Procalcitonin Clearance at 24, 48, 72, and 96 Hours and Mortality in Patients With Cancer and Sepsis: A Retrospective Cohort Study

Utility of Serum Procalcitonin and Its Clearance in Predicting Outcomes in COVID-19 Patients

Introduction Identification of coronavirus disease 2019 (COVID-19) patients at risk of worse clinical outcomes is crucial to improving patient care. Various biochemical markers have been used to predict outcomes in such patients. We aimed to evaluate the role of serum PCT (procalcitonin) and the utility of PCT clearance (PCTc) in predicting the outcome of patients with COVID-19 illness. Methods We prospectively included 39 patients with severe or critical COVID-19 illness with an age equal to more than 18 years. In addition to routine baseline investigations, serum PCT was measured at admission (PCT1) and day 5 of hospitalization (PCT2). PCTc was calculated using the formula [Formula: see text]. Results We observed that serum PCT at admission was significantly higher in non-survivors (median: 1.9 ng/ml IQR: 0.51-4.23) compared to survivors (median 0.35 (IQR: 0.1-1.2), p 0.002). On serial serum-PCT estimation, non-survivors had persistently elevated serum-PCT (median PCT1:1.9 ng/ml (IQR: 0.51-4.23) to median PCT2: 1.9ng/ml (IQR: 0.83-2.72), p 0.51) than survivors (median PCT1:0.35ng/ml (IQR: 0.1-1.19) to median PCT2: 0.15ng/ml (IQR: 0.05-0.29), p 0.01). However, no difference in serum PCTc was observed between the two groups (median: 35.3% (IQR: 12.5-84.9) in survivors vs. 71.7% (33.3-91.7) in non-survivors, p = 0.165). Conclusion Serum PCT is a potential biochemical marker that could predict outcomes in COVID-19 patients. Measurement of serial serum PCT and estimation of PCT clearance may serve as better predictors than a single value; however, well-designed studies are required to identify the definite role of serum PCT in COVID-19 patients of varying severity.

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.

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.