scholarly journals Antimicrobial Stewardship Opportunities in Patients with Bacteremia Not Identified by BioFire FilmArray

2019 ◽  
Vol 57 (5) ◽  
Author(s):  
P. Ny ◽  
A. Ozaki ◽  
J. Pallares ◽  
P. Nieberg ◽  
A. Wong-Beringer
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Blood Culture ◽  
Intensive Care Unit Admission ◽  
Clinical Characteristics ◽  
Length Of Hospital Stay ◽  
Blood Cultures ◽  
Rapid Diagnostics ◽  
Admission Data ◽  
Culture Identification

ABSTRACTA subset of bacteremia cases are caused by organisms not detected by a rapid-diagnostics platform, BioFire blood culture identification (BCID), with unknown clinical characteristics and outcomes. Patients with ≥1 positive blood culture over a 15-month period were grouped by negative (NB-PC) versus positive (PB-PC) BioFire BCID results and compared with respect to demographics, infection characteristics, antibiotic therapy, and outcomes (length of hospital stay [LOS] and in-hospital mortality). Six percent of 1,044 positive blood cultures were NB-PC. The overall mean age was 65 ± 22 years, 54% of the patients were male, and most were admitted from home; fewer NB-PC had diabetes (19% versus 31%,P= 0.0469), although the intensive care unit admission data were similar. Anaerobes were identified in 57% of the bacteremia cases from the NB-PC group by conventional methods:Bacteroidesspp. (30%),Clostridium(11%), andFusobacteriumspp. (8%). Final identification of the NB-PC pathogen was delayed by 2 days (P< 0.01) versus the PB-PC group. The sources of bacteremia were more frequently unknown for the NB-PC group (32% versus 11%,P< 0.01) and of pelvic origin (5% versus 0.1%,P< 0.01) compared to urine (31% versus 9%,P< 0.01) for the PB-PC patients. Fewer NB-PC patients received effective treatment before (68% versus 84%,P= 0.017) and after BCID results (82% versus 96%,P= 0.0048). The median LOS was similar (7 days), but more NB-PC patients died from infection (26% versus 8%,P< 0.01). Our findings affirm the need for the inclusion of anaerobes in BioFire BCID or other rapid diagnostic platforms to facilitate the prompt initiation of effective therapy for bacteremia.

Radiographically Confirmed Community-Acquired Pneumonia in Pediatric Patients Prior to Pneumococcal Vaccination in Nepal

2017 ◽  
Vol 13 (01) ◽  
pp. 057-062
Author(s):  
Dhruba Shrestha ◽  
Ganendra Raya ◽  
Amar Prajapati ◽  
Suruchi Dhaubhadel ◽  
Sushmita Puri ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Pleural Effusion ◽  
Intensive Care Unit Admission ◽  
Pneumococcal Vaccination ◽  
Community Acquired Pneumonia ◽  
Blood Cultures ◽  
Hospital Treatment ◽  
High Morbidity ◽  
Rural Nepal

Background The massive burden of pediatric pneumonia is associated with high morbidity and mortality, particularly in developing countries where immunization programs are absent or recently been implemented. The objective of this study was to describe the number of hospitalizations and outcomes of children aged 1 month to 10 years with community-acquired pneumonia (CAP) between January 1, 2014, and June 30, 2015, in semi-rural Nepal. Methods This retrospective study was undertaken prior to the implementation of the pneumococcal conjugate vaccination (PCV) program in Bhaktapur district of Nepal. Chart review of children with CAP, defined as the presence of symptoms, physical examination findings compatible with bacterial pneumonia together with lobar consolidation on chest X-ray (CXR), was performed. Data extracted included laboratory parameters and blood cultures on admission, antibiotic treatment, and length of hospital stay, as well as complications, such as death, intensive care unit admission, pleural effusion, and empyema. Outcomes assessed were clinical improvement accompanied by radiological improvement of consolidation. Results During the study period, 367 patients were admitted with pneumonia, of which, 74 (20%) had definite CXR evidence of lobar pneumonia. A total of 86.5% of the cases were children < 5 years of age. Admission blood cultures from all patients were negative. More than 80% of patients had white blood cell (WBC) counts >11,000/mm3 and ≥ 75% neutrophils. The highest number of cases presented between February and July. Forty-three of 45 patients responded to crystalline penicillin (CP), and 25/27 patients treated with cefotaxime also responded; the mean duration of treatment was 10 ± 2.3 days. There were no deaths. None of the patients developed empyema, sepsis, or pleural effusion or required intensive care unit admission. Conclusions CAP in pre-PCV semi-rural Nepal mostly affects male children < 5 years old and peaks between March and May. In-hospital treatment with CP or cefotaxime is effective.

scholarly journals Etiology and Impact of Coinfections in Children Hospitalized With Community-Acquired Pneumonia

2017 ◽  
Vol 218 (2) ◽  
pp. 179-188 ◽  
Author(s):  
Vikki G Nolan ◽  
Sandra R Arnold ◽  
Anna M Bramley ◽  
Krow Ampofo ◽  
Derek J Williams ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Length Of Stay ◽  
Intensive Care Unit Admission ◽  
Bacterial Infections ◽  
Clinical Characteristics ◽  
Community Acquired Pneumonia ◽  
Virus Infections ◽  
Oxygen Supplementation

Abstract Background Recognition that coinfections are common in children with community-acquired pneumonia (CAP) is increasing, but gaps remain in our understanding of their frequency and importance. Methods We analyzed data from 2219 children hospitalized with CAP and compared demographic and clinical characteristics and outcomes between groups with viruses alone, bacteria alone, or coinfections. We also assessed the frequency of selected pairings of codetected pathogens and their clinical characteristics. Results A total of 576 children (26%) had a coinfection. Children with only virus detected were younger, more likely to be black, and more likely to have comorbidities such as asthma, compared with children infected with typical bacteria alone. Children with virus-bacterium coinfections had a higher frequency of leukocytosis, consolidation on chest radiography, parapneumonic effusions, intensive care unit admission, and need for mechanical ventilation and an increased length of stay, compared with children infected with viruses alone. Virus-virus coinfections were generally comparable to single-virus infections, with the exception of the need for oxygen supplementation, which was higher during the first 24 hours of hospitalization in some virus-virus pairings. Conclusions Coinfections occurred in 26% of children hospitalized for CAP. Children with typical bacterial infections, alone or complicated by a viral infection, have worse outcomes than children infected with a virus alone.

scholarly journals Prognostic roles of time to positivity of blood cultures in patients with Escherichia coli bacteremia

2020 ◽  
Vol 148 ◽  
Author(s):  
Yufang Chen ◽  
Xun Huang ◽  
Anhua Wu ◽  
Xuan Lin ◽  
Pengcheng Zhou ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Intensive Care Unit ◽  
Septic Shock ◽  
Intensive Care ◽  
Intensive Care Unit Admission ◽  
Blood Cultures ◽  
University Teaching ◽  
Clinical Value ◽  
Prognostic Assessment ◽  
Time To Positivity

Abstract The time to positivity (TTP) of blood cultures has been considered a predictor of clinical outcomes for bacteremia. This retrospective study aimed to determine the clinical value of TTP for the prognostic assessment of patients with Escherichia coli bacteremia. A total of 167 adult patients with E.coli bacteremia identified over a 22-month period in a 3500-bed university teaching hospital in China were studied. The standard cut-off TTP was 11 h in the patient cohort. The septic shock occurred in 27.9% of patients with early TTP (⩽11 h) and in 7.1% of those with a prolonged TTP (>11 h) (P = 0.003). The mortality rate was significantly higher for patients in the early than in the late group (17.7% vs. 4.0%, P < 0.001). Multivariate analysis showed that an early TTP (OR 4.50, 95% CI 1.70–11.93), intensive care unit admission (OR 8.39, 95% CI 2.01–35.14) and neutropenia (OR 4.20, 95% CI 1.55–11.40) were independently associated with septic shock. Likewise, the independent risk factors for mortality of patients were an early TTP (OR 3.80, 95% CI 1.04–12.90), intensive care unit admission (OR 6.45; 95% CI 1.14–36.53), a Pittsburgh bacteremia score ⩾2 (OR 4.34, 95% CI 1.22–15.47) and a Charlson Comorbidity Index ⩾3 (OR 11.29, 95% CI 2.81–45.39). Overall, a TTP for blood cultures within 11 h appears to be associated with worse outcomes for patients with E.coli bacteremia.

scholarly journals 265. Blood culture results pre- and post- antimicrobial administration in the Medicine Intensive Care Unit: a retrospective study in South Bronx

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S131-S132
Author(s):  
Chia-Yu Chiu ◽  
Amara Sarwal ◽  
Addi Feinstein
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Blood Culture ◽  
Blood Cultures ◽  
Antibiotic Administration ◽  
Culture Result ◽  
Blood Culture Result ◽  
South Bronx ◽  
Coagulase Negative Staphylococci ◽  
Before And After

Abstract Background It is intuitive that obtaining blood cultures prior to administering antibiotics can increase the likelihood of a positive blood culture result. Surviving Sepsis Campaign Hour-1 bundle stipulates that obtaining a blood culture and administering antibiotics within 1 hour is a critical determinant of survival. However, the diagnostic sensitivity shortly after antibiotic administration remains unknown. In clinical practice, some health care providers delay antibiotic administration in order to first obtain a blood culture. Methods Adult patients (&gt; 18 years of age) admitted to the Medicine Intensive Care Unit in Lincoln Medical Center, located in South Bronx, New York City, from 09/2019 to 12/2019. Patients needed to have at least one blood culture obtained within 12 hours of admission and have received intravenous antibiotics during the admission to the Medicine Intensive Care Unit. Results Of 327 patients screened, 196 met enrolment criteria and 253 sets of blood cultures underwent analysis. Blood cultures grew bacteria in 21.8% of pre-antimicrobial group whereas 26.9% in post-antimicrobial group (p=0.37). 25.9% of patients received antibiotics within 1 hour before blood culture sampling, while 34.0% of patients received antibiotics &gt;1 hour prior to obtaining blood culture. Blood culture results positive for coagulase-negative staphylococci were more prevalent in the pre-antimicrobial group. Table 1. Patient Characteristics Table 2. Number of blood cultures obtained and blood culture result Table 3. Initial antimicrobial agent and 30-day mortality Conclusion In the sequence of blood culture and antibiotic administration, there is no 30-day survival difference in pre-antimicrobial group and post-antimicrobial group (p=0.15), as long as both received antibiotics within 12 hours of coming to the hospital. Coagulase-negative staphylococci were higher in the pre-antimicrobial group which may indicate that the health care provider hastily obtained the blood culture in a non-sterile manner. Antibiotic administration should not be delayed because of pending blood culture collection. In addition, given that more than 70% of patients were ultimately found to have negative blood cultures, it would be useful to develop practical tools to identify low-risk patients that can be treated without obtaining blood culture, as the blood culture would not be likely to provide diagnostic information. Figure 1: Hours Before and After IV Antibiotic Started Figure 2: Distribution of Blood Culture Before and After IV Antibiotics Disclosures All Authors: No reported disclosures

scholarly journals Letter to Editor: Clinical characteristics and prognostic factors for intensive care unit admission of patients with COVID-19: retrospective study using machine learning and natural language processing. (Preprint)

2021 ◽  
Author(s):  
Francisco Martos Pérez ◽  
Ricardo Gomez Huelgas ◽  
María Dolores Martín Escalante ◽  
José Manuel Casas Rojo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Prognostic Factors ◽  
Retrospective Study ◽  
Intensive Care Unit Admission ◽  
Language Processing ◽  
Clinical Characteristics ◽  
Microbiological Diagnosis

UNSTRUCTURED Letter to Editor. Comment to “Clinical characteristics and prognostic factors for intensive care unit admission of patients with COVID-19: retrospective study using machine learning and natural language processing” publicado por Izquierdo et al en Journal of Medical Internet Research Dear Sir, The article by Izquierdo et al published in the recent issue of Journal of Medical Internet Research (1) employed a combination of conventional and machine-learning tools to describe the clinical characteristics of patients with COVID-19 and the factors that predict intensive care unit (ICU) admission. We would like to make some comments about its design. The authors should have provided the proportion of patients with positive microbiological diagnosis. If the artificial intelligence software’s capacity for retrieving this information is limited in some way, this should be explained. The classification bias introduced by the lack of microbiological confirmation may have been significant, since the study includes patients from 1 January 2020. Although some undiagnosed cases have likely been present prior to the first declared case (1st march 2020)(2) in Castilla-La Mancha, it is improbable that there were many of them. ICU admissions are related to many factors not addressed in the study. The decision not to admit a patient to the ICU because of short life expectancy, low quality of life, or high burden of comorbidities may have had a great impact during the first wave of the COVID-19 pandemic, when a scarcity of ICU beds was manifested in some regions of Spain. The 6,1% ICU admission rate reported by the authors was 36% lower than the 8,3% reported in a national survey of 15111 patients from 150 hospitals in Spain(3). We could hypothesize that the patients included in the study had a milder disease. However, given the absence of microbiological diagnosis in an unknown percentage of patients, inclusion of a significant proportion of patients without a real COVID-19 diagnosis cannot be ruled out. These doubts could have been resolved if a microbiological diagnosis had been a requisite for inclusion. The mortality rate, the most robust and relevant endpoint, should also been reported and the factors related to it analysed. Artificial intelligence is having an increasing impact on the rate of health care information processing. However, minimization of selection and classification biases should be guaranteed in the design of investigations. In this case, this could have been achieved by including only microbiologically confirmed cases and prolonging the period of inclusion, since most of the COVID-19 cases emerged after the end date of the study inclusion period. These changes in the design would have allowed for a better evaluation of the performance of artificial intelligence techniques, making the results obtained in the sample closer to those of real population.   Bibliography 1. Izquierdo JL, Ancochea J; Savana COVID-19 Research Group, Soriano JB. Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing. J Med Internet Res. 2020;22(10):e21801. Published 2020 Oct 28. doi:10.2196/21801. PMID: 33090964 2. Europa Press (2020, march 1st). Un varón de 62 años ingresado en Guadalajara, primer caso positivo por coronavirus en C-LM. Retrieved 2020, January 8th. https://www.europapress.es/castilla-lamancha/noticia-varon-62-anos-ingresado-guadalajara-primer-caso-positivo-coronavirus-lm-20200301103741.html 3. Casas-Rojo JM, Antón-Santos JM, Millán-Núñez-Cortés J, et al. Clinical characteristics of patients hospitalized with COVID-19 in Spain: Results from the SEMI-COVID-19 Registry. Características clínicas de los pacientes hospitalizados con COVID-19 en España: resultados del Registro SEMI-COVID-19. Rev Clin Esp. 2020;220(8):480-494. doi:10.1016/j.rce.2020.07.003. PMID: 32762922

scholarly journals Clinical Characteristics and Outcomes of Patients With Diabetes Admitted for COVID-19 Treatment in Dubai: Single-Centre Cross-Sectional Study

10.2196/22471 ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. e22471
Author(s):  
Rahila Bhatti ◽  
Amar Hassan Khamis ◽  
Samara Khatib ◽  
Seemin Shiraz ◽  
Glenn Matfin
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Clinical Characteristics ◽  
Laboratory Data ◽  
Length Of Hospital Stay ◽  
C Reactive Protein ◽  
Cross Sectional ◽  
Reactive Protein ◽  
Patients With Diabetes ◽  
D Dimer

Background Recent studies have shown that diabetes is a major risk factor that contributes to the severity of COVID-19 and resulting mortality. Poor glycemic control is also associated with poor patient outcomes (eg, hospitalization and death). Objective This study aimed to describe the clinical characteristics and outcomes of patients with diabetes who were admitted to our hospital for COVID-19 treatment. Methods This cross-sectional, observational study comprised patients with diabetes admitted with COVID-19 to Mediclinic Parkview Hospital in Dubai, United Arab Emirates, from March 30 to June 7, 2020. We studied the differences among characteristics, length of hospital stay, diabetes status, comorbidities, treatments, and outcomes among these patients. Results Of the cohort patients, 25.1% (103/410) had coexistent diabetes or prediabetes. These patients represented 17 different ethnicities, with 59.2% (61/103) from Asian countries and 35% (36/103) from Arab countries. Mean patient age was 54 (SD 12.5) years, and 66.9% (69/103) of patients were male. Moreover, 85.4% (88/103) of patients were known to have diabetes prior to admission, and 14.6% (15/103) were newly diagnosed with either diabetes or prediabetes at admission. Most cohort patients had type 2 diabetes or prediabetes, and only 2.9% (3/103) of all patients had type 1 diabetes. Furthermore, 44.6% (46/103) of patients demonstrated evidence suggesting good glycemic control during the 4-12 weeks prior to admission, as defined arbitrarily by admission hemoglobin A1c level <7.5%, and 73.8% (76/103) of patients had other comorbidities, including hypertension, ischemic heart disease, and dyslipidemia. Laboratory data (mean and SD values) at admission for patients who needed ward-based care versus those who needed intensive care were as follows: fibrinogen, 462.8 (SD 125.1) mg/dL vs 660.0 (SD 187.6) mg/dL; D-dimer, 0.7 (SD 0.5) µg/mL vs 2.3 (SD 3.5) µg/mL; ferritin, 358.0 (SD 442.0) mg/dL vs 1762.4 (SD 2586.4) mg/dL; and C-reactive protein, 33.9 (SD 38.6) mg/L vs 137.0 (SD 111.7) mg/L. Laboratory data were all significantly higher for patients in the intensive care unit subcohort (P<.05). The average length of hospital stay was 14.55 days for all patients, with 28.2% (29/103) of patients requiring intensive care. In all, 4.9% (5/103) died during hospitalization—all of whom were in the intensive care unit. Conclusions Majority of patients with diabetes or prediabetes and COVID-19 had other notable comorbidities. Only 4 patients tested negative for COVID-19 RT-PCR but showed pathognomonic changes of COVID-19 radiologically. Laboratory analyses revealed distinct abnormal patterns of biomarkers that were associated with a poor prognosis: fibrinogen, D-dimer, ferritin, and C-reactive protein levels were all significantly higher at admission in patients who subsequently needed intensive care than in those who needed ward-based care. More studies with larger sample sizes are needed to compare data of COVID-19 patients admitted with and without diabetes within the UAE region.

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