Dataset Information

Assessment of patient dose and optimization levels in chest and abdomen CR examinations at referral hospitals in Tanzania.

ABSTRACT: The aim of this study was to evaluate the radiation doses to patient during chest and abdomen CR examinations, and assess the related level of optimization at five referral hospitals in Tanzania. The international code of practice for dosimetry in diagnostic radiology was applied to determine the entrance surface air kerma (ESAK) to patients. The level of optimization was assessed from low-contrast objects scores of phantom images at different exposures. The results show that mean ESAK varied from 0.16 to 0.37 mGy for chest PA and from 2 to 6 mGy for abdomen AP. Assuming similar patient and phantom attenuations, the optimization performed at all facilities was consistent with phantom evaluations in terms of tube potential settings in use. However, all facilities seemed to operate at higher tube load values above 5 mAs for chest examination, which can lead to unnecessary patient doses. Inadequate initial training on CR technology explains in large proportion the inappropriate use of exposure parameters.

SUBMITTER: Masoud AO

PROVIDER: S-EPMC5690155 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Assessment of patient dose and optimization levels in chest and abdomen CR examinations at referral hospitals in Tanzania.

Masoud A O AO Muhogora W E WE Msaki P K PK

Journal of applied clinical medical physics 20150908 5

The aim of this study was to evaluate the radiation doses to patient during chest and abdomen CR examinations, and assess the related level of optimization at five referral hospitals in Tanzania. The international code of practice for dosimetry in diagnostic radiology was applied to determine the entrance surface air kerma (ESAK) to patients. The level of optimization was assessed from low-contrast objects scores of phantom images at different exposures. The results show that mean ESAK varied fr ...[more]

PMID: 26699324

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Project description:ObjectiveTo delineate the prevalence and factors associated with antimicrobial use across six referral hospitals in Tanzania using WHO point prevalence survey (PPS) methodology to inform hospital-specific antimicrobial stewardship programmes.DesignCross-sectional analytical study.SettingSix referral hospitals in Tanzania.ParticipantsPatients irrespective of age and gender (n=948) admitted in the six referral hospital wards before 8:00 hours on each day of the survey were included in December 2019. Using the WHO PPS methodology, data on hospitals, wards, patients, antibiotics, and indications for antibiotics were collected.Outcome measuresWe analysed the prevalence of antibiotic use by referral hospital, ward, indication and patient characteristics as the main outcomes. We also described adherence to the Tanzania Standard Treatment Guidelines (STG) and WHO's AWaRe categorisation of antibiotics.ResultsApproximately 62.3% of inpatients were prescribed antibiotics, predominantly from the Access group of antibiotics (ceftriaxone, metronidazole or ampicillin-cloxacillin). The overall adherence of antibiotic prescriptions to the Tanzania STG was high (84.0%), with the exception of Sekou Toure Regional Referral Hospital (68.0%) and Maweni Regional Referral Hospital (57.8%). The most common indication for antibiotic prescriptions was community-acquired infections (39.8%). Children less than 2 years of age (OR 1.73, 95% CI 1.02 to 2.92, p=0.039); admission to surgical wards (OR 4.90, 95% CI 2.87 to 8.36, p <0.001); and admission to paediatric wards (OR 3.93, 95% CI 2.16 to 7.15, p <0.001) were associated with increased odds of antibiotic use. Only 2 of 591 patients were prescribed antibiotics based on culture and antimicrobial susceptibility testing results.ConclusionsEmpirical use of antibiotics is common, and the Access group of antibiotics is predominantly prescribed in children less than 2 years and patients admitted to surgical and paediatric wards. Lack of utilisation of antimicrobial susceptibility testing services in these hospitals requires urgent interventions. Routine monitoring of antibiotic use is recommended to be part of antibiotic stewardship programmes in Tanzania.

Project description:PurposeOrgan autosegmentation efforts to date have largely been focused on adult populations, due to limited availability of pediatric training data. Pediatric patients may present additional challenges for organ segmentation. This paper describes a dataset of 359 pediatric chest-abdomen-pelvis and abdomen-pelvis Computed Tomography (CT) images with expert contours of up to 29 anatomical organ structures to aid in the evaluation and development of autosegmentation algorithms for pediatric CT imaging.Acquisition and validation methodsThe dataset collection consists of axial CT images in Digital Imaging and Communications in Medicine (DICOM) format of 180 male and 179 female pediatric chest-abdomen-pelvis or abdomen-pelvis exams acquired from one of three CT scanners at Children's Wisconsin. The datasets represent random pediatric cases based upon routine clinical indications. Subjects ranged in age from 5 days to 16 years, with a mean age of 7 years. The CT acquisition, contrast, and reconstruction protocols varied across the scanner models and patients, with specifications available in the DICOM headers. Expert contours were manually labeled for up to 29 organ structures per subject. Not all contours are available for all subjects, due to limited field of view or unreliable contouring due to high noise.Data format and usage notesThe data are available on The Cancer Imaging Archive (TCIA_ (https://www.cancerimagingarchive.net/) under the collection Pediatric-CT-SEG. The axial CT image slices for each subject are available in DICOM format. The expert contours are stored in a single DICOM RTSTRUCT file for each subject. The contour names are listed in Table 2.Potential applicationsThis dataset will enable the evaluation and development of organ autosegmentation algorithms for pediatric populations, which exhibit variations in organ shape and size across age. Automated organ segmentation from CT images has numerous applications including radiation therapy, diagnostic tasks, surgical planning, and patient-specific organ dose estimation.

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Project description:IntroductionHealth insurance coverage is critical for persons living with chronic conditions such as heart failure. Lack of health insurance may affect the ability to access regular healthcare appointments, pay for medication refills which can result in frequent hospitalization that is associated with poor clinical outcomes. In scarce resource locations such as sub-Saharan Africa, where uptake of health insurance is still suboptimal, the effect of health insurance on chronic conditions such as heart failure is poorly understood. The objective of this study was to assess the association of health insurance on the severity of heart failure for patients attending outpatient clinics at tertiary hospitals in Mwanza, Tanzania.MethodsAs part of a larger cohort study, patients with heart failure were recruited from Bugando Medical Center (BMC) and Sekou Toure Regional Hospital (STRH) in Mwanza City, Tanzania. Heart failure was based on Framingham criteria and the severity was determined by New York Heart Association (NYHA) classification. Descriptive analysis and multivariable logistic regression were used to describe the study participants and to assess the association between health insurance status and the severity of heart failure at baseline.Results418 patients were enrolled, and majority were female (n = 264, 63%), small scale farmers (n = 278, 66.5%) and were from Mwanza City (n = 299, 71.5%). More than two-thirds of patients did not have health insurance (n = 295, 70.6%) and the majority were in the NYHA I and II classification (n = 267, 64.7%). There was no association between health insurance status and the severity of heart (aOR 0.97; 95% CI 0.84-1.60). Being male, small-scale businessperson and those seen at STRH was associated with higher odds of being in NYHA Class III/IV (aOR = 1.97; 95% CI: 1.21-3.17), (aOR = 2.61; 95% CI: 1.27-5.34) and (aOR 1.91 95% CI: 1.17-3.13) respectively. Having secondary and college education was associated with lower odds of being in Class III/IV (0.42; 95% CI: 0.18-0.98) and (aOR = 0.23 95% CI: 0.06-0.86) respectively.ConclusionIn this study, only a third of the patients had health insurance. Health insurance was not associated with the severity of heart failure. Since heart failure is a chronic condition patients who do not have health insurance may incur out of pocket expenses, future research should focus on the effect of out-of-pocket expenditures on clinical outcomes.

Dataset Information

Assessment of patient dose and optimization levels in chest and abdomen CR examinations at referral hospitals in Tanzania.

Publications

Assessment of patient dose and optimization levels in chest and abdomen CR examinations at referral hospitals in Tanzania.

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