The role of presepsin in the diagnosis and assessment of severity of sepsis and severe pneumonia

Титова, Е. А.; Eyrikh, A R; Titova, Z.A.

doi:10.26442/terarkh201890114-47

Cited by 6 publications

(5 citation statements)

References 5 publications

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“…Bacteria are common pathogens of community acquired pneumonia (CAP), but bacterial culture detection from blood and sputum requires several days and gives a not negligible number of false negative results [33]. In this context, plasmatic levels of PSP demonstrated a good diagnostic and prognostic value for bacterial CAP (BCAP) [16], being able to predict ICU mortality in these patients [17]. In the case of active pulmonary tuberculosis (APTB), culture basis diagnosis is not widely available, because Mycobacterium tuberculosis culturing requires specific and long-lasting culture conditions.…”

Section: Psp In Pulmonary Infectionsmentioning

confidence: 99%

Clinical application of presepsin as diagnostic biomarker of infection: overview and updates

Galliera

Massaccesi

Vecchi

et al. 2019

Clinical Chemistry and Laboratory Medicine (CCLM)

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The appropriate identification of bacterial infection is the basis for effective treatment and control of infective disease. Among this context, an emerging biomarker of infection is presepsin (PSP), recently described as early marker of different infections. PSP secretion has been shown to be associated with monocyte phagocytosis and plasmatic levels of PSP increase in response to bacterial infection and decrease after antibiotic treatment, therefore it can be considered a marker of activation of immune cell response towards an invading pathogen. Different methods have been developed to measure PSP and this review will briefly describe the different clinical fields of application of PSP, ranging from intensive care to neonatal infection, to orthopedic and pulmonary infection as well as fungal infections and cardiovascular infections.

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Section: Psp In Pulmonary Infectionsmentioning

confidence: 99%

Clinical application of presepsin as diagnostic biomarker of infection: overview and updates

Galliera

Massaccesi

Vecchi

et al. 2019

Clinical Chemistry and Laboratory Medicine (CCLM)

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“…The patient’s ICU unit reflects the difference in the etiology of sepsis, the more that is known about this the more specific therapies can be, so this also occupies an important part [ 38 ].Sepsis can arise from different causes, such as traumatic infection, postoperative infection, and severe pneumonia, which have different effects on the prognosis of patients [ 39 ]. These should receive recognition in clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Prediction of prognosis in elderly patients with sepsis based on machine learning (random survival forest)

Zhang

et al. 2022

BMC Emerg Med

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Background Elderly patients with sepsis have many comorbidities, and the clinical reaction is not obvious. Thus, clinical treatment is difficult. We planned to use the laboratory test results and comorbidities of elderly patients with sepsis from a large-scale public database Medical Information Mart for Intensive Care (MIMIC) IV to build a random survival forest (RSF) model and to evaluate the model’s predictive value for these patients. Methods Clinical information of elderly patients with sepsis in MIMIC IV database was collected retrospectively. Machine learning (RSF) was used to select the top 30 variables in the training cohort to build the final RSF model. The model was compared with the traditional scoring systems SOFA, SAPSII, and APSIII. The performance of the model was evaluated by C index and calibration curve. Results A total of 6,503 patients were enrolled in the study. The top 30 important variables screened by RSF were used to construct the final RSF model. The new model provided a better C-index (0.731 in the validation cohort). The calibration curve described the agreement between the predicted probability of RSF model and the observed 30-day survival. Conclusions We constructed a prognostic model to predict a 30-day mortality risk in elderly patients with sepsis based on machine learning (RSF algorithm), and it proved superior to the traditional scoring systems. The risk factors affecting the patients were also ranked. In addition to the common risk factors of vasopressors, ventilator use, and urine output. Newly added factors such as RDW, type of ICU unit, malignant cancer, and metastatic solid tumor also significantly influence prognosis.

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“…The prognostic utility of presepsin has also been evaluated in hospitalized patients with a known cause of infection. Two studies on patients with confirmed pneumonia noted an association between presepsin elevation and mortality, with presepsin elevation being more pronounced in septic patients compared to those with the relatively milder presentation of severe pneumonia [ 50 , 51 ]. Similar findings were also reported in a cohort of patients with another definite focus of infection, an enterocutaneous fistula [ 52 ].…”

Section: Reviewmentioning

confidence: 99%

Presepsin as a Diagnostic and Prognostic Biomarker in Sepsis

Velissaris¹,

Zareifopoulos²,

Karamouzos³

et al. 2021

Cureus

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Sepsis is a condition characterized by high morbidity and mortality which is commonly encountered in an emergency and critical care setting. Despite a substantial body of research, the ideal biomarker for the diagnosis and prognostic stratification of septic patients remains unknown. This review aimed to summarize the publications referring to the validity of the biomarker presepsin when used for the detection, monitoring and prognosis in patients suffering with sepsis. This work is a narrative review based on a PubMed/Medline search conducted in order to identify all relevant publications referring to the use of presepsin in sepsis. Search was not limited by year of publication so all articles archived in the database would be retrieved. No article from before 2010 was identified.A total of 57 publications of the last decade were included, all of which support the use of presepsin as a biomarker for the assessment of septic patients. It has been used alone or in combination with commonly used biomarkers in the evaluation of patients with sepsis in settings such as the emergency department and the intensive care unit. It is useful in the initial workup of patients with suspected sepsis in the emergency setting and may be a predictive factor of mortality and the most severe complication of sepsis.Presepsin seems to be a valuable tool for the laboratory workup of sepsis, especially when used in conjunction with other biomarkers and clinical rating scores with an established role in this population. Further research is needed to evaluate the clinical implications of utilizing presepsin measurements in the workup of sepsis.

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The role of presepsin in the diagnosis and assessment of severity of sepsis and severe pneumonia

Cited by 6 publications

References 5 publications

Clinical application of presepsin as diagnostic biomarker of infection: overview and updates

Clinical application of presepsin as diagnostic biomarker of infection: overview and updates

Prediction of prognosis in elderly patients with sepsis based on machine learning (random survival forest)

Presepsin as a Diagnostic and Prognostic Biomarker in Sepsis

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