The Shapiro–Procalcitonin algorithm (SPA) as a decision tool for blood culture sampling: validation in a prospective cohort study

Wyss, Géraldine; Berger, Silvia; Haubitz, Sebastian; Fankhauser, Hans; Buergi, Ulrich; Müeller, Beat; Schuetz, Philipp; Fux, Christoph A; Conen, Anna

doi:10.1007/s15010-020-01423-6

Cited by 10 publications

(16 citation statements)

References 38 publications

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“…Schuetz, Philipp et al proposed specific procalcitonin algorithms for patients with low, moderate, and high sensitivity to reduce excessive antibiotic exposure in patients with respiratory infections and sepsis in 2011 ( 30 ). The Shapiro-Procalcitonin algorithm had been validated prospectively in 2020 to be highly valuable in predicting bacteremia, increasing the positive rate of true blood culture from 15 to 26% ( 31 ). Professor Vincent Jl ’s articles were the most cited among the top 10 cited authors, far more than other scholars.…”

Section: Discussionmentioning

confidence: 99%

Research frontiers and trends in the application of artificial intelligence to sepsis: A bibliometric analysis

Tang

Zhao

et al. 2023

Front. Med.

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BackgroundWith the increasing interest of academics in the application of artificial intelligence to sepsis, thousands of papers on this field had been published in the past few decades. It is difficult for researchers to understand the themes and latest research frontiers in this field from a multi-dimensional perspective. Consequently, the purpose of this study is to analyze the relevant literature in the application of artificial intelligence to sepsis through bibliometrics software, so as to better understand the development status, study the core hotspots and future development trends of this field.MethodsWe collected relevant publications in the application of artificial intelligence to sepsis from the Web of Science Core Collection in 2000 to 2021. The type of publication was limited to articles and reviews, and language was limited to English. Research cooperation network, journals, cited references, keywords in this field were visually analyzed by using CiteSpace, VOSviewer, and COOC software.ResultsA total of 8,481 publications in the application of artificial intelligence to sepsis between 2000 and 2021 were included, involving 8,132 articles and 349 reviews. Over the past 22 years, the annual number of publications had gradually increased exponentially. The USA was the most productive country, followed by China. Harvard University, Schuetz, Philipp, and Intensive Care Medicine were the most productive institution, author, and journal, respectively. Vincent, Jl and Critical Care Medicine were the most cited author and cited journal, respectively. Several conclusions can be drawn from the analysis of the cited references, including the following: screening and identification of sepsis biomarkers, treatment and related complications of sepsis, and precise treatment of sepsis. Moreover, there were a spike in searches relating to machine learning, antibiotic resistance and accuracy based on burst detection analysis.ConclusionThis study conducted a comprehensive and objective analysis of the publications on the application of artificial intelligence in sepsis. It can be predicted that precise treatment of sepsis through machine learning technology is still research hotspot in this field.

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Section: Discussionmentioning

confidence: 99%

Research frontiers and trends in the application of artificial intelligence to sepsis: A bibliometric analysis

Tang

Zhao

et al. 2023

Front. Med.

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“…The same is true for procalcitonin: a recent study found that a combination of procalcitonin with a clinical prediction score for blood culture positivity was able to significantly reduce the number of blood cultures with very few positive cultures being missed (3). In fact, that study concluded that procalcitonin in combination with the clinical SHAPIRO score has high predictive value for bacteremia, increasing true culture positivity from 15% to 26%; restricting sampling based on the combination of biomarker and clinical criteria would have reduced sampling by 48%, whereas still detecting 90% of organisms (3, 4). Other studies have come up with similar conclusions when combining procalcitonin with clinical prediction rules regarding blood culture positivity (5).…”

Section: To the Editormentioning

confidence: 97%

“…For example, d-dimers show suboptimal discrimination based on area under the curve measures regarding the prediction of pulmonary embolism with many false-positive results; still, without a doubt, using d-dimer within a well-validated clinical algorithm based on the clinical pretest probability and a low cutoff with a high negative predictive value helps to significantly reduce unnecessary CT scans and other diagnostic and therapeutic measures (2). The same is true for procalcitonin: a recent study found that a combination of procalcitonin with a clinical prediction score for blood culture positivity was able to significantly reduce the number of blood cultures with very few positive cultures being missed (3). In fact, that study concluded that procalcitonin in combination with the clinical SHAPIRO score has high predictive value for bacteremia, increasing true culture positivity from 15% to 26%; restricting sampling based on the combination of biomarker and clinical criteria would have reduced sampling by 48%, whereas still detecting 90% of organisms (3,4).…”

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confidence: 99%

“…A positive blood culture may be the only means through which a bacterial pathogen and its antibiotic susceptibility can be identified. Without these data, patients are at increased risk of misdiagnosis and inappropriate antibiotic therapy, increasing their risk for poor outcomes (3,4). Are the potential savings on blood culture sampling that could be made through incorporation of procalcitonin into the clinical assessment, as suggested by…”

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confidence: 99%

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The Value of a Biomarker Should be Judged on What it Adds to the Clinical Assessment: Not the Area Under the Curve

Schuetz

2023

Critical Care Medicine

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“…The vein puncture site was properly disinfected with 70% alcohol and 2% tincture of iodine. Two bottles of blood for each patient were collected (5ml blood for patients older than ve years and 1-3ml for under ve patients) aseptically from both hands within 30-minute difference [30]. After obtaining the blood, it was inoculated at bedside into Tryptone Soy Broth (TSB) (Oxoid, Hampshire, UK) maintaining a minimum of blood to broth ratio 1:10.…”

Section: Data Collection Specimen Processing and Culturing For Identi...mentioning

confidence: 99%

Phenotypic Bacterial Isolates, Antimicrobial Susceptibility Pattern and Associated Factors among Septicemia Suspected Patients at a hospital, in Northwest Ethiopia. Prospective cross- sectional study

Belew

Tamir

Dilnessa

et al. 2022

Preprint

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Background Septicemia is a life-threatening infection when pathogenic bacteria infiltrate the bloodstream, leading morbidity and mortality in Ethiopian hospital patients. Multidrug resistance is a therapeutic challenge among this patient and has a paucity of data in the hospitals. Therefore, this study aimed to assess the bacterial isolates, antimicrobial susceptibility pattern, and associated factors among septicemia suspected patients. Methods Prospective cross-sectional study was conducted among 214 septicemia suspected patients from February to June 2021 a hospital in northwest, Ethiopia. Blood samples were collected aseptically and processed to identify bacterial isolates by using different standard microbiological procedures. Antimicrobial susceptibility pattern was performed using the modified Kirby Bauer disc diffusion on Mueller Hinton agar. Epi-data V4.2 was used to enter data and SPSS V25 for analysis. The variables were assessed using a bivariate logistic regression model with a 95% confidence interval, and declared statistically significant; P-value was < 0.05. Results The overall bacterial isolates was found 45/214 (21%) in this study. Gram-negative and positive bacteria were 25/45(55.6%), 20/45(44.4%) respectively. The most common bacterial isolates were Staphylococcus aureus12/45 (26.7%), Klebsiella pneumonia8/45(17.8%), Escherichia coli 6/45 (13.3%). Gram-negative bacteria showed susceptible to amikacin (88%), meropenem, imipenem (76%), but resistance to (92%) ampicillin, (85.7%) amoxicillin-clavulanic acid. S.aureus (91.7%) resistance to Penicillin, (58.3%) cefoxitin and (75%) susceptible to ciprofloxacillin. S.pyogenes and S.agalactia were (100%) susceptible to Vancomacin. Multidrug resistance was found in 27/45(60%) of the bacterial isolates. The main predictors related to patients suspected of septicemia were prolonged hospitalization (AOR = 2.29, 95% CI: 1.18, 7.22), fever (AOR = 0.39, 95%CI: 0.18, 0.85) and length of hospital stay (AOR = 0.13, 95%CI: 0.02, 0.82). Conclusions Bacterial isolates among septicemia suspected patients were high. The majority of the bacterial isolates were multidrug-resistant. To prevent antimicrobial resistance, specific antibiotic utilization strategy should be applied.

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The Shapiro–Procalcitonin algorithm (SPA) as a decision tool for blood culture sampling: validation in a prospective cohort study

Cited by 10 publications

References 38 publications

Research frontiers and trends in the application of artificial intelligence to sepsis: A bibliometric analysis

Research frontiers and trends in the application of artificial intelligence to sepsis: A bibliometric analysis

The Value of a Biomarker Should be Judged on What it Adds to the Clinical Assessment: Not the Area Under the Curve

Phenotypic Bacterial Isolates, Antimicrobial Susceptibility Pattern and Associated Factors among Septicemia Suspected Patients at a hospital, in Northwest Ethiopia. Prospective cross- sectional study

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