The diagnostic value of serum C-reactive protein, procalcitonin, interleukin-6 and lactate dehydrogenase in patients with severe acute pancreatitis

Diagnostic value of CRP for predicting the severity of acute pancreatitis: a systematic review and meta-analysis

BACKGROUND

C-reactive protein (CRP) is a pentameric protein commonly used as a biomarker of inflammation or stress response which can be obtained during routine blood tests. Therefore, we conducted a systematic review and meta-analysis to explore its ability to predict the severity of acute pancreatitis (AP). This meta-analysis was registered in the PROSPERO system (registration number: CRD42022353769).

METHODS

41 studies with 6156 cases of acute pancreatitis, retrieved from PubMed, Cochrane Library, Springer, and Embase databases, were incorporated. We calculated the pooled estimates for predicting the severity of acute pancreatitis based on CRP levels. We also calculated the combined negative likelihood ratio (NLR), combined positive likelihood ratio (PLR) and combined diagnostic odds ratio (DOR) using a bivariate mixed model. Sensitivity analysis was used to examine the robustness of the results. Factors associated with heterogeneity were identified by meta-regression analysis. A summary operating characteristic (SROC) curve was generated to assess the diagnostic value of CRP in predicting severe acute pancreatitis. Fagan's test was used to calculate likelihood ratios and post-test probabilities, and publication bias was gauged by asymmetry tests.

RESULTS

SROC analysis yielded an AUC of 0.85 (95%CI: 0.81-0.88) with a sensitivity of 0.76 (95%CI: 0.69-0.83) and specificity of 0.79 (95%CI: 0.74-0.83). The combined NLR, PLR and DOR were 0.30 (0.23-0.40), 3.66 (2.94-4.55) and 12.19 (8.05-18.44) respectively. Sensitivity analysis demonstrated the stability of our results after omitting any study. Finally, meta-regression analysis indicated that the description of the reference test, prospective design, blinding method and spectrum of the disease could account for heterogeneity in this meta-analysis.

CONCLUSION

CRP has significant value as a biomarker for assessing AP severity. Besides, other parameters such as patient history, physical signs, and imaging should be considered to determine disease severity.

Procalcitonin in inflammatory bowel disease: A diagnostic or prognostic marker

Serological biomarkers have been rapidly progressing as non-invasive tests for the early detection of inflammatory bowel disease (IBD). Procalcitonin (PCT) is a novel acute-phase reactant protein that is elevated in the inflammatory process, especially in bacterial infections. This study aimed to review the diagnostic value of PCT in IBD activity. However, there were controversies about the role of PCT in the detecting of IBD disease activity. Studies showed varied diagnostic cut-points (ranging from 0.13 to 1.0 ng/dl) and sensitivity up to 93 %. Although the clear role of PCT as a valuable diagnostic marker was not identified in determining disease activity, PCT measurement in addition to other inflammatory markers can improve the diagnostic value of these markers. Moreover, further studies are required to confirm PCT's value in distinguishing IBD disease activity.

Changes of serum NSE, lactate and CRP in patients with postoperative infection after acute craniocerebral injury and their predictive value for prognosis

To investigate the changes of serum neuron-specific enolase (NSE), lactate and C-reactive protein (CRP) in patients with postoperative infection after acute craniocerebral injury and their predictive value for prognosis. 71 patients with postoperative infection after acute craniocerebral injury were selected as infection group, and 56 patients without postoperative infection were selected as non-infection group. NSE, CRP and blood lactic acid levels were detected in all patients. The relationship between each index and thecondition and prognosis of patients was analyzed. The levels of serum NSE, lactic acid and CRP in infected group were higher than those in non-infection group (P<0.05). The levels of serum NSE, lactic acid and CRP in severe group were higher than those in mild group (P<0.05). Serum levels of NSE, lactic acid and CRP were positively correlated with the severity of infection (P<0.05), the area under the curve (AUC) of the receiver operating characteristic curve (ROC) was greater than that of the NSE level (P<0.05). The levels of serum NSE, lactate and CRP in the good prognosis group were lower than those in the poor prognosis group (P<0.05). The area under the curve (AUC) of receiver operating characteristic curve (ROC) of lactate level in predicting the prognosis of patients with infection was higher than that of NSE and CRP (P<0.05). Serum NSE, lactic acid and CRP have predictive value in patients with acute craniocerebral injury.

Mediation effect of stroke recurrence in the association between post-stroke lactate dehydrogenase and functional disability

Background

We aimed to use lactate dehydrogenase (LDH) as a marker of inflammation burden and quantify post-stroke inflammation's direct and indirect effect on functional disability.

Methods

We analyzed 5,129 patients with acute ischemic stroke (AIS) admitted to Shenyang First People's Hospital. Stroke recurrence and functional outcome measured by the modified Rankin Scale (mRS) were assessed at 90 days. Functional disability was defined as mRS score > 2. Receiver operating characteristic curve and restricted cubic spline (RCS) analysis were conducted to illustrate the associations between LDH levels and 90-day functional outcomes in patients with AIS. Mediation analyses were performed to examine the potential causal chain in which stroke recurrence may mediate the relationship between LDH and functional outcome. Positive correlation between LDH and hs-CRP was found and mediation effects of stroke recurrence in the association between LDH or hs-CRP and functional disability were both less than 20%. Sensitivity analyses in different subgroups showed comparable results.

Results

Among 5,129 included AIS patients, the median (IQR) level of LDH was 186 (161-204.4) U/L. Functional disability was seen in 1200 (23.4%) patients and recurrence was observed in 371(7.2%) patients at 90-day follow-up. Each standard deviation increase in the concentration of LDH was linked to an increased risk of functional disability (adjusted odds ratio[aOR], 1.07; 95%CI,1.04-1.09) and stroke recurrence (aOR,1.02; 95%CI, 1.01-1.04) within 90 days. The highest quartile of LDH (>204.2 U/L) had an elevated risk of suffering functional disability (aOR, 1.21; 95%CI, 1.00-1.47) and recurrence (aOR, 1.21; 95%CI,1.00-1.47) compared with the lowest quartile of LDH (<161 U/L). Stroke recurrence during follow-up explained 12.90% (95%CI, 6.22-21.16%) of the relationship between LDH and functional disability. Positive correlation between LDH and hs-CRP was found and mediation effects of recurrence in the association between LDH or hs-CRP and functional disability were both less than 20%. Sensitivity analyses in different subgroups showed comparable results.

Conclusion

The relationship between LDH and functional disability at 90 days among AIS patients is partially mediated by stroke recurrence, accounting for less than 20%. LDH deserves equal attention as hs-CRP in predicting recurrence and functional outcome. In addition to traditional secondary prevention measures, innovative anti-inflammatory strategies warrant further investigation.

Role of Interleukin 6 in Acute Pancreatitis: A Possible Marker for Disease Prognosis

Acute pancreatitis (AP) is a significant cause of morbidity, even in children, and is frequently associated with systemic manifestations. There are many cytokines involved in the inflammatory response characteristic of this disease. Interleukin 6 (IL-6) is one of the most important cytokines involved in AP, beginning from cellular injury and continuing to the systemic inflammatory response and distant organ involvement. IL-6 is a multifunctional cytokine that regulates acute-phase response and inflammation. It is produced by various cells and exerts its biological role on many cells through its high-affinity complex receptor. IL-6 has been investigated as a predicting maker for severe forms of AP. Many studies have validated the use of IL-6 serum levels in the first 48 h as a reliable marker for severe evolution and multisystemic involvement. Still, it has not been used in daily practice until now. This review discusses the main binding mechanisms by which IL-6 triggers cellular response and the AP pathogenetic mechanisms in which IL-6 is involved. We then emphasize the promising role of IL-6 as a prognostic marker, which could be added as a routine marker at admission in children with AP.

Construction and validation of a nomogram for predicting survival in elderly patients with severe acute pancreatitis: a retrospective study from a tertiary center

PURPOSE

There is a lack of adequate models specifically designed for elderly patients with severe acute pancreatitis (SAP) to predict the risk of death. This study aimed to develop a nomogram for predicting the overall survival of SAP in elderly patients.

METHODS

Elderly patients diagnosed with SAP between January 1, 2017 and December 31, 2022 were included in the study. Risk factors were identified through least absolute shrinkage and selection operator regression analysis. Subsequently, a novel nomogram model was developed using multivariable logistic regression analysis. The predictive performance of the nomogram was evaluated using metrics such as the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA).

RESULTS

A total of 326 patients were included in the analysis, with 260 in the survival group and 66 in the deceased group. Multivariate logistic regression indicated that age, respiratory rate, arterial pH, total bilirubin, and calcium were independent prognostic factors for the survival of SAP patients. The nomogram demonstrated a performance comparable to sequential organ failure assessment (P = 0.065). Additionally, the calibration curve showed satisfactory predictive accuracy, and the DCA highlighted the clinical application value of the nomogram.

CONCLUSION

We have identified key demographic and laboratory parameters that are associated with the survival of elderly patients with SAP. These parameters have been utilized to create a precise and user-friendly nomogram, which could be an effective and valuable clinical tool for clinicians.

Predictive Value of Troponin I, Creatinine Kinase Isoenzyme and the New Japanese Severity Score in Severe Acute Pancreatitis

Purpose

To evaluate troponin I, creatine kinase isoenzyme, and the new Japanese Severity Score(JSS) for predicting Severe Acute Pancreatitis-Associated myocardial Injury(SACI).

Patients and Methods

This retrospective study included 136 patients with Severe Acute Pancreatitis, hospitalized in grade-III hospital from June 1, 2015, to October 31, 2022; selected using convenience sampling method and divided into SACI occurrence (n =34) and SACI non-occurrence (n =102) groups. New JSS evaluated predictive value of each SACI index. Binary logistic regression model compared risk factors and constructed a prediction model. Area under receiver operating characteristic curve (AUC) and Hosmer-Lemeshow goodness of fit test evaluated model's prediction efficiency and calibration ability.

Results

The incidence of SACI was 25%. Univariate analysis found that troponin I and creatine kinase isoenzyme were significantly different (P < 0.05) and independent risk factors for SACI. The new JSS, troponin I, and creatine kinase isoenzyme were included in the prediction model. The prediction model had a good calibration ability, and its predicted value and the actual observed value were not significantly different (Hosmer-Lemeshow χ2 = 5.408, P = 0.368). AUC of the model was 0.803 (95% CI: 0.689-0.918), and the optimal threshold of the prediction model was 0.318 with the maximum Youden index (0.488). The AUC for internal validation was 0.788 (95% CI: 0.657-0.876), and external validation was 0.761 (95% CI: 0.622-0.832).

Conclusion

Troponin I and creatine kinase isoenzymes combined with the new JSS have a high predictive value for SACI, improving the early prediction and treatment of at-risk patients.

Development and Validation of a Nomogram for Predicting the Severity of the First Episode of Hyperlipidemic Acute Pancreatitis

Purpose

Early detection of hyperlipidemic acute pancreatitis (HLAP) with exacerbation tendency is crucial for clinical decision-making and improving prognosis. The aim of this study was to establish a reliable model for the early prediction of HLAP severity.

Patients and Methods

A total of 225 patients with first-episode HLAP who were admitted to Fujian Medical University Union Hospital from June 2012 to June 2023 were included. Patients were divided into mild acute pancreatitis (MAP) or moderate-severe acute pancreatitis and severe acute pancreatitis (MSAP+SAP) groups. Independent predictors for progression to MSAP or SAP were identified through univariate analysis and least absolute shrinkage and selection operator regression. A nomogram was established through multivariate logistic regression analysis to predict this progression. The calibration, receiver operating characteristic(ROC), and clinical decision curves were employed to evaluate the model's consistency, differentiation, and clinical applicability. Clinical data of 93 patients with first-episode HLAP who were admitted to the First Affiliated Hospital of Fujian Medical University from October 2015 to October 2022 were collected for external validation.

Results

White blood cell count, lactate dehydrogenase, albumin, serum creatinine, serum calcium, D-Dimer were identified as independent predictors for progression to MSAP or SAP in patients with HLAP and used to establish a predictive nomogram. The internally verified Harrell consistency index (C-index) was 0.908 (95% CI 0.867-0.948) and the externally verified C-index was 0.950 (95% CI 0.910-0.990). The calibration, ROC, and clinical decision curves showed this nomogram's good predictive ability.

Conclusion

We have established a nomogram that can help identify HLAP patients who are likely to develop MSAP or SAP at an early stage, with high discrimination and accuracy.

Prediction of severe hypertriglyceridemia-associated acute pancreatitis using a nomogram based on CT findings and blood biomarkers

Hypertriglyceridemia is a common cause of acute pancreatitis (AP). Fatty liver, a manifestation of metabolic syndrome, is related to the severity of AP. The present study aimed to construct an accurate predictive model for severe AP (SAP) by combining the fatty liver infiltration on a computerized tomography (CT) scan with a series of blood biomarkers in patients with hypertriglyceridemia-associated AP (HTG-AP). A total of 213 patients diagnosed with HTG-AP were included in the present retrospective study. Clinical information and imageological findings were retrospectively analyzed. The model was constructed from independent risk factors using univariate analysis, the least absolute shrinkage and selection operator method. Subsequently, the data from the training group of 111 patients with HTG-AP was analyzed using logistic regression analysis. The efficacy of the model was verified using an external validation group of 102 patients through the receiver operating characteristic curve (ROC). Independent predictors, including serum calcium, C-reactive protein, lactate dehydrogenase and liver-to-spleen CT attenuation ratio (L/S ratio), were incorporated into the nomogram model for SAP in HTG-AP. The model achieved a sensitivity of 91.3% and a specificity of 88.6% in the training group. Compared with the Ranson model, the established nomogram model exhibited a better discriminative ability in the training group [area under the curve (AUC): 0.957] and external validation group (AUC: 0.930), as well as better calibration and clinical benefits. The present study demonstrates that the constructed nomogram based on CT findings and blood biomarkers is useful for the accurate prediction of SAP in HTG-AP.

Disease-specific plasma protein profiles in patients with fever after traveling to tropical areas

Fever is common among individuals seeking healthcare after traveling to tropical regions. Despite the association with potentially severe disease, the etiology is often not determined. Plasma protein patterns can be informative to understand the host response to infection and can potentially indicate the pathogen causing the disease. In this study, we measured 49 proteins in the plasma of 124 patients with fever after travel to tropical or subtropical regions. The patients had confirmed diagnoses of either malaria, dengue fever, influenza, bacterial respiratory tract infection, or bacterial gastroenteritis, representing the most common etiologies. We used multivariate and machine learning methods to identify combinations of proteins that contributed to distinguishing infected patients from healthy controls, and each other. Malaria displayed the most unique protein signature, indicating a strong immunoregulatory response with high levels of IL10, sTNFRI and II, and sCD25 but low levels of sCD40L. In contrast, bacterial gastroenteritis had high levels of sCD40L, APRIL, and IFN-γ, while dengue was the only infection with elevated IFN-α2. These results suggest that characterization of the inflammatory profile of individuals with fever can help to identify disease-specific host responses, which in turn can be used to guide future research on diagnostic strategies and therapeutic interventions.

Establishment and validation of early prediction model for hypertriglyceridemic severe acute pancreatitis

BACKGROUND

The prevalence of hypertriglyceridaemia-induced acute pancreatitis (HTG-AP) is increasing due to improvements in living standards and dietary changes. However, currently, there is no clinical multifactor scoring system specific to HTG-AP. This study aimed to screen the predictors of HTG-SAP and combine several indicators to establish and validate a visual model for the early prediction of HTG-SAP.

METHODS

The clinical data of 266 patients with HTG-SAP were analysed. Patients were classified into severe (N = 42) and non-severe (N = 224) groups according to the Atlanta classification criteria. Several statistical analyses, including one-way analysis, least absolute shrinkage with selection operator (LASSO) regression model, and binary logistic regression analysis, were used to evaluate the data.

RESULTS

The univariate analysis showed that several factors showed no statistically significant differences, including the number of episodes of pancreatitis, abdominal pain score, and several blood diagnostic markers, such as lactate dehydrogenase (LDH), serum calcium (Ca2+), C-reactive protein (CRP), and the incidence of pleural effusion, between the two groups (P < 0.000). LASSO regression analysis identified six candidate predictors: CRP, LDH, Ca2+, procalcitonin (PCT), ascites, and Balthazar computed tomography grade. Binary logistic regression multivariate analysis showed that CRP, LDH, Ca2+, and ascites were independent predictors of HTG-SAP, and the area under the curve (AUC) values were 0.886, 0.893, 0.872, and 0.850, respectively. The AUC of the newly established HTG-SAP model was 0.960 (95% confidence interval: 0.936-0.983), which was higher than that of the bedside index for severity in acute pancreatitis (BISAP) score, modified CT severity index, Ranson score, and Japanese severity score (JSS) CT grade (AUC: 0.794, 0.796, 0.894 and 0.764, respectively). The differences were significant (P < 0.01), except for the JSS prognostic indicators (P = 0.130). The Hosmer-Lemeshow test showed that the predictive results of the model were highly consistent with the actual situation (P > 0.05). The decision curve analysis plot suggested that clinical intervention can benefit patients when the model predicts that they are at risk for developing HTG-SAP.

CONCLUSIONS

CRP, LDH, Ca2+, and ascites are independent predictors of HTG-SAP. The prediction model constructed based on these indicators has a high accuracy, sensitivity, consistency, and practicability in predicting HTG-SAP.

Detection of respiratory pathogenic bacterial nucleic acid detection by Loop-mediated Isothermal Amplification in patients with bacterial pulmonary infections

Objective

Nucleic acid testing can accurately and rapidly identify the presence of pathogenic bacteria. In this study, we analyzed respiratory pathogenic bacteria nucleic acids by LAMP (Loop-mediated isothermal amplification) to clarify the clinical application in patients with bacterial pulmonary infections.

Methods

Clinical data and specimens were collected from 99 patients with bacterial pulmonary infections from June 2021 to April 2023. We compared the differences between nucleic acid detection of LAMP and sputum culture. The correlation between inflammation manifestations of pulmonary imaging and the nucleic acid detection of LAMP was compared and analyzed. And the relationship between LAMP and blood inflammatory markers were analyzed.

Results

The positive rate of LAMP using sputum specimens was significantly higher than that of sputum culture (P < 0.05). Pathogenic bacteria in sputum samples are more likely to be detected by LAMP in patients with inflammatory on lung imaging examination. The coincidence rate of elevated PCT and CRP expression with positive LAMP results were 83.87 % and 88.71 %, respectively. Moreover, PCT, CRP and WBC were significantly higher in LAMP positive group than those in negative group (P < 0.05).

Conclusion

Nucleic acid testing of sputum specimens for pathogenic bacteria by LAMP on the basis of imaging examination can provide a rapid and accurate experimental basis for clinical diagnosis of bacterial pulmonary infections.

A Clinic-Radiomics Model for Predicting the Incidence of Persistent Organ Failure in Patients with Acute Necrotizing Pancreatitis

Background

Persistent organ failure (POF) is the leading cause of death in patients with acute necrotizing pancreatitis (ANP). Although several risk factors have been identified, there remains a lack of efficient instruments to accurately predict the incidence of POF in ANP.

Methods

Retrospectively, the clinical and imaging data of 178 patients with ANP were collected from our database, and the patients were divided into training (n = 125) and validation (n = 53) cohorts. Through computed tomography image acquisition, the volume of interest segmentation, and feature extraction and selection, a pure radiomics model in terms of POF prediction was established. Then, a clinic-radiomics model integrating the pure radiomics model and clinical risk factors was constructed. Both primary and secondary endpoints were compared between the high- and low-risk groups stratified by the clinic-radiomics model.

Results

According to the 547 selected radiomics features, four models were derived from features. A clinic-radiomics model in the training and validation sets showed better predictive performance than pure radiomics and clinical models. The clinic-radiomics model was evaluated by the ratios of intervention and mechanical ventilation, intensive care unit (ICU) stays, and hospital stays. The results showed that the high-risk group had significantly higher intervention rates, ICU stays, and hospital stays than the low-risk group, with the confidence interval of 90% (p < 0.1 for all).

Conclusions

This clinic-radiomics model is a useful instrument for clinicians to evaluate the incidence of POF, facilitating patients' and their families' understanding of the ANP prognosis.

Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis

Background

Severe acute pancreatitis (SAP) can progress to lung and kidney dysfunction, and blood clotting within 48 hours of its onset, and is associated with a high mortality rate. The aim of this study was to establish a reliable diagnostic prediction model for the early stage of severe pancreatitis.

Methods

The clinical data of patients diagnosed with acute pancreatitis from October 2017 to June 2022 at the Shangluo Central Hospital were collected. The risk factors were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. A novel nomogram model was then established by multivariable logistic regression analysis.

Results

The data of 436 patients with acute pancreatitis, 45 (10.3%) patients had progressed to SAP. Through univariate and LASSO regression analyses, the neutrophils (P <0.001), albumin (P < 0.001), blood glucose (P < 0.001), serum calcium (P < 0.001), serum creatinine (P < 0.001), blood urea nitrogen (P < 0.001) and procalcitonin (P = 0.005) were identified as independent predictive factors for SAP. The nomogram built on the basis of these factors predicted SAP with sensitivity of 0.733, specificity of 0.9, positive predictive value of 0.458 and negative predictive value of 0.967. Furthermore, the concordance index of the nomogram reached 0.889 (95% CI, 0.837-0.941), and the area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis was significantly higher than that of the APACHEII and ABISAP scoring systems. The established model was validated by plotting the clinical decision curve analysis (DCA) and clinical impact curve (CIC).

Conclusion

We established a nomogram to predict the progression of early acute pancreatitis to SAP with high discrimination and accuracy.

Optimal timing of free total rhubarb anthraquinones on immune regulation in rats with severe acute pancreatitis

ETHNOPHARMACOLOGICAL RELEVANCE

Rhubarb is the peeled and dried root of Rheum palmatum L., Rheum tanguticum Maxim. ex Balf. or Rheum officinale Baill. Free total rhubarb anthraquinones (FTRAs) isolated and extracted from rhubarb display the beneficial effects of anti-inflammation and immunological modulation. The timing of immune regulation is a major problem in the immunotherapy for severe acute pancreatitis (SAP). several studies reported that FTRAs could reduce systemic inflammatory responses by inhibiting early immune overactivity in the gut in rats with SAP. But, the optimal timing of rhubarb and FTRAs administration is not clear in clinical practice. Therefore, the time window for the best efficacy of rhubarb and FTRAs in the treatment of SAP patients should be further elucidated.

AIM OF THE STUDY

The main purpose of the present study was to evaluate the efficacy and optimal timing of immune modulation with FTRAs in the treatment of SAP in rats.

MATERIALS AND METHODS

FTRAs (22.5, 45 and 90 mg/kg), Rhubarb (RHU) (900 mg/kg, positive control) or normal saline (vehicle control) were initiated at 0 (immediately), 48 and 72 h every 12 h for three times in total. The therapeutic effects of FTRAs and RHU on pancreas and intestinal tissues injury, secondary infection with pseudomonas aeruginosa (PA), amylase, lipase, D-lactic acid (DLA), endotoxin (ET), proinflammatory and anti-inflammatory cytokines, macrophages, dendritic cells and regulatory T cells (Tregs) in the blood, small intestine and/or mesenteric lymph node (MLN) were determined in rats with SAP after treatment.

RESULTS

The results showed that administration of FTRAs at 0 h was superior to 48 h and 72 h, which significantly protected the injury of pancreas and intestinal tissues, reduced the mortality induced by secondary infection with PA, decreased the levels of amylase, lipase, DLA, ET, tumor necrosis factor α (TNF-α), interleukin 1β (IL-1β), IL-6, IL-8, IL-18 and Tregs, and increased the levels of IL-4, sTNF-αR, macrophages and dendritic cells, secretary immunoglobulin A (SIgA) in the blood and/or small intestinal tissues in rats with SAP.

CONCLUSIONS

In conclusion, our studies indicate that the treatment window of FTRAs for SAP is within 48 h of development, administration of FTRAs at the early stage (0 h, immune overreaction period) was the optimal time and superior to that of 48 h and 72 h for its therapeutic efficacy. The earlier the administration of FTRAs, the better the therapeutic efficacy. Therefore, our data may provide a scientific rationale for the clinical application and optimal timing of FTRAs in the treatment of SAP.

Interleukin-6 is better than C-reactive protein for the prediction of infected pancreatic necrosis and mortality in patients with acute pancreatitis

INTRODUCTION

This study aimed to identify whether interleukin-6 (IL-6) is better than C-reactive protein (CRP) for the prediction of severe acute pancreatitis (SAP), infected pancreatic necrosis (IPN), and mortality.

METHODS

Sixty-seven patients with acute pancreatitis (AP) who were hospitalized within 48 h of onset and received serum CRP and IL-6 tests from September 2018 to September 2019 were included. Spearman's correlation was performed to assess their associations with severity. The areas under the curve (AUCs) for the prediction of SAP, organ failure, pancreatic necrosis, IPN, and mortality were estimated using receiver operating characteristic curves.

RESULT

Serum CRP and IL-6 levels were significantly positively correlated with the severity of AP (p < 0.05). The AUC for the prediction of SAP based on the CRP level was 0.78 (95% CI, 0.66-0.89) and that based on the IL-6 level was 0.69 (95% CI, 0.56-0.82). For the prediction of organ failure and pancreatic necrosis, CRP was more accurate than IL-6 (AUC 0.80 vs. 0.72 and 0.75 vs. 0.68, respectively). However, CRP was less accurate than IL-6 for predicting mortality and IPN (AUC 0.70 vs. 0.75 and 0.65 vs. 0.81, respectively). Systemic inflammatory response syndrome plus CRP was more accurate than systemic inflammatory response syndrome plus IL-6 (AUC 0.79 vs. 0.72) for the prediction of SAP.

CONCLUSIONS

IL-6 was more accurate than CRP for predicting mortality and IPN in patients with AP.

Elevated lactate dehydrogenase predicts poor prognosis of acute ischemic stroke

Background

Lactate dehydrogenase (LDH) is associated with the prognosis of many diseases, but the relationship between LDH and the poor prognosis (recurrence and death) of acute ischemic stroke (AIS) has not been fully clarified. This study aimed to investigate the association between admission LDH level and poor prognosis in patients with AIS.

Methods

This retrospective study enrolled AIS patients treated in Taizhou Hospital of Zhejiang Province from July 2019 to December 2019. Poor prognosis included AIS recurrence and all-cause death at 3, 6, and 18 months. The correction between LDH and poor prognosis or all-cause death was assessed. Lasso Cox expression and multivariate Cox expression analyses were used to evaluate the association of LDH with the risk of poor prognosis and all-cause death, respectively. A nomogram was constructed to evaluate the predictive Values of LDH for the poor prognosis and all-cause death of AIS.

Results

732 patients were included in the study. Multivariate analysis shows that admission LDH levels were significantly correlated with poor prognosis [odds ratio (OR),1.003; 95% confidence interval (95% CI), 1.001–1.005; P = 0.001] and all-cause death (OR, 1.005; 95% CI, 1.000–1.009; P = 0.031). The correlation analysis showed that admission LDH level was positively correlated with National Institutes of Health Stroke Scale (NIHSS) score and modified Rankin Scale (mRS) score. Time-dependent receiver operating characteristic (td-ROC) curves analysis showed that the AUC values of admission LDH level for predicting prognosis of AIS patients in 3-month, 6-month, 12-month and 18-month were 0.706 (95% CI, 0.604–0.810), 0.653 (95% CI, 0.583–0.723), 0.616 (95% CI, 0.556–60676) and 0.610 (95% CI, 0.552–0.680), respectively. And td-ROC also showed that the AUC values of admission LDH level for predicting all-cause death of AIS patients in 3-month, 6-month,12-month and 18-month were 0.861 (95% CI, 0.764–0.958), 0.824 (95% CI, 0.753–0.890), 0.726 (95% CI, 0.633–0.819) and 0.715 (95% CI, 0.622–0.807), respectively. The nomograms were constructed to create the predictive models of the poor prognosis and all-cause death of AIS.

Conclusion

Higher LDH levels are independently associated with poor prognosis and all-cause death of AIS.

Impact of lactate dehydrogenase on prognosis of patients undergoing cardiac surgery

Background

Lactate dehydrogenase (LDH) has been reported in multiple heart diseases. Herein, we explored the prognostic effects of preoperative LDH on adverse outcomes in cardiac surgery patients.

Methods

Retrospective data analysis was conducted from two large medical databases: Medical Information Mart for Intensive Care (MIMIC) III and MIMIC IV databases. The primary outcome was in-hospital mortality, whereas the secondary outcomes were 1-year mortality, continuous renal replacement therapy, prolonged ventilation, and prolonged length of intensive care unit and hospital stay.

Results

Patients with a primary endpoint had significantly higher levels of LDH (p < 0.001). Multivariate regression analysis presented that elevated LDH was independently correlated with increased risk of primary and secondary endpoints (all p < 0.001). Subgroup analyses showed that high LDH was consistently associated with primary endpoint. Moreover, LDH exhibited the highest area under the curve (0.768) for the prediction of primary endpoint compared to the other indicators, including neutrophil–lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet–lymphocyte ratio (PLR), lactate, and simplified acute physiology score (SAPS) II. The above results were further confirmed in the MIMIC IV dataset.

Conclusions

Elevated preoperative LDH may be a robust predictor of poor prognosis in cardiac surgery patients, and its predictive ability is superior to NLR, LMR, PLR, lactate, and SAPS II.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02848-7.

Prediction of the severity of acute pancreatitis using machine learning models

BACKGROUND

Acute pancreatitis (AP) is the most common pancreatic disease. Predicting the severity of AP is critical for making preventive decisions. However, the performance of existing scoring systems in predicting AP severity was not satisfactory. The purpose of this study was to develop predictive models for the severity of AP using machine learning (ML) algorithms and explore the important predictors that affected the prediction results.

METHODS

The data of 441 patients in the Department of Gastroenterology in our hospital were analyzed retrospectively. The demographic data, blood routine and blood biochemical indexes, and the CTSI score were collected to develop five different ML predictive models to predict the severity of AP. The performance of the models was evaluated by the area under the receiver operating characteristic curve (AUC). The important predictors were determined by ranking the feature importance of the predictive factors.

RESULTS

Compared to other ML models, the extreme gradient boosting model (XGBoost) showed better performance in predicting severe AP, with an AUC of 0.906, an accuracy of 0.902, a sensitivity of 0.700, a specificity of 0.961, and a F1socre of 0.764. Further analysis showed that the CTSI score, ALB, LDH, and NEUT were the important predictors of the severity of AP.

CONCLUSION

The results showed that the XGBoost algorithm can accurately predict the severity of AP, which can provide an assistance for the clinicians to identify severe AP at an early stage.

Dynamic Monitoring of Immunoinflammatory Response Identifies Immunoswitching Characteristics of Severe Acute Pancreatitis in Rats

Background

Immune dysfunction is the main characteristic of severe acute pancreatitis (SAP), and the timing of immune regulation has become a major challenge for SAP treatment. Previous reports about the time point at which the immune status of SAP changed from excessive inflammatory response to immunosuppression (hypo-inflammatory response) are conflicting.

Purposes

The aims of this study are to explore the immunological dynamic changes in SAP rats from the perspective of intestinal mucosal immune function, and to determine the immunoswitching point from excessive inflammatory response to immunosuppression.

Methods

Retrograde injection of sodium taurocholate into the pancreaticobiliary duct was applied to establish a SAP model in rats. The survival rate and the activities of serum amylase and pancreatic lipase in SAP rats were measured at different time points after model construction. The pathological changes in the pancreas and small intestines were analyzed, and the levels of intestinal pro- and anti-inflammatory cytokines and the numbers of intestinal macrophages, dendritic cells, Th1, Th2, and T regulatory cells were assessed. Meanwhile, the SAP rats were challenged with Pseudomonas aeruginosa (PA) strains to simulate a second hit, and the levels of intestinal inflammatory cytokines and the numbers of immune cells were analyzed to confirm the immunoswitching point.

Results

The time periods of 12–24 h and 48–72 h were the two death peaks in SAP rats. The pancreas of SAP rats showed self-limiting pathological changes, and the switching period of intestinal cytokines, and innate and adaptive immunity indexes occurred at 24–48 h. It was further confirmed that 48 h after SAP model construction was the immunoswitching point from excessive inflammatory response to immunosuppression.

Conclusion

The SAP rats showed characteristics of intestinal mucosal immune dysfunction after model construction, and the 48th h was identified as the immunoswitching point from excessive inflammatory response to immunosuppression. The results are of great significance for optimizing the timing of SAP immune regulation.

Correlation of Different Serum Biomarkers with Prediction of Early Pancreatic Graft Dysfunction Following Simultaneous Pancreas and Kidney Transplantation

Background: Despite recent advances and refinements in perioperative management of simultaneous pancreas−kidney transplantation (SPKT) early pancreatic graft dysfunction (ePGD) remains a critical problem with serious impairment of early and long-term graft function and outcome. Hence, we evaluated a panel of classical blood serum markers for their value in predicting early graft dysfunction in patients undergoing SPKT. Methods: From a prospectively collected database medical data of 105 patients undergoing SPKT between 1998 and 2018 at our center were retrospectively analyzed. The primary study outcome was the detection of occurrence of early pancreatic graft dysfunction (ePGD), the secondary study outcome was early renal graft dysfunction (eRGD) as well as all other outcome parameters associated with the graft function. In this context, ePGD was defined as pancreas graft-related complications including graft pancreatitis, pancreatic abscess/peritonitis, delayed graft function, graft thrombosis, bleeding, rejection and the consecutive need for re-laparotomy due to graft-related complications within 3 months. With regard to analyzing ePGD, serum levels of white blood cell count (WBC), C-reactive protein (CRP), procalcitonin (PCT), pancreatic lipase as well as neutrophil−lymphocyte ratio (NLR) and platelet−lymphocyte ratio (PLR) were measured preoperatively and at postoperative days (POD) 1, 2, 3 and 5. Further, peak serum levels of CRP and lipase during the first 72 h were evaluated. Receiver operating characteristics (ROC) curves were performed to assess their predictive value for ePGD and eRGD. Cut-off levels were calculated with the Youden index. Significant diagnostic biochemical cut-offs as well as other prognostic clinical factors were tested in a multivariate logistic regression model. Results: Of the 105 patients included, 43 patients (41%) and 28 patients (27%) developed ePGD and eRGD following SPKT, respectively. The mean WBC, PCT, NLR, PLR, CRP and lipase levels were significantly higher on most PODs in the ePGD group compared to the non-ePGD group. ROC analysis indicated that peak lipase (AUC: 0.82) and peak CRP levels (AUC: 0.89) were highly predictive for ePGD after SPKT. The combination of both achieved the highest AUC (0.92; p < 0.01) in predicting ePGD. Concerning eRGD, predictive accuracy of all analyzed serological markers was moderate (all AUC < 0.8). Additionally, multivariable analysis identified previous dialysis/no preemptive transplantation (OR 2.4 (95% CI: 1.41−4.01), p = 0.021), donor age (OR 1.07 (95% CI: 1.03−1.14), p < 0.010), donor body mass index (OR 1.32 (95% CI: 1.01−1.072), p = 0.04), donors cerebrovascular cause of death (OR 7.8 (95% CI: 2.21−26.9), p < 0.010), donor length of ICU stay (OR 1.27 (95% CI: 1.08−1.49), p < 0.010), as well as CIT pancreas (OR 1.07 (95% CI: 1.03−1.14), p < 0.010) as clinical relevant prognostic predictors for ePGD. Further, a peak of lipase (OR 1.04 (95% CI: 1.02−1.07), p < 0.010), peak of CRP levels (OR 1.12 (95% CI: 1.02−1.23), p < 0.010), pancreatic serum lipase concentration on POD 2 > 150 IU/L (OR 2.9 (95% CI: 1.2−7.13), p = 0.021) and CRP levels of ≥ 180 ng/mL on POD 2 (OR 3.6 (95% CI: 1.54−8.34), p < 0.01) and CRP levels > 150 ng/mL on POD 3 (OR 4.5 (95% CI: 1.7−11.4), p < 0.01) were revealed as independent biochemical predictive variables for ePGD after transplantation. Conclusions: In the current study, the combination of peak lipase and CRP levels were highly effective in predicting early pancreatic graft dysfunction development following SPKT. In contrast, for early renal graft dysfunction the predictive value of this parameter was less sensitive. Intensified monitoring of these parameters may be helpful for identifying patients at a higher risk of pancreatic ischemia reperfusion injury and various IRI- associated postoperative complications leading to ePGD and thus deteriorated outcome.

The Value of RANSON Score Combined with BMI in Predicting the Mortality in Severe Acute Pancreatitis: A Retrospective Study

Objective

To explore the value of modified RANSON score in predicting mortality from severe acute pancreatitis (SAP).

Methods

In this retrospective study, 461 SAP patients hospitalized from January 2016 to January 2020 were enrolled. AP (acute pancreatitis) patients from our hospital were employed as the training set. In addition, AP patients from the affiliated hospital of Nantong University were set as the validation set. The clinical characteristics of patients were compared between the two sets. The independent risk factors for SAP were determined through logistic regression. Moreover, the risk factors were derived for various prediction models by logistic regression. Multiple methods were adopted to assess the predictive ability of various models.

Results

A total of 338 patients were assigned into the training set, while 123 patients were assigned into the validation set. The patients in the training and validation sets showed the consistent distribution trends (P>0.05). In the training set, significant differences between patients in the non-survival and survival groups were BMI, PCT, platelets (PLT), direct bilirubin (DBil) and RANSON scores (P<0.05). In further multivariate analysis, BMI, PCT and RANSON score were found as the independent risk factors for the mortality of SAP (OR=1.12, 1.25, 1.28, 95% CI:1.06–1.19, 1.08–1.44, 1.12–1.47, P<0.05). In the training set and validation set, ROC curve analysis showed that AUC of BMI+RANSON score was 0.778 and 0.789, respectively. In the calibration curve, the fitting degree of RANSON score+BMI and ideal assessment model was 0.975 and 0.854, respectively. The decision curve suggested that the net benefit per patient increased with the lengthening of the RANSON score+ BMI model curve. As revealed by the results of NRI and IDI indicators, RANSON score+BMI was optimized based on RANSON score (P<0.05).

Conclusion

BMI+RANSON was confirmed as a modified model effective in predicting the mortality from SAP.

Development and validation of a prediction model for moderately severe and severe acute pancreatitis in pregnancy

BACKGROUND

The severity of acute pancreatitis in pregnancy (APIP) is correlated with higher risks of maternal and fetal death.

AIM

To develop a nomogram that could predict moderately severe and severe acute pancreatitis in pregnancy (MSIP).

METHODS

Patients with APIP admitted to West China Hospital between January 2012 and December 2018 were included in this study. They were divided into mild acute pancreatitis in pregnancy (MAIP) and MSIP. Characteristic parameters and laboratory results were collected. The training set and test set were randomly divided at a ratio of 7:3. Least absolute shrinkage and selection operator regression was used to select potential prognostic factors. A nomogram was developed by logistic regression. A random forest model was used to validate the stability of the prediction factors. Receiver operating characteristic curves and calibration curves were used to evaluate the model’s predictive performance.

RESULTS

A total of 190 patients were included in this study. A total of 134 patients (70.5%) and 56 patients (29.5%) were classified as having MAIP and MSIP, respectively. Four independent predictors (lactate dehydrogenase, triglyceride, cholesterol, and albumin levels) were identified for MSIP. A nomogram prediction model based on these factors was established. The model had areas under the curve of 0.865 and 0.853 in the training and validation sets, respectively. The calibration curves showed that the nomogram has a good consistency.

CONCLUSION

A nomogram including lactate dehydrogenase, triglyceride, cholesterol, and albumin levels as independent predictors was built with good performance for MSIP prediction.

Predictive value of arterial blood lactic acid concentration on the risk of all-cause death within 28 days of admission in patients with severe acute pancreatitis

ObjectiveTo evaluate the ability of arterial blood lactic acid concentration to predict death within 28 days of admission of patients with severe acute pancreatitis (SAP) in the intensive care unit (ICU).MethodsClinical data of 523 SAP patients in the MIMIC-IV database were retrospectively analyzed. Patients were divided into those who survived (n=461) and those who died (n=62) within 28 days of admission. The association between lactic acid concentration and all-cause death in SAP patients was determined by Cox regression analysis, Kaplan-Meier survival analysis and subgroup analysis. The ability of lactic acid concentration to predict the risk of all-cause death in SAP patients was determined by time-dependent receiver operating curve (ROC) analysis.ResultsArterial blood lactic acid concentration was significantly higher in the 62 patients who died within 28 days than in the 461 patients who survived (P <0.05). Adjusted multivariate Cox regression analysis showed that lactic acid concentration was a significant independent predictor on all-cause mortality within 28 days of admission for SAP (hazard ratio=1.22, 95% confidence interval 1.09-1.36, P <0.001), as did time-dependent ROC analysis (area under the ROC curve=0.741). Kaplan-Meier analysis showed that the rate of all-cause mortality within 28 days of admission was significantly higher in patients with high than low lactic acid concentration (P <0.0001). Subgroup analysis showed that there was no significant interaction between lactic acid concentration and other factors with all-cause death within 28 days of admission (all P >0.05).ConclusionArterial blood lactic acid concentration is an important independent predictor of all-cause mortality within 28 days of admission of SAP patients in the ICU.

Serum Lactate Dehydrogenase Is a Sensitive Predictor of Systemic Complications of Acute Pancreatitis

BACKGROUND

Acute pancreatitis (AP) is a common and potentially life-threatening inflammatory disease that can cause various complications, including systemic inflammatory response syndrome (SIRS), pleural effusion, ascitic fluid, myocardial infarction, and acute kidney injury (AKI). However, there is still a lack of rapid and effective indicators to assess the disease. The aim of this study was to investigate the associations of high serum lactate dehydrogenase (LDH) levels with AP severity and systemic complications.

METHODS

AP patients treated from July 2014 to December 2020 were retrospectively enrolled. They were divided into elevated (n = 93) and normal (n = 143) LDH groups. Their demographic data, clinical data, hospital duration, and hospital expenses were analyzed. Linear and binary logistic regression analyses were used to determine whether elevated LDH is a risk factor for AP severity and complications after adjusting for confounders.

RESULTS

There were significant differences in AP severity scores (Ranson, MODS, BISAP, APACHE II, and CTSI), hospital duration, hospital expenses, and the incidences of complications (SIRS, pleural effusion, ascitic fluid, myocardial infarction, and AKI) between the elevated and normal LDH groups. After adjusting for confounders, elevated LDH was associated with AP severity scores and hospital duration and expenses (based on linear regression analyses) and was a risk factor for the occurrence of AP complications and interventions, that is, diuretic and vasoactive agent use (based on binary logistic regression analyses).

CONCLUSIONS

Elevated LDH is associated with high AP severity scores and high incidences of complications (SIRS, pleural effusion, ascitic fluid, myocardial infarction, and AKI).

A prediction model for acute respiratory distress syndrome among patients with severe acute pancreatitis: a retrospective analysis

Background:

Acute respiratory distress syndrome (ARDS) is a severe complication among patients with severe acute pancreatitis (SAP), which may be associated with increased mortality in hospitalized patients. Thus, an effective model to predict ARDS in patients with SAP is urgently required.

Methods:

We retrospectively analyzed the data from the patients with SAP who recruited in Xiangya Hospital between April 2017 and May 2021. Patients meeting the Berlin definition of ARDS were categorized into the ARDS group. Logistic regression models and a nomogram were utilized in the study. Descriptive statistics, logistic regression models, and a nomogram were used in the current study.

Results:

Comorbidity of ARDS occurred in 109 (46.58%) of 234 patients with SAP. The SAP patients with ARDS group had a higher 60-day mortality rate, an increased demand for invasive mechanical ventilation, and a longer intensive care unit (ICU) stay than those without ARDS (p < .001 for all). Partial pressure of oxygen (PaO2): fraction of inspired oxygen (FiO2) < 200, platelets <125 × 109/L, lactate dehydrogenase >250 U/L, creatinine >111 mg/dL, and procalcitonin >0.5 ng/mL were independent risk variables for development of ARDS in SAP patients. The area under the curve for the model was 0.814, and the model fit was acceptable [p = .355 (Hosmer–Lemeshow)]. Incorporating these 5 factors, a nomogram was established with sufficient discriminatory power (C-index 0.814). Calibration curve indicated the proper discrimination and good calibration in the predicting nomogram model.

Conclusion:

The prediction nomogram for ARDS in patients with SAP can be applied using clinical common variables after the diagnosis of SAP. Future studies would be warranted to verify the potential clinical benefits of this model.

Leukocyte cell population data from the blood cell analyzer as a predictive marker for severity of acute pancreatitis

BACKGROUND

The prediction for severe acute pancreatitis (SAP) is the key to give timely targeted treatment. Leukocyte cell population data (CPD) have been widely applied in early prediction and diagnosis of many diseases, but their predictive ability for SAP remains unexplored. We aim to testify whether CPD could be an indicator of AP severity in the early stage of the disease.

METHODS

The prospective observational study was conducted in the emergency department ward of a territory hospital in Shanghai. The enrolled AP patients should meet 2012 Atlanta guideline.

RESULTS

Totally, 103 AP patients and 62 healthy controls were enrolled and patients were classified into mild AP (n = 30), moderate SAP (n = 42), and SAP (n = 31). Forty-two CPD parameters were examined in first 3 days of admission. Four CPD parameters were highest in SAP on admission and were constantly different among 3 groups during first 3 days of hospital stay. Eighteen CPD parameters were found correlated with the occurrence of SAP. Stepwise multivariate logistic regression analysis identified a scoring system of 4 parameters (SD_LALS_NE, MN_LALS_LY, SD_LMALS_MO, and SD_AL2_MO) with a sensitivity of 96.8%, specificity of 65.3%, and AUC of 0.87 for diagnostic accuracy on early identification of SAP. AUC of this scoring system was comparable with MCTSI, SOFA, APACHE II, MMS, BISAP, or biomarkers as CRP, PCT, and WBC in prediction of SAP and ICU transfer or death.

CONCLUSIONS

Several leukocyte CPD parameters have been identified different among MAP, MSAP, and SAP. They might be ultimately incorporated into a predictive system marker for severity of AP.

Combined detection of procalcitonin, heparin-binding protein, and interleukin-6 is a promising assay to diagnose and predict acute pancreatitis

Background

Acute pancreatitis (AP), one of the most common clinical emergencies, is characterized by variable clinical features and inadequate diagnostic methods. At present, the commonly used indicators do not have high specificity and do not necessarily reflect disease severity. We therefore aimed to investigate diagnostic and prognostic value of plasma procalcitonin, heparin‐binding protein, and interleukin‐6 for acute pancreatitis by separate detection and joint detection.

Methods

The study involved 451 participants, including 343 AP patients and 108 healthy controls. We analyzed the association of the three biomarkers with the severity and prognosis of AP.

Results

A statistically significant increase in the mean plasma analyte levels was detected in the study group compared to the control group. Multivariate comparison showed that plasma levels of PCT, HBP, and IL‐6 were all significantly different among the three groups at different sampling times (1st, 3rd, 7th, and 10th day of admission) (p < 0.01). The combination of the three indicators had significantly higher diagnostic value than either the individual markers or pairwise combinations (p < 0.001). The levels of the three were all significantly higher in severe acute pancreatitis (SAP) patients than in non‐SAP patients (p < 0.001); meanwhile, patients with high levels had a worse prognosis than those with low levels (p < 0.05). In multivariate analysis adjusted for age and sex, high levels of PCT, HBP, and IL‐6 were found to be independently associated with the development of AP.

Conclusions

It dramatically improved the diagnostic power of AP when PCT, HBP, and IL‐6 were combined; high PCT, HBP, and IL‐6 levels within 3 days of admission may be the potentially useful indicators for predicting SAP.

The impact of fluid resuscitation via colon on patients with severe acute pancreatitis

Severe acute pancreatitis (SAP) is a life-threatening disease. Fluid Resuscitation Via Colon (FRVC) may be a complementary therapy for early controlled fluid resuscitation. But its clinical application has not been reported. This study aims to explore the impact of FRVC on SAP. All SAP patients with the first onset within 72 h admitted to the hospital were included from January 2014 to December 2018 through electronic databases of Ruijin hospital and were divided into FRVC group (n = 103) and non-FRVC group (n = 78). The clinical differences before and after the therapy between the two groups were analyzed. Of the 181 patients included in the analysis, the FRVC group received more fluid volume and reached the endpoint of blood volume expansion ahead of the non-FRVC group. After the early fluid resuscitation, the inflammation indicators in the FRVC group were lower. The rate of mechanical ventilation and the incidence of hypernatremia also decreased significantly. Using pure water for FRVC was more helpful to reduce hypernatremia. However, Kaplan–Meier 90-day survival between the two groups showed no difference. These results suggest that the combination of FRVC might benefit SAP patients in the early stage of fluid resuscitation, but there is no difference between the prognosis of SAP patients and that of conventional fluid resuscitation. Further prospective study is needed to evaluate the effect of FRVC on SAP patients.

Future Biomarkers for Infection and Inflammation in Febrile Children

Febrile patients, suffering from an infection, inflammatory disease or autoimmunity may present with similar or overlapping clinical symptoms, which makes early diagnosis difficult. Therefore, biomarkers are needed to help physicians form a correct diagnosis and initiate the right treatment to improve patient outcomes following first presentation or admittance to hospital. Here, we review the landscape of novel biomarkers and approaches of biomarker discovery. We first discuss the use of current plasma parameters and whole blood biomarkers, including results obtained by RNA profiling and mass spectrometry, to discriminate between bacterial and viral infections. Next we expand upon the use of biomarkers to distinguish between infectious and non-infectious disease. Finally, we discuss the strengths as well as the potential pitfalls of current developments. We conclude that the use of combination tests, using either protein markers or transcriptomic analysis, have advanced considerably and should be further explored to improve current diagnostics regarding febrile infections and inflammation. If proven effective when combined, these biomarker signatures will greatly accelerate early and tailored treatment decisions.

The predictive and diagnostic accuracy of long pentraxin-3 in COVID-19 pneumonia

Background/aim

The purpose of this study is to evaluate serum pentraxin-3 (PTX-3) levels in Sars-CoV-2 virus infection (COVID-19) patients and to investigate whether PTX-3 predicts the disease prognosis.

Materials and methods

This study was conducted on 88 confirmed COVID-19 patients who were hospitalized due to symptomatic pneumonia between April 15 and August 15, 2020. The patients were divided into two groups as survived patients and non-survived patients. Both groups were compared according to demographic features, comorbid conditions and measurement of the PTX-3 and other laboratory parameters of the patients.

Results

Of 88 patients with COVID-19, 59 (67%) were discharged with complete cure and 29 (33%) resulted in death. 46 (52.3%) of the patients were men. PTX-3 median value (IQR) was 3.66 ng/mL (0.9–27.9) in all patients, 3.3 ng/mL (0.9–27.9) in survivors and 3.91 ng/mL (1.9–23.2) in nonsurvivors which was significantly higher (P = 0.045). As a receiver operating characteristic curve analysis the cut-off value of PTX-3 for predicting mortality in patients was 3.73 with 65% sensitivity and 65% specificity (AUC: 0.646, 95% CI: 0.525– 0.767, P = 0.045). Also, we found significant cut-off values with respect to D-dimer, D-dimer/PTX-3, high-sensitivity troponin, high- sensitivity troponin/PTX-3, lymphocyte, PTX-3/lymphocyte, procalcitonin, procalcitonin/PTX-3, CRP, and CRP/PTX-3 (P < 0.05).

Conclusion

In this study, as far as we know, for the first time, we have shown PTX-3 as the new mortality biomarker for COVID-19 disease.