Dataset Information

Independent Predictive Ability of Procalcitonin of Acute Kidney Injury among Critically Ill Patients.

ABSTRACT: It is unclear whether serum procalcitonin (PCT) levels rise in patients with acute kidney injury (AKI), and it is also unclear whether the elevation of PCT levels in this setting is independent of the existence of infection and impaired renal clearance. We conducted a retrospective study in a regional teaching hospital in Taiwan to evaluate the AKI-predictive ability of serum PCT among critically ill patients. We enrolled 330 patients (mean age, 70.5 ± 16.4 years; 57.0% men) who were admitted to the intensive care unit (ICU) from 1 July 2016, to 31 December 2016, and who had serum PCT measurement performed within 24 h after ICU admission. We used the generalized additive model and generalized linear model to evaluate the association of serum PCT levels and renal function variables. In addition, we used the multivariate logistic regression method to demonstrate serum PCT level as an independent predictor of AKI in both the non-infected patients (odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.12-1.71, p = 0.003) and the infected patients (OR = 1.23, 95% CI = 1.03-1.46, p = 0.020). In conclusion, serum PCT level at ICU admission is an independent predictor of developing AKI irrespective of infection among critically ill patients.

SUBMITTER: Huang YT

PROVIDER: S-EPMC7355446 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Independent Predictive Ability of Procalcitonin of Acute Kidney Injury among Critically Ill Patients.

Huang Ya-Ting YT Lai Min-Yu MY Kan Wei-Chih WC Shiao Chih-Chung CC

Journal of clinical medicine 20200621 6

It is unclear whether serum procalcitonin (PCT) levels rise in patients with acute kidney injury (AKI), and it is also unclear whether the elevation of PCT levels in this setting is independent of the existence of infection and impaired renal clearance. We conducted a retrospective study in a regional teaching hospital in Taiwan to evaluate the AKI-predictive ability of serum PCT among critically ill patients. We enrolled 330 patients (mean age, 70.5 ± 16.4 years; 57.0% men) who were admitted to ...[more]

PMID: 32575833

Similar Datasets

Project description:BackgroundThere has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived from cardiothoracic surgery. Therefore, we aimed to develop an AKI prediction score for major non-cardiothoracic surgery patients who were admitted to the intensive care unit (ICU).MethodsThe data of critically-ill patients from non-cardiothoracic operations in the Thai Surgical Intensive Care Unit (THAI-SICU) study were used to develop an AKI prediction score. Independent prognostic factors from regression analysis were included as predictors in the model. The outcome of interest was AKI within 7 days after the ICU admission. The AKI diagnosis was made according to the Kidney Disease Improving Global Outcomes (KDIGO)-2012 serum creatinine criteria. Diagnostic function of the model was determined by area under the Receiver Operating Curve (AuROC). Risk scores were categorized into four risk probability levels: low (0-2.5), moderate (3.0-8.5), high (9.0-11.5), and very high (12.0-16.5) risk. Risk of AKI was presented as likelihood ratios of positive (LH+).ResultsA total of 3474 critically-ill surgical patients were included in the model; 333 (9.6%) developed AKI. Using multivariable logistic regression analysis, older age, high Sequential Organ Failure Assessment (SOFA) non-renal score, emergency surgery, large volume of perioperative blood loss, less urine output, and sepsis were identified as independent predictors for AKI. Then AKI prediction score was created from these predictors. The summation of the score was 16.5 and had a discriminative ability for predicting AKI at AuROC = 0.839 (95% CI 0.825-0.852). LH+ for AKI were: low risk = 0.117 (0.063-0.200); moderate risk = 0.927 (0.745-1.148); high risk = 5.190 (3.881-6.910); and very high risk = 9.892 (6.230-15.695), respectively.ConclusionsThe function of AKI prediction score to predict AKI among critically ill patients who underwent non-cardiothoracic surgery was good. It can aid in early recognition of critically-ill surgical patients who are at risk from ICU admission. The scores could guide decision making for aggressive strategies to prevent AKI during the perioperative period or at ICU admission.Trial registrationTCTR20190408004, registered on April 4, 2019.

Dataset Information

Independent Predictive Ability of Procalcitonin of Acute Kidney Injury among Critically Ill Patients.

Publications

Independent Predictive Ability of Procalcitonin of Acute Kidney Injury among Critically Ill Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets