scholarly journals 198. Clinical Prediction of Bacteremia and the Need for Early Antibiotic Therapy in Solid Tumor Cancer Patients

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S103-S104
Author(s):  
Jonathan M Hyak ◽  
Mayar Al Mohajer ◽  
Daniel Musher ◽  
Benjamin Musher
Keyword(s):  
Cancer Patients ◽  
Solid Tumor ◽  
Cardiopulmonary Arrest ◽  
Tertiary Care ◽  
Organ Transplant ◽  
Vital Signs ◽  
Care Hospital ◽  
Robust Model ◽  
Binomial Regression ◽  
Sirs Criteria

Abstract Background Cancer patients (pts) frequently receive empiric antibiotics without clear indication. This retrospective study investigated the relationship between the systemic inflammatory response syndrome (SIRS), early antibiotic (Anb) use, and bacteremia in solid tumor pts presenting to the emergency department (ED). Methods We extracted data from the electronic medical records of adults with solid tumors admitted to a tertiary care hospital through the ED for any reason over a 2 year period. Pts with neutropenic fever, organ transplant, trauma, or cardiopulmonary arrest were excluded. Rates of SIRS and bacteremia among pts receiving early Anb (eAnb, within 8 hours of admission) were compared to all others using χ 2. Binomial regression and receiver operator curves assessed predictors of bacteremia. Results Of 3580 eligible pts, 1344 pts were SIRS positive (≥ 2 criteria) and 2236 were SIRS negative; 501 (37%) and 493 (22%), respectively, received eAnb (p< 0.001). eAnb use increased with additional SIRS criteria (Fig 1). Of SIRS positive pts, 860 (64%) had BCs drawn within 48 hrs of presentation, of which 19% were positive. Of SIRS negative pts, 826 (37%) had cultures drawn within 48 hrs of presentation, of which 14% were positive (19% vs 14%, p=0.004). Of pts who had BCs drawn, the proportion of positive BCs among those who received eAnb and those who did not was identical (16% in each group; p=1). Of 276 pts ultimately proven to have bacteremia within 48 hrs, only 59% were SIRS positive, and only 49% received eAnb in the ED. By regression, only two SIRS components predicted bacteremia, fever (OR 1.8 ± 0.39, p=0.01) and tachycardia (1.4 ± 0.22, p=0.03), and SIRS criteria as a whole were poorly predictive of bacteremia (AUC 0.57, Table 1). A more robust model, which included additional labs and vital signs, was only marginally better (AUC 0.61, Table 2). Figure 1: Proportion of patients receiving early antibiotics by SIRS score Table 1: SIRS as a predictor of bacteremia Table 2: Best predictive model of bacteremia Conclusion Clinicians still use SIRS criteria to determine the need for eAnb. However, SIRS criteria are poor predictors of bacteremia in solid tumor pts, who frequently manifest them due to complications of cancer or cancer-directed therapy rather than infection. Furthermore, patients who are SIRS negative may be bacteremic. More reliable models are needed to guide judicious use of Anb in the solid tumor population. Disclosures All Authors: No reported disclosures

Clinical prediction of bacteremia and early antibiotics therapy in patients with solid tumors

2021 ◽  
pp. 1-7
Author(s):  
Jonathan M. Hyak ◽  
Mayar Al Mohajer ◽  
Daniel M. Musher ◽  
Benjamin L. Musher
Keyword(s):  
Solid Tumors ◽  
Solid Tumor ◽  
Cardiopulmonary Arrest ◽  
Tertiary Care ◽  
Organ Transplant ◽  
Antibiotic Use ◽  
Care Hospital ◽  
Tumor Patients ◽  
Binomial Regression ◽  
Sirs Criteria

Abstract Objective: To investigate the relationship between the systemic inflammatory response syndrome (SIRS), early antibiotic use, and bacteremia in solid-tumor patients. Design, setting, and participants: We conducted a retrospective observational study of adults with solid tumors admitted to a tertiary-care hospital through the emergency department over a 2-year period. Patients with neutropenic fever, organ transplant, trauma, or cardiopulmonary arrest were excluded. Methods: Rates of SIRS, bacteremia, and early antibiotics (initiation within 8 hours of presentation) were compared using the χ2 and Student t tests. Binomial regression and receiver operator curves were analyzed to assess predictors of bacteremia and early antibiotics. Results: Early antibiotics were administered in 507 (37%) of 1,344 SIRS-positive cases and 492 (22%) of 2,236 SIRS-negative cases (P < .0001). Of SIRS-positive cases, 70% had blood cultures drawn within 48 hours and 19% were positive; among SIRS negative cases, 35% had cultures and 13% were positive (19% vs 13%; P = .003). Bacteremic cases were more often SIRS positive than nonbacteremic cases (60% vs 50%; P =.003), but they received early antibiotics at similar rates (50% vs 49%, P = .72). Three SIRS components predicted early antibiotics: temperature (OR, 1.7; 95% CI, 1.31–2.29; P = .0001), tachycardia (OR, 1.4; 95% CI, 1.10–1.69; P < .0001), and white blood-cell count (OR, 1.8; 95% CI, 1.56–2.14; P < .0001). Only temperature (OR, 1.6; 95% CI, 1.09–2.41; P = .01) and tachycardia (OR, 1.5; 95% CI, 1.09–2.06; P = .01) predicted bacteremia. SIRS criteria as a composite were poorly predictive of bacteremia (AUC, 0.57). Conclusions: SIRS criteria are frequently used to determine the need for early antibiotics, but they are poor predictors of bacteremia in solid-tumor patients. More reliable models are needed to guide judicious use of antibiotics in this population.

scholarly journals 181. Limited Effectiveness of an EMR Alert-Based Antibiotic Timeout Procedure in Solid Tumor Cancer Patients

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S97-S98
Author(s):  
Jonathan M Hyak ◽  
Mayar Al Mohajer ◽  
Benjamin Musher
Keyword(s):  
Solid Tumor ◽  
Cardiopulmonary Arrest ◽  
Tertiary Care ◽  
Organ Transplant ◽  
Active Role ◽  
Care Hospital ◽  
Post Intervention ◽  
Limited Effectiveness ◽  
Days Of Therapy ◽  
Before And After

Abstract Background Computer-based antibiotic time-outs, in which providers receive automated electronic medical record (EMR) alerts regarding continuation of inpatient antibiotics (Anb), are common stewardship initiatives. We assessed the efficacy of such an intervention in oncology patients (pts), who frequently receive Anb when hospitalized. Methods An EMR alert triggered 48 hours after starting vancomycin (vanc), cefepime (cef), piperacillin-tazobactam (pip-tazo), meropenem (mero), and fluoroquinolones (flq) was initiated in a tertiary care hospital in November 2018. To assess the efficacy of the intervention in adults with solid tumor malignancies, demographic, vital sign, laboratory, and treatment data were extracted retrospectively from the EMR. Pts with neutropenic fever, organ transplant, trauma, and cardiopulmonary arrest were excluded. We compared length of therapy [LOT; days of therapy per 1000 patient-days (DOT/1000 pd)] via t-test and incidence rate ratio (IRR) for 3- and 12-month periods preceding and following the intervention. November 2018 was excluded as a washout period. Results The groups did not differ by age, sex, length of stay, or rate of bacteremia (Table 1). Comparing the 3 months before and after the intervention, neither mean LOT (2.9 ± 0.20 vs 2.6 ± 0.14 DOT/1000 pd, p=0.31) nor rate of Anb use changed (IRR 0.97, p=0.32). However, when considering only the Anb targeted by the intervention, cef usage was 1.4 times higher post- intervention (p=0.002), while use of other Anb was similar (Table 2). Comparing 12 months before to 12 months after the intervention, mean LOT was longer after (0.74 ± 0.018) than before (0.68 ± 0.020 DOT/1000 pd; p=0.03), and Anb use increased (IRR 1.3, p&lt; 0.0001). Specifically, mero (IRR 1.8, p&lt; 0.0001) and cef (1.6, p&lt; 0.0001) were used more frequently after the intervention while none were used less (table 2). Table 1: Study Group Characteristics Table 2: Antibiotic Use Three Months Before and After, and Twelve Months Before and After, the Intervention Conclusion Despite wide adoption and efficacy in other populations, an EMR-based Anb time-out did not mitigate the continuation of Anb among inpatients with solid tumors. The intervention may require additional measures, such as an active role for pharmacy, to be effective. However, qualitative studies may also be required to understand why providers are hesitant to limit Anb use in this population. Disclosures All Authors: No reported disclosures

scholarly journals Prevalence and clinical correlation of hepatitis E virus antibody in the patients’ serum samples from a tertiary care hospital in Thailand during 2015–2018

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Atiporn Boonyai ◽  
Anchalee Thongput ◽  
Thidarat Sisaeng ◽  
Parisut Phumchan ◽  
Navin Horthongkham ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Tertiary Care ◽  
Laboratory Data ◽  
Organ Transplant ◽  
Hospital Setting ◽  
Antibody Detection ◽  
Enzyme Linked Immunosorbent Assay ◽  
Care Hospital ◽  
Serum Samples ◽  
Igm Antibodies

Abstract Background Prevalence and incidence of hepatitis caused by HEV infection are usually higher in developing countries. This study demonstrated the HEV seroprevalence and incidence of HEV infection in patients with clinical hepatitis in a tertiary hospital in Thailand. Methods A laboratory-based cross-sectional study was conducted using 1106 serum samples from patients suspected of HEV infection sent to the Serology laboratory, Siriraj Hospital, for detecting HEV antibodies during 2015–2018. Prevalence of anti-HEV IgG and IgM antibodies in general patients, including organ transplant recipients and pregnant women in a hospital setting, were determined using indirect enzyme-linked immunosorbent assay (ELISA) kits. Comparison of laboratory data between groups with different HEV serological statuses was performed. Results HEV IgG antibodies were detected in 40.82% of 904 serum samples, while HEV IgM antibodies were detected in 11.75% of 1081 serum samples. Similar IgG and IgM antibody detection rates were found in pregnant women. Interestingly, anti-HEV IgM antibodies were detected in 38.5% of patients who underwent organ transplantation. Patients who tested positive for anti-HEV IgM antibodies had higher alanine aminotransferase levels than those who had not. In contrast, patients who tested positive for anti-HEV IgG had more elevated levels of total bilirubin than those who tested negative. Conclusions HEV seroprevalence and incidence in patients with clinical hepatitis were relatively high in the Thai population, including the pregnancy and organ transplant subgroups. The results potentially benefit the clinicians in decision-making to investigate HEV antibodies and facilitating proper management for patients.

ALKALINE PHOSPHATASE AS A PROGNOSTIC MARKER IN CANCER BREAST PATIENTS IN A TERTIARY CARE HOSPITAL

2021 ◽  
pp. 14-16
Author(s):  
Asha Premlata Omega Oraon ◽  
Bela Rose Ekka
Keyword(s):  
Alkaline Phosphatase ◽  
Cancer Patients ◽  
Prognostic Marker ◽  
Prognostic Markers ◽  
Tertiary Care Hospital ◽  
Serum Alkaline Phosphatase ◽  
Tertiary Care ◽  
Control Group ◽  
Care Hospital ◽  
Cancer Breast

OBJECTIVE: To estimate the value of Alkaline Phosphatase in cancer breast patients in a tertiary care hospital. MATERIAL AND METHODS: The study was conducted to estimate the value of Serum Alkaline Phosphatase in 50 cancer breast patients and 50 normal patients of same age as a control group. RESULTS: The level of serum Alkaline Phosphatase was signicantly increased (p<0.05)in cancer patients compared to the control group. CONCLUSION: There is an increase in serum Alkaline Phosphatase in cancer patients compared to the control group and can be a prognostic markers for the progress of the disease.

To Determine the Prevalence of Obesity in Breast Cancer Patients

2021 ◽  
Keyword(s):  
Breast Cancer ◽  
Body Mass Index ◽  
Cancer Patients ◽  
Body Mass ◽  
Tertiary Care ◽  
Overweight And Obesity ◽  
World Health ◽  
Care Hospital ◽  
Breast Cancer Patients ◽  
Prevalence Of Obesity

Background: Breast Cancer is one of the leading causes of death worldwide. Pakistan alone has the highest rate of Breast Cancer than any other Asian country as approximately 90000 new cases are diagnosed every year out of which 40000 dies. Obesity is also a critical public health problem growing with every passing year in Pakistan and worldwide. Research studies are being conducted worldwide regarding the relation between the two problems. Objective: The objective of this study is to determine the prevalence of obesity in breast cancer patients in a tertiary care hospital in Karachi, Pakistan. Methods: BMI is used as a screening tool for overweight and obesity. According to World Health Organization, a body mass index (BMI) over 25 is considered overweight, and over 30 is obese. A retrospective analysis of 262 patients diagnosed with Breast Cancer during 2019 and 2020 was performed. Patients’ hospital records in Oncology were reviewed. The weight in kilograms and height in centimeters of patients were reviewed. Their BMI was calculated and recorded using the SPSS system. Results: The median BMI was 28.25 kg/m2 with an interquartile range of 25.15 - 31.99 kg/m2. Nearly 80% of the study participants had body mass index higher than normal levels (n=203, 77.5%) and out of them approximately half were overweight (n=104, 51.2%) and the remaining were obese (n=99, 48.7%). Conclusion: We conclude from our study that body mass index is positively correlated with breast cancer occurrence and thus the proportion of females having BMI >= 25 was significantly higher among patients.

scholarly journals Pathways to care and diagnostic delay among cervical cancer patients attending a tertiary care hospital in Puducherry: a cross-sectional study

2020 ◽  
Vol 7 (6) ◽  
pp. 2298
Author(s):  
Roshina Sunny ◽  
Sitanshu Sekhar Kar ◽  
Dasari Papa ◽  
Sujiv Akkilagunta ◽  
Jeby Jose Olickal
Keyword(s):  
Cervical Cancer ◽  
Cancer Patients ◽  
Tertiary Care ◽  
Diagnostic Delay ◽  
Cross Sectional Study ◽  
Cancer Center ◽  
Care Hospital ◽  
Sectional Study ◽  
Cross Sectional ◽  
Care Facilities

Background: The high mortality among cervical cancer patients in India can be attributed to presentation at advanced stages. The varied and lengthy pathway taken up to diagnosis could be a major reason for advanced stage at presentation. Hence, we aimed to describe the care pathways and diagnostic delay among cervical cancer patients.Methods: A hospital-based cross-sectional study was conducted among 101 cervical cancer patients attending a cancer clinic at a Regional Cancer Center. The histo-pathologically confirmed cases of cervical cancer, who registered in July to October 2018 were approached. Data were collected through personal interviews using a semi-structured questionnaire. Descriptive statistics were used to describe the number of providers visited and diagnostic delay.Results: The median (range) number of providers visited by the patients up to diagnosis was 2 (1-5). As the first point of care, 14% of participants approached sub-center or primary care facilities, 27% approached secondary care facilities, 49% participants approached tertiary care facilities and 11% came directly to a regional cancer center. Diagnosis was made only in 24% of participants at secondary and tertiary care levels. The median (IQR) number of days to get diagnosed was 66 (30-130) days and three fourth of the patients had a diagnostic delay.Conclusions: The diagnostic delay was higher among patients who consulted multiple providers. Implementing a protocol to be followed at all three levels of health care delivery system may enhance the early diagnosis. 

scholarly journals Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury

2020 ◽  
Vol 15 (11) ◽  
pp. 1557-1565 ◽  
Author(s):  
Kumardeep Chaudhary ◽  
Akhil Vaid ◽  
Áine Duffy ◽  
Ishan Paranjpe ◽  
Suraj Jaladanki ◽  
...  
Keyword(s):  
Intensive Care ◽  
Deep Learning ◽  
Medical Information ◽  
Tertiary Care ◽  
Vital Signs ◽  
Kidney Injury ◽  
The United States ◽  
Care Hospital ◽  
Electronic Health Record Data ◽  
Electronic Health

Background and objectivesSepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records.Design, setting, participants, & measurementsWe used the Medical Information Mart for Intensive Care III database, which consists of electronic health record data from intensive care units in a tertiary care hospital in the United States. We included patients ≥18 years with sepsis who developed AKI within 48 hours of intensive care unit admission. We then used deep learning to utilize all available vital signs, laboratory measurements, and comorbidities to identify subphenotypes. Outcomes were mortality 28 days after AKI and dialysis requirement.ResultsWe identified 4001 patients with sepsis-associated AKI. We utilized 2546 combined features for K-means clustering, identifying three subphenotypes. Subphenotype 1 had 1443 patients, and subphenotype 2 had 1898 patients, whereas subphenotype 3 had 660 patients. Subphenotype 1 had the lowest proportion of liver disease and lowest Simplified Acute Physiology Score II scores compared with subphenotypes 2 and 3. The proportions of patients with CKD were similar between subphenotypes 1 and 3 (15%) but highest in subphenotype 2 (21%). Subphenotype 1 had lower median bilirubin levels, aspartate aminotransferase, and alanine aminotransferase compared with subphenotypes 2 and 3. Patients in subphenotype 1 also had lower median lactate, lactate dehydrogenase, and white blood cell count than patients in subphenotypes 2 and 3. Subphenotype 1 also had lower creatinine and BUN than subphenotypes 2 and 3. Dialysis requirement was lowest in subphenotype 1 (4% versus 7% [subphenotype 2] versus 26% [subphenotype 3]). The mortality 28 days after AKI was lowest in subphenotype 1 (23% versus 35% [subphenotype 2] versus 49% [subphenotype 3]). After adjustment, the adjusted odds ratio for mortality for subphenotype 3, with subphenotype 1 as a reference, was 1.9 (95% confidence interval, 1.5 to 2.4).ConclusionsUtilizing routinely collected laboratory variables, vital signs, and comorbidities, we were able to identify three distinct subphenotypes of sepsis-associated AKI with differing outcomes.

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