Procalcitonin clearance for early prediction of survival in critically ill patients with severe sepsis

Study of Biochemical Parameters as Predictors for Need of Invasive Ventilation in Severely Ill COVID-19 Patients

Background

Though laboratory tests have been shown to predict mortality in COVID-19, there is still a dearth of information regarding the role of biochemical parameters in predicting the type of ventilatory support that these patients may require.

Methods

The purpose of our retrospective observational study was to investigate the relationship between biochemical parameters and the type of ventilatory support needed for the intensive care of severely ill COVID-19 patients. We comprehensively recorded history, physical examination, vital signs from point-of-care testing (POCT) devices, clinical diagnosis, details of the ventilatory support required in intensive care and the results of the biochemical analysis at the time of admission. Appropriate statistical methods were used and P-values < 0.05 were considered significant. Receiver operating characteristics (ROC) analysis was performed and Area Under the Curve (AUC) of 0.6 to 0.7, 0.7 to 0.8, 0.8 to 0.9, and >0.9, respectively, were regarded as acceptable, fair, good, and exceptional for discrimination.

Results

Statistically significant differences (p<0.05) in Urea (p = 0.0351), Sodium (p = 0.0142), Indirect Bilirubin (p = 0.0251), Albumin (p = 0.0272), Aspartate Transaminase (AST) (p = 0.0060) and Procalcitonin (PCT) (p = 0.0420) were observed between the patients who were maintained on non-invasive ventilations as compared to those who required invasive ventilation. In patients who required invasive ventilation, the levels of Urea, Sodium, Indirect bilirubin, AST and PCT were higher while Albumin was lower. On ROC analysis, higher levels of Albumin was found to be acceptable indicator of maintenance on non-invasive ventilation while higher levels of Sodium and PCT were found to be fair predictor of requirement of invasive ventilation.

Conclusion

Our study emphasizes the role of biochemical parameters in predicting the type of ventilatory support that is needed in order to properly manage severely ill COVID-19 patients.

28-day sepsis mortality prediction model from combined serial interleukin-6, lactate, and procalcitonin measurements: a retrospective cohort study

Sepsis is a global medical issue owing to its unacceptably high mortality rate. Therefore, an effective approach to predicting patient outcomes is critically needed. We aimed to search for a novel 28-day sepsis mortality prediction model based on serial interleukin-6 (IL-6), lactate (LAC), and procalcitonin (PCT) measurements. We enrolled 367 septic patients based on Sepsis-3 (Third International Consensus Definitions for Sepsis and Septic Shock). Serum IL-6, LAC, and PCT levels were measured serially. Results collected within 24 and 48-72 h of admission were marked as D1 and D3 (e.g., IL-6D1/D3), respectively; the IL-6, LAC, and PCT clearance (IL-6c, LACc, PCTc) at D3 were calculated. Data were split into training and validation cohorts (7:3). Logistic regression analyses were used to select variables to develop models and choose the best one according to the Akaike information criterion (AIC). Receiver operating characteristic curves (ROC), calibration plots, and decision curve analysis (DCA) were used to test model performance. A nomogram was used to validate the model. There were 314 (85.56%) survivors and 53 (14.44%) non-survivors. Logistic regression analyses showed that IL-6D1, IL-6D3, PCTD1, PCTD3, and LACcD3 could be used to develop the best prediction model. The areas under the curves (AUC) of the training (0.849, 95% CI: 0.787-0.911) and validation cohorts (0.828, 95% CI: 0.727-0.929), calibration plot, and the DCA showed that the model performed well. Thus, the predictive value of the risk nomogram was verified. Combining IL-6D1, IL-6D3, PCTD1, PCTD3, and LACcD3 may create an accurate prediction model for 28-day sepsis mortality. Multiple-center research with a larger quantity of data is necessary to determine its clinical utility.

Biochemical Parameters as Prognostic Markers in Severely Ill COVID-19 Patients

Background

Prognostication plays a pivotal role in critical care medicine. Its importance is indisputable in the management of coronavirus disease 2019 (COVID-19), as the presentation of this disease may vary from docile, self-limiting symptoms to lethal conditions. Amid the COVID-19 pandemic, much emphasis was initially placed on molecular and serological testing. However, it was realized later that routine laboratory tests also provide key information in terms of the severity of the disease and thus could be used to predict the outcome of these patients.

Methodology

The aim of our study was to evaluate the biochemical parameters as prognostic markers in severely ill COVID-19 patients. We carried out a retrospective, case-control study. The study population was comprised of all severely ill COVID-19 patients admitted between October 2020 and January 2021 at our level 3 COVID hospital. Cases were defined as the patients who expired despite treatment and all resuscitative measures as per the standard operating procedures (SOPs) of our COVID intensive care unit (ICU) while controls were defined as the patients that were transferred out of the COVID ICU for further recovery. The detailed history, findings of physical examination, vitals recorded by point of care testing (POCT) devices at our ICU, clinical diagnosis, and the results of the biochemical analysis were recorded in a specially designed pro forma. The biochemical parameters recorded at the time of admission were compared between the groups of controls and cases in order to evaluate their role as predictors of mortality using appropriate statistical methods. P-values less than 0.05 were considered statistically significant. For all the parameters that showed a statistically significant difference, receiver operating characteristics (ROC) analysis was done to assess the utility of biochemical parameters as predictors of mortality or survival. Areas under the curve (AUCs) of 0.6 to 0.7, 0.7 to 0.8, 0.8 to 0.9, and >0.9 were considered acceptable, fair, good, and excellent for discrimination, respectively.

Results

Of the 178 severely ill COVID-19 patients enrolled in the study, 86 were controls and 92 were cases (52% mortality). Serum urea (p<0.0001), creatinine (p=0.0019), aspartate transaminase (AST) (p=0.0104), lactate dehydrogenase (LDH) (p=0.0001), procalcitonin (PCT) (p=0.0344), and interleukin 6 (IL-6) (p=0.0311) levels were significantly higher (p<0.05), while total protein (p=0.0086), albumin (p<0.0001), and indirect bilirubin (p=0.0147) levels were significantly lower (p<0.05) in cases as compared to controls. The difference was statistically insignificant (p>0.05) for serum sodium, potassium, total and direct bilirubin, globulin, alanine transaminase (ALT), alkaline phosphatase (ALP), D-dimer, and ferritin. On ROC analysis, urea was fair (AUC=0.721), creatinine (AUC=0.698) and IL-6 (AUC=0.698) were acceptable predictors of mortality, while albumin (AUC=0.698) was an acceptable predictor of survival in severely ill COVID-19 patients during their intensive care stay.

Conclusion

Understanding the pathophysiological changes associated with the severity of COVID-19 in terms of an alteration of biochemical parameters is a pressing priority. Our study highlights the importance of routine laboratory tests in predicting outcomes in severely ill COVID-19 patients.

A Pilot Assessment on the Role of Procalcitonin Dynamic Monitoring in the Early Diagnosis of Infection Post Cardiac Surgery

Purpose

To evaluate the value of dynamic monitoring of procalcitonin (PCT) as a biomarker for the early diagnosis of postoperative infections in patients undergoing cardiac surgery.

Methods

In total, 252 patients who underwent cardiac surgery were retrospectively included. The postoperative patients’ PCT level, change value (△PCT), and clearance rate (△PCTc) were compared between the infected and noninfected groups in adult and pediatric patients on postoperative days (PODs) 1, 3, and 5. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic value.

Results

Procalcitonin concentration decreased progressively in the noninfected group in adult and pediatric patients; PCT concentration continued to rise until it peaked on POD 3 in the infected group. In adult patients, the AUC of PCT for diagnosis of infection on PODs 1, 3, and 5 were 0.626, 0.817, and 0.806, with the optimal cut-off values of 7.35, 3.63, and 1.73 ng/ml, respectively. The diagnostic efficiency of △PCT₃ and △PCT_C3 was significantly better than △PCT₅ and △PCT_C5, respectively. In pediatric patients, the AUC of PCT for diagnosis of infection on PODs 1, 3, and 5 were 0.677, 0.747, and 0.756, respectively, and the optimal cut-off values were 27.62, 26.15, and 10.20 ng/ml.

Conclusion

This study showed that dynamic monitoring of PCT levels could be an effective clinical means to help to discover postoperative infection earlier. The PCT level and its change indicators on POD 3 in adult patients and the PCT level on POD 5 in children can indicate infection.

Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection

Background: Procalcitonin (PCT) is a promising biomarker for predicting infection. Bloodstream infection (BSI) is usually a deteriorating stage of sepsis. The purpose of this study was to explore the predictive value of intense serial PCT assays for BSI in the intensive care unit (ICU). Methods: This study was a retrospective study based on a clinical database. We analyzed the data of critically ill patients from February 2016 to May 2020. The patients who received PCT assays and blood cultures (BCs) were classified into four groups according to the BCs: (i) BC negative, (ii) bacteria positive, (iii) fungi-positive, and (iv) combined-positive, and the patients with bacteremia were further subdivided into Gram+ and Gram- bacteremia. Results: The database included 11,219 patients. There were 3,593 patients who met the criteria for the analysis. The PCT concentration differed significantly across BC groups (p < 0.0001). The fluctuation of PCT significantly increased in the BC positive groups (p < 0.0001). According to the receiver operating characteristic (ROC), the optimum cutoff of the fluctuation of PCT was around 8 ng/ml for predicting BSI. Conclusion: Our study indicated that the fluctuation of PCT could be an indicator for screening BSI, but less accurate for Gram-positive infections. With a fluctuation of PCT less than 8 ng/ml, BSI should not be a rational cause for sepsis exacerbating.

Role of Procalcitonin in the Prognosis of Mortality in Patients Admitted to the Intensive Care Unit: A Review Study

Background

This review study aimed to investigate the role of PCT in the prognosis of mortality among patients admitted to the intensive care units (ICU). Procalcitonin (PCT) is a polypeptide and prohormone of calcitonin. This prohormone is secreted by thyroid gland C cells in response to hypercalcemia, and Its elevated level indicates infection, especially bacterial infections, in which there is a systematic response to infection.

Materials and Methods

This narrative review study was performed based on Cochrane collaboration recommendations for reviews. We reviewed all the titles and abstracts of published research articles with the following inclusion criteria studies aimed to confirm the function of a prognostic model in predicting mortality or survival, (b) mortality or survival of a specific endpoint (for example, 30 days), (c) patients admitted to intensive care units, and d) the articles written in English. The exclusion criteria of the current review included: (a) articles whose data were not specifically focused on prognosis of patients in ICU, (b) articles that did not provide sufficient information on the cause of death of patients in ICU, and (c) articles focusing on the treatment of comorbid patients with infections in ICU. The search was conducted on Google Scholar, PubMed, Magiran, ScienceDirect, and SID. Also, to search Iranian databases, including SID and Magiran, the same terms and expressions were searched.

Results

Based on the findings of this review, serum levels of PCT were reported within the range of at least 5 to more than 16 ng/ml in patients admitted to ICU. The mortality rate was estimated at 5.7% to 79% in these patients. Moreover, the incidence of sepsis was reported from 13% to 77.6%.

Conclusion

Serum levels of PCT as a prognostic factor may help early detection, and better classification of the poor prognoses sepsis patients and more invasive treatment of patients admitted to ICU and are at risk for mortality.

Should serial monitoring of procalcitonin be done routinely in critically ill patients of ICU: A systematic review and meta-analysis

Sepsis is a life-threatening condition with dysregulated host response to infection. It is a major determinant of mortality in the intensive care unit (ICU). Procalcitonin (PCT) is widely investigated for prognosis in patients with sepsis. Most of the studies have cited that elevated PCT concentrations and PCT non-clearance are associated with poor outcomes in patients with sepsis and some studies have cited as having no additional benefit. Most of the studies have evaluated single PCT measurement and correlated with prognosis and outcome in septic patients. Limited literature is there about serial PCT levels and its impact on the outcome of patients with sepsis. We searched literature through PubMed, Embase, Web of Knowledge, and the Cochrane Library from 2007 to 2017 and present a systematic review and meta-analysis of studies evaluating the utility of serial measurement of PCT for prognosis in critically ill patients. Articles that assessed PCT non-clearance as a marker of mortality data were included. The primary objective of this meta-analysis was to pool the results of all the available studies on serial PCT non-clearance as a mortality predictor and formulate overall area under receiver operating curve (AUROC). To find out the overall proportion of mortality in PCT non-clearance was our secondary objective. To detect the mortality using PCT non-clearance, ROC curve analysis was done. Area under curve (AUC) of the studies was varying between 0.52 and 0.86. Overall AUC was observed 0.711 (95% confidence interval (CI): 0.662–0.760) under fixed effect model and 0.708 (95% CI: 0.648–0.769) under random effect model. There was moderate variation among the studies, i.e., I² 50.80% (95% CI: 0.00–80.42%). The overall proportion of mortality was 37.54% with much heterogeneity (I² 88.24%) among the studies. PCT non-clearance is a fair predictor of mortality. Further studies are needed to define optimal cut off point for PCT non-clearance in ICU patients with sepsis.

Toddalolactone Protects Lipopolysaccharide-Induced Sepsis and Attenuates Lipopolysaccharide-Induced Inflammatory Response by Modulating HMGB1-NF-κB Translocation

Toddalolactone (TA-8) is a main compound isolated from Toddalia asiatica (L.) Lam., and its anti-inflammatory activity and anti-inflammatory mechanism are less studied. In the present study, we investigated the anti-inflammatory effects of TA-8. Our experimental results showed that TA-8 inhibited the production of pro-inflammatory cytokines by both lipopolysaccharide (LPS)-activated RAW 264.7 cells and septic mice. Moreover, TA-8 suppressed the NF-κB transcriptional activity, reduced the nuclear translocation and phosphorylation of NF-κB, blocked the translocation of HMGB1 from the nucleus to cytosol, and decreased LPS-induced up-regulation of TLR4 and IKBKB expression, and decreased IκBα phosphorylation. In addition, the administration of TA-8 decreased LPS-induced liver damage markers (AST and ALT), attenuated infiltration of inflammatory cells and tissue damage of lung, liver, and kidney, and improved survival in septic mice. Taken together, these results suggested that toddalolactone protects LPS-induced sepsis and attenuates LPS-induced inflammatory response by modulating HMGB1-NF-κB translocation. TA-8 could potentially be a novel anti-inflammatory and immunosuppressive drug candidate in the treatment of sepsis and septic shock.

Checking procalcitonin suitability for prognosis and antimicrobial therapy monitoring in burn patients

Background

Due to greater infection susceptibility, sepsis is the main cause of death in burn patients. Quick diagnosis and patient stratification, early and appropriated antimicrobial therapy, and focus control are crucial for patients' survival. On the other hand, superfluous extension of therapy is associated with adverse events and arousal of microbial resistance. The use of biomarkers, necessarily coupled with close clinical examination, may predict outcomes, stratifying patients who need more intensive care, and monitor the efficacy of antimicrobial therapy, allowing faster de-escalation or stop, reducing the development of resistance and possibly the financial burden, without increasing mortality. The aim of this work is to check the suitability of procalcitonin (PCT) to fulfill these goals in a large sample of septic burn patients.

Methods

One hundred and one patients, with 15% or more of total body surface area (TBSA) burned, admitted from January 2011 to December 2014 at Coimbra Burns Unit (CBU), in Portugal were included in the sample. All patients had a diagnosis of sepsis, according to the American Burn Association (ABA) criteria. The sample was factored by survival (68 survivors and 33 non-survivors). The maximum value of PCT in each day was used for statistical analysis. Data were summarized by location measures (mean, median, minimum, maximum, quartiles) and dispersion measures (standard error and range measures). Statistical analysis was performed with SPSS© 23.0 IBM© for Windows©.

Results

There were statistically significant differences between PCT levels of patients from the survivor and non-survivor groups during the first and the last weeks of hospitalization as well as during the first week after sepsis suspicion, being slightly higher during this period. During the first 7 days of antimicrobial therapy, PCT was always higher in the non-survivor, still without reaching statistical significance, but when the analysis was extended till the 15th day, PCT increased significantly, rapidly, and steadily, denouncing therapy failure.

Conclusion

Despite being not an ideal biomarker, PCT proved to have good prognostic power in septic burn patients, paralleling the evolution of the infectious process and reflecting the efficacy of antimicrobial therapy, and the inclusion of its serial dosing may be advised to reinforce antimicrobial stewardship programs at burn units; meanwhile, more accurate approaches are not available.

Procalcitonin-guided antibiotic therapy in critically ill adults: a meta-analysis

Background

As a novel biomarker of inflammation, procalcitonin (PCT) has proven useful to guide antibiotic therapy in intensive care unit (ICU). However, there are controversial on mortality. The aim of this study was to evaluate the utility of PCT-guided antibiotic therapy in critically ill adults and determine whether studies are sufficient.

Methods

A systematic search in PubMed, Embase and Cochrane was performed. We included only randomized controlled trials which compared the safety and efficacy between PCT-guided or standard antibiotic therapy groups in ICU adults. Trial sequential analysis and GARDE approach were performed.

Results

Fifteen studies met our criteria for inclusion finally, with a cumulative number of 5486 ICU patients. There was no difference in 28-day mortality between two compared groups (P = 0.626), but significant decreases were observed in the duration of antibiotic therapy for the first episode of infection (P < 0.001) and length of hospitalization (P = 0.049). No significant deference was found in secondary endpoints except total duration of antibiotic therapy (P < 0.001). TSA revealed that the pooled sample sizes of 28-day mortality and the duration of antibiotic therapy for the first episode of infection exceeded the estimated required information size, but not the length of hospitalization.

Conclusions

PCT-guided therapy is a better and safer algorithm to be applied into ICU patients, which appears no effect on 28-day mortality while performing preferable utility in reducing the duration of antibiotic therapy for the first episode of infection. More studies on these endpoints were not recommended.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2622-3) contains supplementary material, which is available to authorized users.

Early Kinetics of Procalcitonin in Predicting Surgical Outcomes in Type A Aortic Dissection Patients

BACKGROUND

In cardiac surgery, elevation of procalcitonin (PCT) could be observed postoperatively in the absence of any evidence of infection and also seems to be a prognostic marker. PCT levels measured in patients undergoing Type A aortic dissection (TAAD) were used to determine prognostic values for complications and surgical outcomes.

METHODS

Measurements of PCT, C-reactive protein (CRP), and leukocyte count were observed in TAAD surgery patients (n = 251; average age: 49.02 ± 12.83 years; 78.5% male) at presurgery (T0) and 24 h (T1), 48 h (T2), and 7 days (T3) postsurgery. PCT clearance (PCTc) on days 2 and 7 was calculated: (PCTday1- PCTday2/day7)/PCTday1 × 100%. Endotracheal intubation duration, length of stay (LOS) in the Intensive Care Unit (ICU)/hospital, and complications were recorded.

RESULTS

PCT peaked 24 h postsurgery (median 2.73 ng/ml) before decreasing. Correlation existed between PCT levels at T1 and duration of cardiopulmonary bypass (P = 0.001, r = 0.278). Serum PCT concentrations were significantly higher in nonsurvivor and multiple organ dysfunction syndrome groups on all postoperative days. PCT levels at T1 correlated with length of time of ventilation support and ICU/hospital LOS. Comparing PCT values of survivors versus nonsurvivors, a PCT cutoff level of 5.86 ng/ml at T2 had high sensitivity (70.6%) and specificity (74.3%) in predicting in-hospital death. PCTc-day 2 and 7 were significantly higher in survivor compared with nonsurvivor patients (38% vs. 8%, P= 0.012, 83% vs. -39%, P< 0.001). A PCTc-day 7 cutoff point of 48.7% predicted survival with high sensitivity (77.8%) and specificity (81.8%).

CONCLUSIONS

PCT level and PCTc after TAAD surgery might serve as early prognostic markers to predict postoperative outcome. PCT measurement may help identify high-risk patients.

Dynamic Changes of Plasma Neutrophil Gelatinase-Associated Lipocalin Predicted Mortality in Critically Ill Patients with Systemic Inflammatory Response Syndrome

Background and Aims:

About 50% of patients admitted to the Intensive Care Unit have systemic inflammatory response syndrome (SIRS), and about 10%–20% of them died. Early risk stratification is important to reduce mortality. Plasma neutrophil gelatinase-associated lipocalin (NGAL) is increased by inflammation and infection. Its ability to predict mortality in SIRS patients is of interest. We evaluated the ability of serial measurement of NGAL for the prediction of mortality in critically ill patients with SIRS.

Materials and Methods:

This is a secondary analysis of a single-center, prospective, observational study. Patients who fulfill the SIRS criteria were recruited in the study. Delta NGAL at 24 and 48 h (ΔNGAL-24 and ΔNGAL-48) was defined as 24 and 48 h NGAL minus day 1 NGAL; NGAL clearance (NGALc) was defined as percentage of ΔNGAL over day 1 NGAL. The primary outcome of the study is in-hospital mortality.

Results:

A total of 151 patients were analyzed, of which 53 (35%) died. Nonsurvivors were older (51 vs. 45, P = 0.03) and had higher Sequential Organ Failure Assessment (9 ± 7 vs. 7 ± 4, P = 0.02) and Simplified Acute Physiology Score II (47 ± 15 vs. 40 ± 15, P = 0.01) scores as compared to survivors. NGAL concentrations over 3 days were higher in nonsurvivors compared to survivors (repeated measures analysis of variance, P = 0.02). Day 1 NGAL, ΔNGAL-24, and NGALc-24 were not independently predictive of mortality. However, day 3 NGAL, ΔNGAL-48, and NGALc-48 were predictive after adjusted for age and severity of illness (odds ratio 9.1 [1.97–41.7]).

Conclusions:

NGAL dynamics over 48 h independently predicted mortality in critically ill patients with SIRS. This could assist clinicians in risk stratification of this group of high-risk patients.

Serum Procalcitonin as a Biomarker for the Prediction of Bacterial Exacerbation and Mortality in Severe COPD Exacerbations Requiring Mechanical Ventilation

BACKGROUND

Procalcitonin (PCT) is being used as a marker of bacterial infections. Although there are several studies showing the diagnostic yield of PCT to differentiate bacterial involvement in chronic obstructive pulmonary disease exacerbations (COPDE), the prognostic yield of PCT in severe COPDE has been studied less.

OBJECTIVES

The primary aim was to determine whether the level of serum PCT at admission in severe COPDE serves as a prognostic biomarker for hospital mortality. The secondary aim was to determine the role of PCT in identifying a bacterial exacerbation.

METHODS

A total of 63 COPDE patients (median age 71 years; male 58.7%) were retrospectively analyzed from our intensive care unit database.

RESULTS

The hospital mortality rate was 23.8%. Admission PCT levels were higher in patients who died during hospitalization (0.66 vs. 0.17 ng/ml; p = 0.014). This association between hospital mortality and serum PCT level remained significant in a multivariate analysis; for every 1 ng/ml increase in PCT level, hospital mortality increased 1.85 times (odds ratio; 95% confidence interval: 1.07-3.19; p = 0.026). The optimal admission PCT threshold was 0.25 ng/ml in order to discern patients who had bacterial exacerbation with a sensitivity of 63%, a specificity of 67%, and a negative predictive value of 80%. The negative predictive value increased to 89% when both the admission and follow-up PCT levels remained <0.25 ng/ml.

CONCLUSION

This study shows that admission PCT levels have a prognostic importance in estimating hospital mortality among patients with severe COPDE. A PCT level <0.25 ng/ml at the time of admission and during follow-up is suggestive of the absence of a bacterial cause of COPDE.

Carriere K, Chung CR. Clinical Usefulness of Procalcitonin and C-Reactive Protein as Outcome Predictors in Critically Ill Patients with Severe Sepsis and Septic Shock

Sepsis is a major cause of mortality and morbidity in critically ill patients. Procalcitonin (PCT) and C-reactive protein (CRP) are the most frequently used biomarkers in sepsis. We investigated changes in PCT and CRP concentrations in critically ill patients with sepsis to determine which biochemical marker better predicts outcome. We retrospectively analyzed 171 episodes in 157 patients with severe sepsis and septic shock who were admitted to the Samsung Medical Center intensive care unit from March 2013 to February 2014. The primary endpoint was patient outcome within 7 days from ICU admission (treatment failure). The secondary endpoint was 28-day mortality. Severe sepsis was observed in 42 (25%) episodes from 41 patients, and septic shock was observed in 129 (75%) episodes from 120 patients. Fifty-five (32%) episodes from 42 patients had clinically-documented infection, and 116 (68%) episodes from 99 patients had microbiologically-documented infection. Initial peak PCT and CRP levels were not associated with treatment failure and 28-day mortality. However, PCT clearance (PCTc) and CRP (CRPc) clearance were significantly associated with treatment failure (p = 0.027 and p = 0.030, respectively) and marginally significant with 28-day mortality (p = 0.064 and p = 0.062, respectively). The AUC for prediction of treatment success was 0.71 (95% CI, 0.61–0.82) for PCTc and 0.71 (95% CI, 0.61–0.81) for CRPc. The AUC for survival prediction was 0.77 (95% CI, 0.66–0.88) for PCTc and 0.77 (95% CI, 0.67–0.88) for CRPc. Changes in PCT and CRP concentrations were associated with outcomes of critically ill septic patients. CRP may not be inferior to PCT in predicting outcome in these patients.

Prognostic Value of Procalcitonin in Adult Patients with Sepsis: A Systematic Review and Meta-Analysis

Procalcitonin (PCT) has been widely investigated for its prognostic value in septic patients. However, studies have produced conflicting results. The purpose of the present meta-analysis is to explore the diagnostic accuracy of a single PCT concentration and PCT non-clearance in predicting all-cause sepsis mortality. We searched PubMed, Embase, Web of Knowledge and the Cochrane Library. Articles written in English were included. A 2 × 2 contingency table was constructed based on all-cause mortality and PCT level or PCT non-clearance in septic patients. Two authors independently evaluated study eligibility and extracted data. The diagnostic value of PCT in predicting prognosis was determined using a bivariate meta-analysis model. We used the Q-test and I² index to test heterogeneity. Twenty-three studies with 3,994 patients were included. An elevated PCT level was associated with a higher risk of death. The pooled relative risk (RR) was 2.60 (95% confidence interval (CI), 2.05–3.30) using a random-effects model (I² = 63.5%). The overall area under the summary receiver operator characteristic (SROC) curve was 0.77 (95% CI, 0.73–0.80), with a sensitivity and specificity of 0.76 (95% CI, 0.67–0.82) and 0.64 (95% CI, 0.52–0.74), respectively. There was significant evidence of heterogeneity for the PCT testing time (P = 0.020). Initial PCT values were of limited prognostic value in patients with sepsis. PCT non-clearance was a prognostic factor of death in patients with sepsis. The pooled RR was 3.05 (95% CI, 2.35–3.95) using a fixed-effects model (I² = 37.9%). The overall area under the SROC curve was 0.79 (95% CI, 0.75–0.83), with a sensitivity and specificity of 0.72 (95% CI, 0.58–0.82) and 0.77 (95% CI, 0.55–0.90), respectively. Elevated PCT concentrations and PCT non-clearance are strongly associated with all-cause mortality in septic patients. Further studies are needed to define the optimal cut-off point and the optimal definition of PCT non-clearance for accurate risk assessment.