used to select candidate predictors obtained within 24 h of intensive care unit admission. The area under the curve and decision curve analysis curves were used to determine the discriminatory ability. On the other hand, the calibration curve was employed to evaluate the calibrated performance of the newly developed machine learning models.

RESULTS

In the MIMIC-IV database, there were 808 patients diagnosed with moderate and severe TBI (msTBI) (msTBI is defined as Glasgow Coma Score < 12). Of these, 60 (7.43%) patients experienced severe AKI. External validation in the eICU-CRD indicated that the random forest (RF) model had the highest area under the curve of 0.819 (95% confidence interval 0.783-0.851). Furthermore, in the calibration curve, the RF model was well calibrated (P = 0.795).

CONCLUSIONS

In this study, the RF model demonstrated better discrimination in predicting severe AKI than other models. An online calculator could facilitate its application, potentially improving the early detection of severe AKI and subsequently improving the clinical outcomes among patients with msTBI.

Prognostic Factors for Stage 3 Acute Kidney Injury in Isolated Serious Traumatic Brain Injury

BACKGROUND

Stage 3 acute kidney injury (AKI) has been observed to develop following serious traumatic brain injury (TBI) and is associated with worse outcomes, though its incidence is not consistently established. This study aims to report the incidence of stage 3 AKI in serious isolated TBI in a large, national trauma database, and explore associated predictive factors.

METHODS

This was a retrospective cohort study using 2015-2018 data from the American College of Surgeons Trauma Quality Improvement Program (ACS-TQIP), a national database of trauma patients. Adult trauma patients admitted to the hospital with isolated serious TBI were included. Variables relating to demographics, comorbidities, vitals, hospital presentation, and course of stay were assessed. Imputed multivariable logistic regression assessed factors predictive of stage 3 AKI development.

RESULTS

A total of 342,675 patients with isolated serious TBI were included, 1,585 (0.5%) of whom developed stage 3 AKI. Variables associated with stage 3 AKI in multivariable analysis were older age, male sex, Black race, higher BMI, history of hypertension, diabetes, peripheral artery disease, chronic kidney disease, higher injury severity score, higher heart rate on arrival, lower oxygen saturation and motor Glasgow coma scale (GCS), admission to the intensive care unit (ICU) or operating room, development of catheter-associated urinary tract infections (CAUTI) or acute respiratory distress syndrome (ARDS), longer ICU stay and ventilation duration.

CONCLUSIONS

Stage 3 AKI occurred in 0.5% of serious TBI cases. Complications of ARDS and CAUTI are more likely to co-occur with stage 3 AKI in serious TBI patients.

Prediction of early acute kidney injury after trauma using prehospital systolic blood pressure and lactate levels: A prospective validation study

BACKGROUND

Acute kidney injury (AKI) after trauma is a major complication independently associated with a prolonged hospital stay and increased mortality. We previously reported that the prehospital systolic blood pressure (SBP) and early hospital arterial lactate level, along with specific cut-off values, show good performance in the early prediction of AKI using AUC-ROC [1]. The purpose of this study was to prospectively validate whether or not these parameters are predictive of newly occurring AKI after trauma.

METHODS

This was a prospective review of trauma patients who were admitted to a single trauma center from January to December 2019. Patients who were <16 years old, who had burns, and who had chronic kidney disease were excluded. AKI was defined according to the Risk, Injury, Failure, Loss of the kidney function, and End-stage kidney disease (RIFLE) classification based on serum creatinine alone. Patients with a low prehospital SBP (≤126 mmHg) and high lactate levels (≥2.5 mmol/L) were defined as the high-risk group, and other patients were defined as the low-risk group.

RESULTS

A total of 489 trauma patients were admitted to our center, of whom 403 were eligible for the study. The high-risk group consisted of 38 patients, and the low-risk group consisted of 365 patients. The incidence of severe AKI in Stage Injury and Failure was significantly higher in the high-risk group (5 patients, 13.2%) than in the low-risk group (7 patients, 1.9%), with an odds ratio of 7.75 and 95% confidence interval of 2.33-25.77.

CONCLUSIONS

These predictors showed good performance in the early prediction of severe AKI after trauma. Early prediction of the high-risk groups for severe AKI after trauma prompting early treatment may help improve the prognosis of trauma patients.

Association Between Serum Osmolality and Acute Kidney Injury in Critically Ill Patients: A Retrospective Cohort Study

Purposes: Acute kidney injury (AKI) is a common complication in critically ill patients and is usually associated with poor outcomes. Serum osmolality has been validated in predicting critically ill patient mortality. However, data about the association between serum osmolality and AKI is still lacking in ICU. Therefore, the purpose of the present study was to investigate the association between early serum osmolality and the development of AKI in critically ill patients.

Methods: The present study was a retrospective cohort analysis based on the medical information mart for intensive care III (MIMIC-III) database. 20,160 patients were involved in this study and divided into six subgroups according to causes for ICU admission. The primary outcome was the incidence of AKI after ICU admission. The association between early serum osmolality and AKI was explored using univariate and multivariate logistic regression analyses.

Results: The normal range of serum osmolality was 285–300 mmol/L. High serum osmolality was defined as serum osmolality >300 mmol/L and low serum osmolality was defined as serum osmolality <285 mmol/L. Multivariate logistic regression indicated that high serum osmolality was independently associated with increased development of AKI with OR = 1.198 (95% CL = 1.199–1.479, P < 0.001) and low serum osmolality was also independently associated with increased development of AKI with OR = 1.332 (95% CL = 1.199–1.479, P < 0.001), compared with normal serum osmolality, respectively.

Conclusions: In critically ill patients, early high serum osmolality and low serum osmolality were both independently associated with an increased risk of development of AKI.

Predictive Ability of Procalcitonin for Acute Kidney Injury: A Narrative Review Focusing on the Interference of Infection

Acute kidney injury (AKI) is a common yet complicated clinical entity with high morbidity and mortality. An essential strategy to improve AKI patients’ prognoses is finding optimal biomarkers to identify AKI in a timely manner. Procalcitonin (PCT), a well-recognized biomarker for diagnosing infection and guiding antibiotics therapy, has been proposed to predict AKI development and recovery in many clinical settings. The current review provides comprehensive and updated information from relevant studies to evaluate PCT’s AKI-predictive ability and the influence of infection on this predictive ability. PCT has demonstrated optimal predictive ability for AKI in various populations irrespective of infection. However, the predictive ability seems to be blunted by infection since infection and inflammation have a more potent influence than AKI on PCT elevation. We furthermore explain the complicated association between elevated PCT levels and AKI in infection and inflammation situations and recommend directions for further investigations to clarify the essential issue. In conclusion, although conflicting data exist, serum PCT level is a potential biomarker for predicting AKI in many clinical settings regardless of infection. Nevertheless, further studies are warranted to clarify the association between PCT, infection, and AKI and to confirm the utilization of PCT for AKI prediction.

A risk score based on procalcitonin for predicting acute kidney injury in COVID-19 patients

Background

Acute kidney injury (AKI) has been reported developing commonly in coronavirus disease 2019 (COVID‐19) patients and could increase the risk of poor outcomes in these patients. We design this study to explore the value of serum procalcitonin (PCT) on predicting AKI and construct risk score for predicting AKI in COVID‐19 patients.

Methods

Patients diagnosed with COVID‐19 and hospitalized in Renmin Hospital of Wuhan University between January 30 and February 24, 2020, were included. The least absolute shrinkage and selection operator (LASSO) regression was performed to identify the strongest predictors of AKI. Multivariate logistic regression analysis was conducted to find independent risk factors for AKI and construct risk score using odds ratio (OR) value of those risk factors. Receiver operating characteristics (ROC) curves were plotted, and area under the ROC curve (AUC) value was calculated to evaluate the predictive value of single PCT level and the constructed risk score.

Results

Among 389 included COVID‐19 patients, 28 (7.2%) patients developed AKI. LASSO regression showed hypertension, saturation of arterial oxygen (SaO₂), PCT, and blood urea nitrogen (BUN) were the strongest predictors for AKI. After multivariate logistic regression analysis, only SaO₂ (<0.001), PCT (p = 0.004), and BUN (p = 0.005) were independently associated with development of AKI in COVID‐19 patients. The AUC of single PCT and constructed risk score was 0. 881 and 0.928, respectively.

Conclusion

PCT level is correlated with AKI in COVID‐19 patients. The efficient risk score consisted of SaO₂, PCT, and BUN is readily accessible for physicians to evaluate the possibility of AKI in COVID‐19 patients.

Meta-analysis of procalcitonin as a predictor for acute kidney injury

BACKGROUND

Procalcitonin (PCT) was used for predicting the development of acute kidney injury (AKI) in several studies recently. We aimed to investigate the accuracy of PCT for predicting AKI in this study.

METHODS

Studies that assessed the predictive performance of PCT for the development of AKI in adult patients were searched from Medline, Embase, and the Cochrane Library from inception to June 2020. We calculated the pooled sensitivities and specificities and the area under the summary receiver-operating characteristic (SROC) curves. I2 was used to test the heterogeneity and the potential heterogeneity was investigated by meta-regression.

RESULTS

In total, 9 of 119 studies with 4852 patients were included, 1272 were diagnosed with AKI. In the overall analysis, the area under the SROC curve was 0.82 (95% CI, 0.79-0.85) and the pooled sensitivity and specificity were 0.76 (95% confidence interval [CI], 0.64-0.85) and 0.75 (95% CI, 0.61-0.86), respectively. In the subgroup analysis among septic patients, the pooled sensitivity and specificity were 0.59 (95% CI, 0.29-0.84) and 0.53 (95% CI, 0.31-0.74), and the area under the SROC was 0.57 (95% CI, 0.53-0.62).

CONCLUSION

PCT may be a potential predictor for the development of AKI.

Bidirectional Brain-Systemic Interactions and Outcomes After TBI

Traumatic brain injury (TBI) is a debilitating disorder associated with chronic progressive neurodegeneration and long-term neurological decline. Importantly, there is now substantial and increasing evidence that TBI can negatively impact systemic organs, including the pulmonary, gastrointestinal (GI), cardiovascular, renal, and immune system. Less well appreciated, until recently, is that such functional changes can affect both the response to subsequent insults or diseases, as well as contribute to chronic neurodegenerative processes and long-term neurological outcomes. In this review, we summarize evidence showing bidirectional interactions between the brain and systemic organs following TBI and critically assess potential underlying mechanisms.