The value of biomarker-guided antibiotic therapy

Discrepancy of C-Reactive Protein, Procalcitonin and Interleukin-6 at Hospitalization: Infection in Patients with Normal C-Reactive Protein, Procalcitonin and High Interleukin-6 Values

C-reactive protein (CRP) or procalcitonin (PCT) alone has limitations in the early detection of infection or inflammation due to shortcomings in specificity and varied cut-off values. Recently, interleukin (IL)-6 has been assessed, but it is not known to what extent the three values are homogeneous in reality. This retrospective study was conducted with two large datasets (discrepancy set with results within 24 h of admission [7149 patients] and follow-up set until 2 weeks of hospital stay [5261 tests]) consisting of simultaneous examinations of CRP, PCT, and IL-6 between January 2015 and August 2021. The specific discrepant group (n = 102, 1.4%) with normal CRP (<10 mg/L) and PCT (<0.1 ng/mL) and high IL-6 (≥100 pg/mL) values was extracted from the discrepancy set. Dimensionality reduction and visualization were performed using Python. The three markers were not clearly clustered after t-distributed stochastic neighbor embedding. Pearson’s correlation coefficients between two markers were substantially low (0.23−0.55). Among the high normalized IL-6 levels (≥0.5) (n = 349), 17.8% and 38.7% of CRP and PCT levels were very low (≤0.01). 9.2% and 13.4% of normal CRP (n = 1522) had high PCT (≥0.5 ng/mL) and IL-6 (≥100 pg/mL) values, respectively. Infection and bacteremia among 102 patients occurred in 36 (35.3%) and 9 (8.8%) patients, respectively. In patients with bacteremia, IL-6 was the first to increase, followed by PCT and CRP. Our study revealed that CRP, PCT, and IL-6 levels were considerably discrepant, which could be misinterpreted if only CRP tests are performed.

How should we interpret lactate in labour? A reference study

OBJECTIVE

To investigate maternal lactate concentrations in labour and the puerperium.

DESIGN

Reference study.

SETTING

Tertiary obstetric unit.

POPULATION

1279 pregnant women with good perinatal outcomes at term.

METHODS

Electronic patient records were searched for women who had lactate measured on the day of delivery or in the following 24 hours, but who were subsequently found to have a very low likelihood of sepsis, based on their outcomes.

MAIN OUTCOME MEASURES

The normative distribution of lactate and C-reactive protein (CRP), differences according to the mode of birth, and the proportion of results above the commonly used cut-offs (≥2 and ≥4 mmol/l).

RESULTS

Lactate varied between 0.4-5.4 mmol/l (median 1.8 mmol/l, interquartile range [IQR] 1.3-2.5). It was higher in women who had vaginal deliveries than caesarean sections (median 1.9 vs. 1.6 mmol/l, p_diff  < 0.001), demonstrating the association with labour (particularly active pushing in the second stage). In contrast, CRP was more elevated in women who had caesarean sections (median 71.8 mg/l) than those who had vaginal deliveries (33.4 mg/l, p_diff  < 0.001). In total, 40.8% had a lactate ≥2 mmol/l, but 95.3% were <4 mmol/l.

CONCLUSIONS

Lactate in labour and the puerperium is commonly elevated above the levels expected in healthy pregnant or non-pregnant women. There is a paucity of evidence to support using lactate or CRP to make decisions about antibiotics around the time of delivery but, as lactate is rarely higher than 4 mmol/l, this upper limit may still represent a useful severity marker for the investigation and management of sepsis in labour.

Implementation of Procalcitonin in Antibiotic Stewardship: Derivation of a Consensus Algorithm for Procalcitonin Use in Clinical Practice

Reducing antibiotics overuse is essential to minimize antibiotics related side effects and to prevent the emergence of multidrug-resistant bacteria. Procalcitonin (PCT) guided antibiotics therapy has been reported to be safe in patients with acute respiratory infections and sepsis, improving clinical outcomes as well as reducing the duration of antibiotics use. However, there is still no universal agreement on clinical guidelines in Korea for optimal PCT applications. Through this expert consensus meeting, clinical research findings in the PCT-guided antibiotics treatment interventions and real-world clinical applications were discussed. From the perspective of antibiotic stewardship, PCT application target groups, cut-offs, and testing cycles were discussed to reach a consensus on the PCT-guided antibiotics treatment algorithm for application in Korea. Combining clinical assessment for patients with an appropriate PCT-guided antibiotics treatment algorithm could improve the diagnosis and treatment of acute respiratory infections and sepsis. In addition, continuous education and regular feedback would improve the effectiveness of antibiotic stewardship.

Advances in diagnostic tools for respiratory tract infections. From tuberculosis to COVID19: changing paradigms?

Respiratory tract infections (RTI) are one of the commonest reasons for seeking healthcare, but are amongst the most challenging diseases in terms of clinical decision making. Proper and timely diagnosis is critical in order to optimize management and prevent further emergence of antimicrobial resistance by misuse, or overuse of antibiotics. Diagnostic tools for RTI include those involving syndromic and etiological diagnosis: from clinical and radiological features to laboratory methods targeting both pathogen detection and host biomarkers, as well as their combinations in terms of clinical algorithms. They also include tools for predicting severity and monitoring treatment response. Unprecedented milestones have been achieved in the context of the COVID-19 pandemic, involving the most recent applications of diagnostic technologies both at genotypic and phenotypic level, which have changed paradigms in infectious respiratory diseases in terms of why, how and where diagnostics are performed. The aim of this review is to discuss advances in diagnostic tools that impact clinical decision making, surveillance and follow-up of RTI and tuberculosis. If properly harnessed, recent advances in diagnostic technologies, including omics and digital transformation emerge as an unprecedented opportunity to tackle ongoing and future epidemics while handling antimicrobial resistance from a One Health perspective.

Prognostic Value of Procalcitonin, C-Reactive Protein, and Lactate Levels in Emergency Evaluation of Cancer Patients with Suspected Infection

Simple Summary

Cancer patients are at increased risk of infections and related complications, including sepsis. We developed a scoring system for mortality prediction based on readily available clinical and laboratory data, including the quick sequential organ failure assessment (qSOFA) score, cancer subtype, and several laboratory markers (procalcitonin, C-reactive protein, lactate dehydrogenase, and albumin) that can be used in emergency departments for cancer patients with suspected infection. The prediction score, which stratifies patients into four different risk groups (from low risk to very high risk), achieved excellent performance in predicting 14-day mortality, with an area under the receiver operating characteristic curve value of 0.88 (95% confidence interval 0.85–0.91). The score was also effective in predicting intensive care unit admission and 30-day mortality.

Abstract

Cancer patients have increased risk of infections, and often present to emergency departments with infection-related problems where physicians must make decisions based on a snapshot of the patient’s condition. Although C-reactive protein, procalcitonin, and lactate are popular biomarkers of sepsis, their use in guiding emergency care of cancer patients with infections is unclear. Using these biomarkers, we created a prediction model for short-term mortality in cancer patients with suspected infection. We retrospectively analyzed all consecutive patients who visited the emergency department of MD Anderson Cancer Center between 1 April 2018 and 30 April 2019. A clinical decision model was developed using multiple logistic regression for various clinical and laboratory biomarkers; coefficients were used to generate a prediction score stratifying patients into four groups according to their 14-day mortality risk. The prediction score had an area under the receiver operating characteristic curve value of 0.88 (95% confidence interval 0.85–0.91) in predicting 14-day mortality. The prediction score also accurately predicted intensive care unit admission and 30-day mortality. Our simple new scoring system for mortality prediction, based on readily available clinical and laboratory data, including procalcitonin, C-reactive protein, and lactate, can be used in emergency departments for cancer patients with suspected infection.