Higher incidence of acute respiratory distress syndrome in cardiac surgical patients with elevated serum procalcitonin concentration: a prospective cohort study

Progress in Procalcitonin Detection Based on Immunoassay

Procalcitonin (PCT) serves as a crucial biomarker utilized in diverse clinical contexts, including sepsis diagnosis and emergency departments. Its applications extend to identifying pathogens, assessing infection severity, guiding drug administration, and implementing theranostic strategies. However, current clinical deployed methods cannot meet the needs for accurate or real-time quantitative monitoring of PCT. This review aims to introduce these emerging PCT immunoassay technologies, focusing on analyzing their advantages in improving detection performances, such as easy operation and high precision. The fundamental principles and characteristics of state-of-the-art methods are first introduced, including chemiluminescence, immunofluorescence, latex-enhanced turbidity, enzyme-linked immunosorbent, colloidal gold immunochromatography, and radioimmunoassay. Then, improved methods using new materials and new technologies are briefly described, for instance, the combination with responsive nanomaterials, Raman spectroscopy, and digital microfluidics. Finally, the detection performance parameters of these methods and the clinical importance of PCT detection are also discussed.

Prognosis prediction of procalcitonin within 24 h for acute diquat poisoning

BACKGROUND

To explore the predictive value of procalcitonin (PCT) within 24 h after poisoning for prognosis of acute diquat poisoning.

METHODS

This retrospective study included acute diquat poisoning patients in the Nanyang City Hospital between May 2017 and July 2021.

RESULTS

Among the 45 patients included, 27 survived. The maximum PCT value within 24 h after poisoning was significantly higher in the non-survival patients [9.65 (2.63, 22.77) vs. 0.15 (0.10, 0.50) µg/mL, P < 0.001] compared to the survival patients. The area under the ROC curve (AUC) indicated that the maximum PCT value within 24 h had a good predictive value (AUC = 0.905, 95% CI: 0.808-1.000) compared to ingested quantity (AUC = 0.879, 95% CI: 0.776-0.981), serum creatinine (AUC = 0.776, 95% CI: 0.640-0.912), or APACHE II score (AUC = 0.778, 95% CI: 0.631-0.925). The predictive value of maximum PCT value within 24 h was comparable with blood lactate (AUC = 0.904, 95%CI: 0.807-1.000).

CONCLUSIONS

The maximum PCT value within 24 h after poisoning might be a good predictor for the prognosis of patients with acute diquat poisoning.

Procalcitonin for the diagnosis of postoperative bacterial infection after adult cardiac surgery: a systematic review and meta-analysis

BACKGROUND AND AIMS

Patients undergoing cardiac surgery are subject to infectious complications that adversely affect outcomes. Rapid identification is essential for adequate treatment. Procalcitonin (PCT) is a noninvasive blood test that could serve this purpose, however its validity in the cardiac surgery population is still debated. We therefore performed a systematic review and meta-analysis to estimate the accuracy of PCT for the diagnosis of postoperative bacterial infection after cardiac surgery.

METHODS

We included studies on adult cardiac surgery patients, providing estimates of test accuracy. Search was performed on PubMed, EmBase and WebOfScience on April 12th, 2023 and rerun on September 15th, 2023, limited to the last 10 years. Study quality was assessed with the QUADAS-2 tool. The pooled measures of performance and diagnostic accuracy, and corresponding 95% Confidence Intervals (CI), were calculated using a bivariate regression model. Due to the variation in reported thresholds, we used a multiple-thresholds within a study random effects model for meta-analysis (diagmeta R-package).

RESULTS

Eleven studies were included in the systematic review, and 10 (2984 patients) in the meta-analysis. All studies were single-center with observational design, five of which with retrospective data collection. Quality assessment highlighted various issues, mainly concerning lack of prespecified thresholds for the index test in all studies. Results of bivariate model analysis using multiple thresholds within a study identified the optimal threshold at 3 ng/mL, with a mean sensitivity of 0.67 (0.47-0.82), mean specificity of 0.73 (95% CI 0.65-0.79), and AUC of 0.75 (IC95% 0.29-0.95). Given its importance for practice, we also evaluated PCT's predictive capability. We found that positive predictive value is at most close to 50%, also with a high prevalence (30%), and the negative predictive value was always > 90% when prevalence was < 20%.

CONCLUSIONS

These results suggest that PCT may be used to help rule out infection after cardiac surgery. The optimal threshold of 3 ng/mL identified in this work should be confirmed with large, well-designed randomized trials that evaluate the test's impact on health outcomes and on the use of antibiotic therapy. PROSPERO Registration number CRD42023415773. Registered 22 April 2023.

Development and validation of a predictive model for early diagnosis of neonatal acute respiratory distress syndrome based on the Montreux definition

Objective

Based on the Montreux definition, we aim to develop and validate a predictive model for the early diagnosis of neonatal acute respiratory distress syndrome (ARDS).

Methods

A retrospective analysis of clinical data on 198 neonates with respiratory distress from January 2018 to January 2022 was conducted. Neonates meeting Montreux definition were classified as ARDS group (n = 79), while the rest were non-ARDS group (n = 119). Univariate analysis identified indicators for neonatal ARDS, followed by logistic regression to construct a predictive model for early diagnosis. The ability of predictors and models to predict neonatal ARDS was evaluated using area under the curve (AUC), and model performance was estimated through bootstrap resampling.

Results

Maternal prenatal fever, abnormal fetal heart beat, meconium-stained amniotic fluid (MSAF), white blood cell (WBC), absolute neutrophil count (ANC), neutrophil percentage (NE%), platelet count (PLT), C-reactive protein (CRP), procalcitonin (PCT), creatine kinase (CK), activated partial thromboplastin time (APTT), serum calcium (Ca) and sodium (Na)exhibited significant differences between the ARDS group and the non-ARDS group (P < 0.05). MSAF (OR=5.037; 95% CI: 1.523-16.657; P < 0.05), ANC (OR = 1.324; 95% CI: 1.172-1.495; P < 0.05), PLT (OR = 0.979; 95% CI: 0.971-0.986; P < 0.05), Ca (OR = 0.020; 95% CI: 0.004-0.088; P < 0.05) emerged as independent risk factors for the development of ARDS. The respective AUC values for MSAF, ANC, PLT, Ca, and the combined prediction models were 0.606, 0.691, 0.808, 0.761 and 0.931. Internal validation showed that the C-index for the model was 0.931.

Conclusions

Early application of the model combining MSAF, ANC, PLT and Ca may have a good predictive effect on the early diagnosis of neonatal ARDS.

Risk of Acute Respiratory Distress Syndrome in Community-Acquired Pneumonia Patients: Use of an Artificial Neural Network Model

This study aimed to explore the independent risk factors for community-acquired pneumonia (CAP) complicated with acute respiratory distress syndrome (ARDS) and to predict and evaluate the risk of ARDS in CAP patients based on artificial neural network models (ANNs). We retrospectively analyzed eligible 989 CAP patients (632 men and 357 women) who met the criteria from the comprehensive intensive care unit (ICU) and the respiratory and critical care medicine department of Changzhou Second People's Hospital, Jiangsu Provincial People's Hospital, Nanjing Military Region General Hospital, and Wuxi Fifth People's Hospital between February 2018 and February 2021. The best predictors to model the ANNs were selected from 51 variables measured within 24 h after admission. By using this model, patients were divided into a training group (n = 701) and a testing group (n = 288 patients). Results showed that in 989 CAP patients, 22 important variables were identified as risk factors. The sensitivity, specificity, and accuracy of the ANNs model training group were 88.9%, 90.1%, and 89.7%, respectively. When ANNs were used in the test group, their sensitivity, specificity, and accuracy were 85.0%, 87.3%, and 86.5%, respectively; when ANNs were used to predict ARDS, the area under the receiver operating characteristic (ROC) curve was 0.943 (95% confidence interval (0.918-0.968)). The nine most important independent variables affecting the ANNs models were lactate dehydrogenase (100%), activated partial thromboplastin time (84.6%), procalcitonin (83.8%), age (77.9%), maximum respiratory rate (76.0%), neutrophil (75.9%), source of admission (68.9%), concentration of total serum kalium (61.3%), and concentration of total serum bilirubin (50.4%) (all important >50%). The ANNs model and the logistic regression models were significantly different in predicting and evaluating ARDS in CAP patients. Thus, the ANNs model has a good predictive value in predicting and evaluating ARDS in CAP patients, and its performance is better than that of the logistic regression model in predicting the incidence of ARDS patients.

Procalcitonin is associated with postnatal respiratory condition severity in preterm neonate

INTRODUCTION

Postnatal respiratory failure is common in preterm neonates and is difficult to distinguish from early-onset neonatal bacterial infection by clinical symptoms. Similar to C-reactive protein (CRP), procalcitonin (PCT) is used as a marker of bacterial infection. Recently, it has been reported that the serum PCT levels increase because of respiratory failure immediately after birth. However, there is insufficient information concerning the relationship between biological inflammation markers, such as PCT and CRP, and postnatal respiratory condition severity.

METHODS

Preterm neonates were classified according to the received respiratory management as follows: nonrespiratory support (NRS), respiratory support (RS), surfactant administration therapy (STA), and STA with nitric oxide inhalation therapy (NO). The median serum PCT and CRP levels at 12-36 h postnatally were compared among the four groups. Additionally, the median serum PCT and CRP levels in the STA group were compared by STA timing and STA number.

RESULTS

The PCT levels for the NRS, RS, STA, and NO groups were 1.04, 6.46, 12.93, and 86.79 μg/L, respectively; the CRP levels were 0.40, 0.80, 1.10, and 16.40 mg/L, respectively. The PCT levels were significantly lower among neonates receiving STA in the birth subgroup (4.82 μg/L) than among those receiving STA in the admission subgroup (14.71 μg/L). The PCT levels were significantly higher among the STA multiple-dose subgroup (24.87 μg/L) than among the STA single-dose subgroup (12.47 μg/L). No significant differences in the CRP levels were observed.

CONCLUSION

The serum PCT levels in preterm neonates were associated with postnatal respiratory condition severity.

Perioperative management after elective cardiac surgery: the predictive value of procalcitonin for infective and noninfective complications

Objective: Procalcitonin (PCT) has been associated with adverse outcomes after cardiac surgery. Nevertheless, there is no consensus on thresholds and timing of PCT measurement to predict adverse outcomes. Materials & methods: A total of 960 patients undergoing elective cardiac surgery were retrospectively evaluated. PCT levels were measured from the first to the seventh postoperative day (POD). The onset of complications was recorded. Results: Complications occurred in 421 (44%) patients. PCT on the third POD was associated with the occurrence of any kind of complications (odds ratio: 1.06; p: 0.037), and noninfectious complications (odds ratio: 1.05; p: 0.035), after adjusting. PCT above the median value at the third POD (>0.33 μg/l) predicted postoperative complications (incidence rate ratio: 1.13; p = 0.035). Conclusion: PCT seems to predict postoperative complications in cardiac surgery. The determination at the third POD yields the greatest sensitivity and specificity.

Critical Illness and Systemic Inflammation Are Key Risk Factors of Severe Acute Kidney Injury in Patients With COVID-19

INTRODUCTION

Acute kidney injury (AKI) is an important complication in COVID-19, but its precise etiology has not fully been elucidated. Insights into AKI mechanisms may be provided by analyzing the temporal associations of clinical parameters reflecting disease processes and AKI development.

METHODS

We performed an observational cohort study of 223 consecutive COVID-19 patients treated at 3 sites of a tertiary care referral center to describe the evolvement of severe AKI (Kidney Disease: Improving Global Outcomes stage 3) and identify conditions promoting its development. Descriptive statistics and explanatory multivariable Cox regression modeling with clinical parameters as time-varying covariates were used to identify risk factors of severe AKI.

RESULTS

Severe AKI developed in 70 of 223 patients (31%) with COVID-19, of which 95.7% required kidney replacement therapy. Patients with severe AKI were older, predominantly male, had more comorbidities, and displayed excess mortality. Severe AKI occurred exclusively in intensive care unit patients, and 97.3% of the patients developing severe AKI had respiratory failure. Mechanical ventilation, vasopressor therapy, and inflammatory markers (serum procalcitonin levels and leucocyte count) were independent time-varying risk factors of severe AKI. Increasing inflammatory markers displayed a close temporal association with the development of severe AKI. Sensitivity analysis on risk factors of AKI stage 2 and 3 combined confirmed these findings.

CONCLUSION

Severe AKI in COVID-19 was tightly coupled with critical illness and systemic inflammation and was not observed in milder disease courses. These findings suggest that traditional systemic AKI mechanisms rather than kidney-specific processes contribute to severe AKI in COVID-19.