Clinical impact of matrix-assisted laser desorption ionization time-of-flight mass spectrometry for the management of inpatient pneumonia without additional antimicrobial stewardship support

Kratz, Ann; Sullivan, Kaede V.; Gallagher, Jason C

doi:10.1017/ice.2019.191

Cited by 5 publications

(3 citation statements)

References 9 publications

(1 reference statement)

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“…These findings are consistent with those reported by Perez-Lopez [34], emphasizing that rapid reporting contributes to the optimization of antibiotherapy. Our results align with studies conducted by de la Pedrosa [8], Osthoff [35,36], which describe the clinical impact of reducing the time for identification information and employ a similar methodology to our study. Notably, we report the antibiogram at 6-8 h after antimicrobial identification, while Osthoff [35], which takes the shortest of the three studies cited, takes 10 h. Other studies have demonstrated a statistically significant reduction in overall mortality and mortality related to infections with rapid diagnosis [37,38].…”

Section: Discussionsupporting

confidence: 90%

Clinical Impact of Rapid Bacterial Microbiological Identification with the MALDI-TOF MS

Uzuriaga,

Leiva,

Guillén-Grima

et al. 2023

Antibiotics

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Rapid microbiological reports to clinicians are related to improved clinical outcomes. We conducted a 3-year quasi-experimental design, specifically a pretest–posttest single group design in a university medical center, to evaluate the clinical impact of rapid microbiological identification information using MALDI-TOF MS on optimizing antibiotic prescription. A total of 363 consecutive hospitalized patients with bacterial infections were evaluated comparing a historical control group (CG) (n = 183), in which the microbiological information (bacterial identification and antibiotic susceptibility) was reported jointly to the clinician between 18:00 h and 22:00 h of the same day and a prospective intervention group (IG) (n = 180); the bacterial identification information was informed to the clinician as soon as it was available between 12:00 h and 14:00 h and the antibiotic susceptibility between 18:00 h and 22:00 h). We observed, in favor of IG, a statistically significant decrease in the information time (11.44 h CG vs. 4.48 h IG (p < 0.01)) from the detection of bacterial growth in the culture medium to the communication of identification. Consequently, the therapeutic optimization was improved by introducing new antibiotics in the 10–24 h time window (p = 0.05) and conversion to oral route (p = 0.01). Additionally, we observed a non-statistically significant decrease in inpatient mortality (global, p = 0.15; infection-related, p = 0.21) without impact on hospital length of stay. In conclusion, the rapid communication of microbiological identification to clinicians reduced reporting time and was associated with early optimization of antibiotic prescribing without worsening clinical outcomes.

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Section: Discussionsupporting

confidence: 90%

Clinical Impact of Rapid Bacterial Microbiological Identification with the MALDI-TOF MS

Uzuriaga,

Leiva,

Guillén-Grima

et al. 2023

Antibiotics

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“…This finding illustrates an antimicrobial stewardship principle that occurs frequently in the literature: educational or informational resources make an impact when accompanied by patient-level antimicrobial stewardship team intervention. [10][11][12][13][14] More involvement of antimicrobial stewardship teams in provider-facing activities, such as audit and feedback and in-person presence on rounds ("handshake stewardship"), may be particularly effective. 2,[15][16][17][18][19] Physicians in our survey indicated that online general medical resources (eg, UpToDate, Wolters Kluwer) are the most frequently referenced when making antibiotic prescribing decisions.…”

Section: Discussionmentioning

confidence: 99%

Performance of infectious diseases specialists, hospitalists, and other internal medicine physicians in antimicrobial case-based scenarios: Potential impact of antimicrobial stewardship programs at 16 Veterans’ Affairs medical centers

Graber

Simon

Zhang

et al. 2022

Infect. Control Hosp. Epidemiol.

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Objective: As part of a project to implement antimicrobial dashboards at select facilities, we assessed physician attitudes and knowledge regarding antibiotic prescribing. Design: An online survey explored attitudes toward antimicrobial use and assessed respondents’ management of four clinical scenarios: cellulitis, community-acquired pneumonia, non–catheter-associated asymptomatic bacteriuria, and catheter-associated asymptomatic bacteriuria. Setting: This study was conducted across 16 Veterans’ Affairs (VA) medical centers in 2017. Participants: Physicians working in inpatient settings specializing in infectious diseases (ID), hospital medicine, and non-ID/hospitalist internal medicine. Methods: Scenario responses were scored by assigning +1 for answers most consistent with guidelines, 0 for less guideline-concordant but acceptable answers and −1 for guideline-discordant answers. Scores were normalized to 100% guideline concordant to 100% guideline discordant across all questions within a scenario, and mean scores were calculated across respondents by specialty. Differences in mean score per scenario were tested using analysis of variance (ANOVA). Results: Overall, 139 physicians completed the survey (19 ID physicians, 62 hospitalists, and 58 other internists). Attitudes were similar across the 3 groups. We detected a significant difference in cellulitis scenario scores (concordance: ID physicians, 76%; hospitalists, 58%; other internists, 52%; P = .0087). Scores were numerically but not significantly different across groups for community-acquired pneumonia (concordance: ID physicians, 75%; hospitalists, 60%; other internists, 56%; P = .0914), for non–catheter-associated asymptomatic bacteriuria (concordance: ID physicians, 65%; hospitalists, 55%; other internists, 40%; P = .322), and for catheter-associated asymptomatic bacteriuria (concordance: ID physicians, 27% concordant; hospitalists, 8% discordant; other internists 13% discordant; P = .12). Conclusions: Significant differences in performance regarding management of cellulitis and low overall performance regarding asymptomatic bacteriuria point to these conditions as being potentially high-yield targets for stewardship interventions.

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“…However, the technical cost is high and it can only be carried out in qualified units. 11 Therefore, early identification of the pathogenic bacteria responsible for pneumonia is particularly important.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Model for the Diagnosis and Discrimination of Gram-Positive and Gram-Negative Bacterial Pneumonia for Children Using Chest Radiography Images and Clinical Information

Wen¹,

Xu²,

Cai³

et al. 2023

IDR

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Purpose This study aimed to develop a deep learning model based on chest radiography (CXR) images and clinical data to accurately classify gram-positive and gram-negative bacterial pneumonia in children to guide the use of antibiotics. Methods We retrospectively collected CXR images along with clinical information for gram-positive (n=447) and gram-negative (n=395) bacterial pneumonia in children from January 1, 2016, to June 30, 2021. Four types of machine learning models based on clinical data and six types of deep learning algorithm models based on image data were constructed, and multi-modal decision fusion was performed. Results In the machine learning models, CatBoost, which only used clinical data, had the best performance; its area under the receiver operating characteristic curve (AUC) was significantly higher than that of the other models (P<0.05). The incorporation of clinical information improved the performance of deep learning models that relied solely on image-based classification. Consequently, AUC and F1 increased by 5.6% and 10.2% on average, respectively. The best quality was achieved with ResNet101 (model accuracy: 0.75, recall rate: 0.84, AUC: 0.803, F1: 0.782). Conclusion Our study established a pediatric bacterial pneumonia model that utilizes CXR and clinical data to accurately classify cases of gram-negative and gram-positive bacterial pneumonia. The results confirmed that the addition of image data to the convolutional neural network model significantly improved its performance. While the CatBoost-based classifier had greater advantages owing to a smaller dataset, the quality of the Resnet101 model trained using multi-modal data was comparable to that of the CatBoost model, even with a limited number of samples.

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Clinical impact of matrix-assisted laser desorption ionization time-of-flight mass spectrometry for the management of inpatient pneumonia without additional antimicrobial stewardship support

Cited by 5 publications

References 9 publications

Clinical Impact of Rapid Bacterial Microbiological Identification with the MALDI-TOF MS

Clinical Impact of Rapid Bacterial Microbiological Identification with the MALDI-TOF MS

Performance of infectious diseases specialists, hospitalists, and other internal medicine physicians in antimicrobial case-based scenarios: Potential impact of antimicrobial stewardship programs at 16 Veterans’ Affairs medical centers

A Deep Learning Model for the Diagnosis and Discrimination of Gram-Positive and Gram-Negative Bacterial Pneumonia for Children Using Chest Radiography Images and Clinical Information

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