Visualisasi Informasi Data Perguruan Tinggi Dengan Data Warehouse Dan Dashboard System

University leaders have the responsibility to monitor all activities and make continuous measurements on the performance and quality of higher education which leads to ensure the achievement of the goals set. All this to get some of the information required, university leaders still have to do the data collection scattered beberpa information systems, either manually. It can slow down the decision making process for people who are at the manager level and above can not monitor the performance and quality of high pergutuan any time.Making college visualization of data information by using data warehouse and dashboard of the system can help university leaders in monitoring or monitoring the performance of all units in college he leads and perform measurements continuously on the performance and quality of higher education lead

High ethionamide resistance in Mycobacterium tuberculosis strains isolated in Kenya

Background: Increasing development of tuberculosis (TB) resistance to the currently available drugs including second-line anti-TB drugs that are being used for treatment of Multi-Drug Resistant TB (MDR-TB) patients has frustrated efforts to control TB worldwide. Ethionamide (Eth) is one of the drugs used in the regimen for treatment of these patients. Objective: To determine level of Ethionamide resistance among second-line anti-tuberculosis drugs in Mycobacterium tuberculosis (MTB) strains isolated in Kenya. Design: A retrospective lab-based study involving archived strains from previous studies carried out at the Centre for Respiratory Diseases Research (CRDR), Kenya Medical Research Institute (KEMRI) from 2002 to 2007. Setting: Centre for Respiratory Diseases Research (CRDR), Kenya Medical Research Institute (KEMRI). Methods: A total of 216 MTB strains with pre-determined first-line drug susceptibility testing (DST) results were used including 78 first-line resistant to individual and combined drugs, and 138 susceptible to streptomycin, rifampicin, isoniazid and ethambutol. The strains were subjected to DST to ethionamide among other second-line. Results: Thirty two [32/216 (14.8%)] strains showed resistance to second-line drugs. Resistance to Eth was the highest [18/32 (56.3%)] including co-resistance with isoniazid [8/18 (44.4%)]. Nine [9/18 (50%)] strains were fully resistant and 9 [9/18 (50%)] were intermediate resistant to Eth. Conclusion: Unexplainable high levels of Eth resistance is a cause for concern. This will impact negatively on the outcome of management of MDR-TB especially in Kenya where the use of this drug is almost mandatory. Close monitoring of Eth before initiating individual patient management may be necessary. Keywords: Ethionamide, Resistant, MDR-TB

Environmental determinants of access to shared sanitation in informal settlements: a cross-sectional study in Abidjan and Nairobi

BACKGROUND: Universal access to basic sanitation remains a global challenge, particularly in low- and middle-income countries. Efforts are underway to improve access to sanitation in informal settlements, often through shared facilities. However, access to these facilities and their potential health gains-notably, the prevention of diarrheal diseases-may be hampered by contextual aspects related to the physical environment. This study explored associations between the built environment and perceived safety to access toilets, and associations between the latter and diarrheal infections. METHODS: A cross-sectional study was carried out between July 2021 and February 2022, including 1714 households in two informal settlements in Abidjan (Cote d'Ivoire) and two in Nairobi (Kenya). We employed adjusted odds ratios (aORs) obtained from multiple logistic regressions (MLRs) to test whether the location of the most frequently used toilet was associated with a perceived lack of safety to use the facility at any time, and whether this perceived insecurity was associated with a higher risk of diarrhea. The MLRs included several exposure and control variables, being stratified by city and age groups. We employed bivariate logistic regressions to test whether the perceived insecurity was associated with settlement morphology indicators derived from the built environment. RESULTS: Using a toilet outside the premises was associated with a perceived insecurity both in Abidjan [aOR = 3.14, 95% confidence interval (CI): 1.13-8.70] and in Nairobi (aOR = 57.97, 95% CI: 35.93-93.53). Perceived insecurity to access toilets was associated with diarrheal infections in the general population (aOR = 1.90, 95% CI: 1.29-2.79 in Abidjan, aOR = 1.69, 95% CI: 1.22-2.34 in Nairobi), but not in children below the age of 5 years. Several settlement morphology features were associated with perceived insecurity, namely, buildings' compactness, the proportion of occupied land, and angular deviation between neighboring structures. CONCLUSIONS: Toilet location was a critical determinant of perceived security, and hence, must be adequately addressed when building new facilities. The sole availability of facilities may be insufficient to prevent diarrheal infections. People must also be safe to use them. Further attention should be directed toward how the built environment affects safety

The role and performance of chest X-ray for the diagnosis of tuberculosis: A cost-effectiveness analysis in Nairobi, Kenya

BACKGROUND: The objective of this study was to establish 1) the performance of chest X-ray (CXR) in all suspects of tuberculosis (TB), as well as smear-negative TB suspects and 2) to compare the cost-effectiveness of the routine diagnostic pathway using Ziehl-Neelsen (ZN) sputum microscopy followed by CXR if case of negative sputum result (ZN followed by CXR) with an alternative pathway using CXR as a screening tool (CXR followed by ZN). METHODS: From TB suspects attending a chest clinic in Nairobi, Kenya, three sputum specimens were examined for ZN and culture (Lowenstein Jensen). Culture was used as gold standard. From each suspect a CXR was made using a four point scoring system: i: no pathology, ii: pathology not consistent for TB, iii: pathology consistent for TB and iv: pathology highly consistent for TB. The combined score i + ii was labeled as "no TB" and the combined score iii + iv was labeled as "TB". Films were re-read by a reference radiologist. HIV test was performed on those who consented. Laboratory and CXR costs were used to compare for cost-effectiveness. RESULTS: Of the 1,389 suspects enrolled, for 998 (72%) data on smear, culture and CXR was complete. 714 films were re-read, showing a 89% agreement (kappa value = 0.75 s.e.0.037) for the combined scores "TB" or "no-TB". The sensitivity/specificity of the CXR score "TB" among smear-negative suspects was 80%/67%. Using chest CXR as a screening tool in all suspects, sensitivity/specificity of the score "any pathology" was 92%, respectively 63%. The cost per correctly diagnosed case was for the routine process $8.72, compared to$9.27 using CXR as screening tool. When costs of treatment were included, CXR followed by ZN became more cost-effective. CONCLUSION: The diagnostic pathway ZN followed by CXR was more cost-effective as compared to CXR followed by ZN. When cost of treatment was also considered CXR followed by ZN became more cost-effective. The low specificity of chest X-ray remains a subject of concern. Depending whether CXR was performed on all suspects or on smear-negative suspects only, 22%–45% of patients labeled as "TB" had a negative culture. The introduction of a well-defined scoring system, clinical conferences and a system of CXR quality control can contribute to improved diagnostic performance

Household carbon monoxide (CO) concentrations in a large African city: An unquantified public health burden?

Carbon monoxide (CO) is a poisonous gas produced by incomplete combustion of carbon-based fuels that is linked to mortality and morbidity. Household air pollution from burning fuels on poorly ventilated stoves can lead to high concentrations of CO in homes. There are few datasets available on household concentrations of CO in urban areas of sub-Saharan African countries. CO was measured every minute over 24 h in a sample of homes in Nairobi, Kenya. Data on household characteristics were gathered by questionnaire. Metrics of exposure were summarised and analysis of temporal changes in concentration was performed. Continuous 24-h data were available from 138 homes. The mean (SD), median (IQR) and maximum 24-h CO concentration was 4.9 (6.4), 2.8 (1.0–6.3) and 44 ppm, respectively. 50% of homes had detectable CO concentrations for 847 min (14h07m) or longer during the 24-h period, and 9% of homes would have activated a CO-alarm operating to European specifications. An association between a metric of total CO exposure and self-reported exposure to vapours >15 h per week was identified, however this were not statistically significant after adjustment for the multiple comparisons performed. Mean concentrations were broadly similar in homes from a more affluent area and an informal settlement. A model of typical exposure suggests that cooking is likely to be responsible for approximately 60% of the CO exposure of Nairobi schoolchildren. Household CO concentrations are substantial in Nairobi, Kenya, despite most homes using gas or liquid fuels. Concentrations tend to be highest during the evening, probably associated with periods of cooking. Household air pollution from cooking is the main source of CO exposure of Nairobi schoolchildren. The public health impacts of long-term CO exposure in cities in sub-Saharan Africa may be considerable and should be studied further

Household carbon monoxide (CO) concentrations in a large African city: An unquantified public health burden?

Carbon monoxide (CO) is a poisonous gas produced by incomplete combustion of carbon-based fuels that is linked to mortality and morbidity. Household air pollution from burning fuels on poorly ventilated stoves can lead to high concentrations of CO in homes. There are few datasets available on household concentrations of CO in urban areas of sub-Saharan African countries. CO was measured every minute over 24 h in a sample of homes in Nairobi, Kenya. Data on household characteristics were gathered by questionnaire. Metrics of exposure were summarised and analysis of temporal changes in concentration was performed. Continuous 24-h data were available from 138 homes. The mean (SD), median (IQR) and maximum 24-h CO concentration was 4.9 (6.4), 2.8 (1.0–6.3) and 44 ppm, respectively. 50% of homes had detectable CO concentrations for 847 min (14h07m) or longer during the 24-h period, and 9% of homes would have activated a CO-alarm operating to European specifications. An association between a metric of total CO exposure and self-reported exposure to vapours >15 h per week was identified, however this were not statistically significant after adjustment for the multiple comparisons performed. Mean concentrations were broadly similar in homes from a more affluent area and an informal settlement. A model of typical exposure suggests that cooking is likely to be responsible for approximately 60% of the CO exposure of Nairobi schoolchildren. Household CO concentrations are substantial in Nairobi, Kenya, despite most homes using gas or liquid fuels. Concentrations tend to be highest during the evening, probably associated with periods of cooking. Household air pollution from cooking is the main source of CO exposure of Nairobi schoolchildren. The public health impacts of long-term CO exposure in cities in sub-Saharan Africa may be considerable and should be studied further.Additional authors: K Mortimer, A Ndombi, C Pearson, M Twigg, S Wes

Household carbon monoxide (CO) concentrations in a large African city: An unquantified public health burden?

Carbon monoxide (CO) is a poisonous gas produced by incomplete combustion of carbon-based fuels that is linked to mortality and morbidity. Household air pollution from burning fuels on poorly ventilated stoves can lead to high concentrations of CO in homes. There are few datasets available on household concentrations of CO in urban areas of sub-Saharan African countries. CO was measured every minute over 24 h in a sample of homes in Nairobi, Kenya. Data on household characteristics were gathered by questionnaire. Metrics of exposure were summarised and analysis of temporal changes in concentration was performed. Continuous 24-h data were available from 138 homes. The mean (SD), median (IQR) and maximum 24-h CO concentration was 4.9 (6.4), 2.8 (1.0–6.3) and 44 ppm, respectively. 50% of homes had detectable CO concentrations for 847 min (14h07m) or longer during the 24-h period, and 9% of homes would have activated a CO-alarm operating to European specifications. An association between a metric of total CO exposure and self-reported exposure to vapours >15 h per week was identified, however this were not statistically significant after adjustment for the multiple comparisons performed. Mean concentrations were broadly similar in homes from a more affluent area and an informal settlement. A model of typical exposure suggests that cooking is likely to be responsible for approximately 60% of the CO exposure of Nairobi schoolchildren. Household CO concentrations are substantial in Nairobi, Kenya, despite most homes using gas or liquid fuels. Concentrations tend to be highest during the evening, probably associated with periods of cooking. Household air pollution from cooking is the main source of CO exposure of Nairobi schoolchildren. The public health impacts of long-term CO exposure in cities in sub-Saharan Africa may be considerable and should be studied further

Household carbon monoxide (CO) concentrations in a large African city: an unquantified public health burden?

Carbon monoxide (CO) is a poisonous gas produced by incomplete combustion of carbon-based fuels that is linked to mortality and morbidity. Household air pollution from burning fuels on poorly ventilated stoves can lead to high concentrations of CO in homes. There are few datasets available on household concentrations of CO in urban areas of sub-Saharan African countries. CO was measured every minute over 24 h in a sample of homes in Nairobi, Kenya. Data on household characteristics were gathered by questionnaire. Metrics of exposure were summarised and analysis of temporal changes in concentration was performed. Continuous 24-h data were available from 138 homes. The mean (SD), median (IQR) and maximum 24-h CO concentration was 4.9 (6.4), 2.8 (1.0-6.3) and 44 ppm, respectively. 50% of homes had detectable CO concentrations for 847 min (14h07m) or longer during the 24-h period, and 9% of homes would have activated a CO-alarm operating to European specifications. An association between a metric of total CO exposure and self-reported exposure to vapours >15 h per week was identified, however this were not statistically significant after adjustment for the multiple comparisons performed. Mean concentrations were broadly similar in homes from a more affluent area and an informal settlement. A model of typical exposure suggests that cooking is likely to be responsible for approximately 60% of the CO exposure of Nairobi schoolchildren. Household CO concentrations are substantial in Nairobi, Kenya, despite most homes using gas or liquid fuels. Concentrations tend to be highest during the evening, probably associated with periods of cooking. Household air pollution from cooking is the main source of CO exposure of Nairobi schoolchildren. The public health impacts of long-term CO exposure in cities in sub-Saharan Africa may be considerable and should be studied further

Household carbon monoxide (CO) concentrations in a large African city: an unquantified public health burden?

Carbon monoxide (CO) is a poisonous gas produced by incomplete combustion of carbon-based fuels that is linked to mortality and morbidity. Household air pollution from burning fuels on poorly ventilated stoves can lead to high concentrations of CO in homes. There are few datasets available on household concentrations of CO in urban areas of sub-Saharan African countries. CO was measured every minute over 24 hours in a sample of homes in Nairobi, Kenya. Data on household characteristics were gathered by questionnaire. Metrics of exposure were summarised and analysis of temporal changes in concentration was performed. Continuous 24-hour data were available from 138 homes. The mean (SD), median (IQR) and maximum 24-hour CO concentration was 4.9 (6.4), 2.8 (1.0-6.3) and 44ppm, respectively. 50% of homes had detectable CO concentrations for 847 minutes (14h07m) or longer during the 24-hour period, and 9% of homes would have activated a CO-alarm operating to European specifications. An association between a metric of total CO exposure and self-reported exposure to vapours >15 h per week was identified, however this were not statistically significant after adjustment for the multiple comparisons performed. Mean concentrations were broadly similar in homes from a more affluent area and an informal settlement. A model of typical exposure suggests that cooking is likely to be responsible for approximately 60% of the CO exposure of Nairobi schoolchildren. Household CO concentrations are substantial in Nairobi, Kenya, despite most homes using gas or liquid fuels. Concentrations tend to be highest during the evening, probably associated with periods of cooking. Household air pollution from cooking is the main source of CO exposure of Nairobi schoolchildren. The public health impacts of long-term CO exposure in cities in sub-Saharan Africa may be considerable and should be studied further

Non-Hodgkin lymphoma response evaluation with MRI texture classification

<p>Abstract</p> <p>Background</p> <p>To show magnetic resonance imaging (MRI) texture appearance change in non-Hodgkin lymphoma (NHL) during treatment with response controlled by quantitative volume analysis.</p> <p>Methods</p> <p>A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests.</p> <p>Results</p> <p>NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images.</p> <p>Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue.</p> <p>Conclusion</p> <p>Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.</p