Conversion from Laparoscopic to Open Cholecystectomy

Introductions: With the advent of newer technology, the era of open surgery for gall bladder diseases has been preferably taken over by laparoscopic cholecystectomy. However, certain cases still require conversion to open surgery. In this review we aim to analyze the reason for conversion.Methods: This retrospective study was conducted at Patan Hospital, Patan Acdemy of Health Sciences, Nepal. All patients who underwent laparoscopic cholecystectomy from February 2009 to July 2012 were included in the study. File numbers of all the patients were obtained from operation room register. The patient files were analyzed for age, sex, duration of symptoms, liver function tests, ultrasound findings and the description in operation note for reason for conversion.Results: The age ranged from 12 to 81 years with mean age of patients 32.76 years and male to female ratio 1:2.9. The mean operating time was 65 minutes and average post operative hospital stay was 1.61 days. Out of 305 patients, 34 (11.14%) required open conversion. Factors esponsible for open conversion were dense fibrosis at Calots in 11 (3.6%), adhesions due to previous abdominal surgery in 6 (1.9%), uncontrollable bleeding in 5 (1.6%), bile duct injury in 4 (1.3%) cholecystoenteric fistula in 3 (0.9%), Mirizzi’s syndrome 2(0.6%).Conclusions: Adhesions at the calot’s triangle was the common reason for conversion from laparoscopic to open cholecystectomy.Keywords: adhesions, conversion, gallstone, laparoscopic cholecystectom

Can REDD+ social safeguards reach the ‘right’ people? Lessons from Madagascar

AbstractThere is extensive debate about the potential impact of the climate mechanism REDD+ on the welfare of forest-dwelling people. To provide emission reductions, REDD+ must slow the rate of deforestation and forest degradation: such a change will tend to result in local opportunity cost to farmers at the forest frontier. Social safeguard processes to mitigate negative impacts of REDD+ are being developed and can learn from existing safeguard procedures such as those implemented by the World Bank. Madagascar has a number of REDD+ pilot projects with World Bank support including the Corridor Ankeniheny-Zahamena (CAZ). Nearly two thousand households around the corridor have been identified as ‘project affected persons’ (PAPs) and given compensation. We compare households identified as project affected persons with those not identified. We found households with more socio-political power locally, those with greater food security, and those that are more accessible were more likely to be identified as eligible for compensation while many people likely to be negatively impacted by the REDD+ project did not receive compensation. We identify three issues which make it difficult for a social safeguard assessment to effectively target the households for compensation: (a) poor information on location of communities and challenging access means that information does not reach remote households; (b) reluctance of people dependant on shifting agriculture to reveal this due to government sanctions; and (c) reliance by safeguard assessors on non-representative local institutions. We suggest that in cases where the majority of households are likely to bear costs and identification of affected households is challenging, the optimal, and principled, strategy may be blanket compensation offered to all the households in affected communities; avoiding the dead weight costs of ineffective safeguard assessments. The Paris Agreement in December 2015 recognised REDD+ as a key policy instrument for climate change mitigation and explicitly recognised the need to respect human rights in all climate actions. However, safeguards will be prone to failure unless those entitled to compensation are aware of their rights and enabled to seek redress where safeguards fail. This research shows that existing safeguard commitments are not always being fulfilled and those implementing social safeguards in REDD+ should not continue with business as usual

Prediction of daily global solar radiation using different empirical models on the basis of meteorological parameters at Trans Himalaya Region, Nepal

Global Solar Radiation (GSR) is the cleanest and freely available energy resource on the earth.  GSR  was measured for six years (2010 -2015) at the horizontal surface using calibrated first-class CMP6 pyranometer at Kathmandu (Lat. 27.70o N, Long. 85.5oE and Alt. 1350m). This paper explains the daily, monthly, and seasonal variations of GSR and also compares with sunshine hour, ambient temperature, relative humidity, and precipitation to GSR. The annual average global solar radiation is about 4.16 kWh/m2/day which is a significant amount to promote solar active and passive energy technologies at the Trans-Himalaya region. In this study, the meteorological parameters are utilized in the regression technique for four different empirical models and finally, the empirical constants are found. Thus obtained coefficients are utilized to predict the GSR using meteorological parameters for the years to come. In addition, the predicted GSR is found to be closer to the measured value of GSR. The values are justified by using statistical tools such as coefficient of determination (R2), root mean square error (RMSE), mean percentage error (MPE), and mean bias error (MBE). Finally, the values of R2, RMSE, MPE, and MBE are found to be 0.792, 1.405, -1.014, and 0.011, respectively for the model (D), which are based on sunshine hour, temperature and relative humidity. In this model, the empirical constants, a = 0.155, b = 0.134, c = 0.014 and d = 0.0007 are determined which can be utilized at the similar geographical locations of Nepal. BIBECHANA 18 (1) (2021) 159-16

Prediction of daily global solar radiation using different empirical models on the basis of meteorological parameters at Trans Himalaya Region, Nepal

Global Solar Radiation (GSR) is the cleanest and freely available energy resource on the earth.  GSR  was measured for six years (2010 -2015) at the horizontal surface using calibrated first-class CMP6 pyranometer at Kathmandu (Lat. 27.70o N, Long. 85.5oE and Alt. 1350m). This paper explains the daily, monthly, and seasonal variations of GSR and also compares with sunshine hour, ambient temperature, relative humidity, and precipitation to GSR. The annual average global solar radiation is about 4.16 kWh/m2/day which is a significant amount to promote solar active and passive energy technologies at the Trans-Himalaya region. In this study, the meteorological parameters are utilized in the regression technique for four different empirical models and finally, the empirical constants are found. Thus obtained coefficients are utilized to predict the GSR using meteorological parameters for the years to come. In addition, the predicted GSR is found to be closer to the measured value of GSR. The values are justified by using statistical tools such as coefficient of determination (R2), root mean square error (RMSE), mean percentage error (MPE), and mean bias error (MBE). Finally, the values of R2, RMSE, MPE, and MBE are found to be 0.792, 1.405, -1.014, and 0.011, respectively for the model (D), which are based on sunshine hour, temperature and relative humidity. In this model, the empirical constants, a = 0.155, b = 0.134, c = 0.014 and d = 0.0007 are determined which can be utilized at the similar geographical locations of Nepal. BIBECHANA 18 (1) (2021) 159-16

Empirical model for estimation of global solar radiation at lowland region Biratnagar using satellite data

This study proposes to find the regression coefficient of the modified Angstrom type model for the estimation of global solar radiation (GSR) in lowland Biratnagar (Lat. 26.5º N, Long. 87.3º E and Alt. 72m) using relative sunshine duration and satellite data of GSR. Using the regression technique, the empirical constants 0.29 and 0.56 are found in the modified Angstrom model. Furthermore, the Modified Angstrom model along with other linear models such as Glover and McCulloch model, Page model, Rietveld model, and Turton's model are statistically assessed to evaluate the significance of models. Statistical tests like MPE, MBE, RMSE, and CC reveal that all these models are statistically significant. These findings can be utilized for other locations with a high confidence level at the similar climatic locations of Nepal. BIBECHANA 18 (1) (2021) 193-20

Empirical model for estimation of global solar radiation at lowland region Biratnagar using satellite data

This study proposes to find the regression coefficient of the modified Angstrom type model for the estimation of global solar radiation (GSR) in lowland Biratnagar (Lat. 26.5º N, Long. 87.3º E and Alt. 72m) using relative sunshine duration and satellite data of GSR. Using the regression technique, the empirical constants 0.29 and 0.56 are found in the modified Angstrom model. Furthermore, the Modified Angstrom model along with other linear models such as Glover and McCulloch model, Page model, Rietveld model, and Turton's model are statistically assessed to evaluate the significance of models. Statistical tests like MPE, MBE, RMSE, and CC reveal that all these models are statistically significant. These findings can be utilized for other locations with a high confidence level at the similar climatic locations of Nepal. BIBECHANA 18 (1) (2021) 193-20

Analysis of Aerosol Optical Depth and Angstrom Exponents over an AERONET site at Pokhara, Nepal

The monthly variability of Aerosol Optical Depth at 0.50 μm (AOD0.50) and Ångström exponents (AE) based on spectral AODs over an Aerosol Robotic Network (AERONET) site Pokhara are analyzed by using aerosol data of the year 2017. The AOD0.50 are characterized by low average values (0.21± 0.12) in monsoon, and highest values in pre-monsoon (0.67± 0.14) followed by winter (0.46± 0.28) and post-monsoon (0.33±.02) with an overall mean of 0.43 ± 0.02. The average AE obtained by using AODs at 0.44 μm and 0.87 μm is 1.20± 0.04 in pre-monsoon, 1.37± 0.05 in monsoon, 1.41±.01 in post-monsoon, and 1.37± 0.07 in winter with an annual average value of 1.35 ± 0.08. These overall variations of AE indicate that the majority of aerosol loading during the study period was a mixture of fine and coarse mode aerosols and the influence of anthropogenic aerosols. The monthly average AOD suggests low aerosol loading in the months of the monsoon season (June to September) than other months of pre-monsoon season (March to May) and post-monsoon season (October and November). BIBECHANA 18 (1) (2021) 118-12

Analysis of Aerosol Optical Depth and Angstrom Exponents over an AERONET site at Pokhara, Nepal

The monthly variability of Aerosol Optical Depth at 0.50 μm (AOD0.50) and Ångström exponents (AE) based on spectral AODs over an Aerosol Robotic Network (AERONET) site Pokhara are analyzed by using aerosol data of the year 2017. The AOD0.50 are characterized by low average values (0.21± 0.12) in monsoon, and highest values in pre-monsoon (0.67± 0.14) followed by winter (0.46± 0.28) and post-monsoon (0.33±.02) with an overall mean of 0.43 ± 0.02. The average AE obtained by using AODs at 0.44 μm and 0.87 μm is 1.20± 0.04 in pre-monsoon, 1.37± 0.05 in monsoon, 1.41±.01 in post-monsoon, and 1.37± 0.07 in winter with an annual average value of 1.35 ± 0.08. These overall variations of AE indicate that the majority of aerosol loading during the study period was a mixture of fine and coarse mode aerosols and the influence of anthropogenic aerosols. The monthly average AOD suggests low aerosol loading in the months of the monsoon season (June to September) than other months of pre-monsoon season (March to May) and post-monsoon season (October and November). BIBECHANA 18 (1) (2021) 118-12

Prevalence and risk factors associated with chronic kidney disease in Nepal: evidence from a nationally representative population-based cross-sectional study.

OBJECTIVE: This study aimed to determine population-based prevalence of chronic kidney disease (CKD) and its associated factors in Nepal. STUDY DESIGN: The study was a nationwide population-based cross-sectional study. SETTING AND PARTICIPANTS: Cross-sectional survey conducted in a nationally representative sample of 12 109 Nepalese adult from 2016 to 2018 on selected chronic non-communicable diseases was examined. Multistage cluster sampling with a mix of probability proportionate to size and systematic random sampling was used for the selection of individuals aged 20 years and above. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome in this study was population-based prevalence of CKD in Nepal. A participant was considered to have CKD if the urine albumin-to-creatinine ratio was greater than or equal to 30 mg/g and/or estimated glomerular filtration rate is less than 60 mL/min/1.73 m2 at baseline and in follow-up using modification of diet in renal disease study equations. The secondary outcome measure was factors associated with CKD in Nepal. The covariate adjusted association of risk factors and CKD was calculated using multivariable binary logistic regression. RESULTS: The overall prevalence of CKD in Nepal was 6.0% (95% CI 5.5 to 6.6). Factors independently associated with CKD included older age (adjusted OR (AOR) 2.6, 95% CI 1.9 to 3.6), Dalit caste (AOR 1.6, 95% CI 1.1 to 2.3), hypertension (AOR 2.4, 95% CI 2.0 to 3.0), diabetes mellitus (AOR 3.2, 95% CI 2.5 to 4.1), raised total cholesterol (AOR 1.3, 95% CI 1.0 to 1.6) and increased waist-to-hip ratio (AOR 1.6, 95% CI 1.2 to 2.3). CONCLUSION: This nationally representative study shows that the prevalence of CKD in the adult population of Nepal is substantial, and it is independently associated with several cardiometabolic traits. These findings warrant longitudinal studies to identify the causes of CKD in Nepal and effective strategies to prevent it

The Reality of Antimicrobial Resistance and Antibiotic Usage Data in Asia: The CAPTURA Experience.

Antimicrobial resistance (AMR), particularly in low- and middle-income countries, is threatening to undermine advances in health and development. Scarce technical and human resources in these countries limit the collection of quality AMR data for evidence-based decision-making. The CAPTURA consortium, funded by the Fleming Fund, was implemented across 7 countries in the South and Southeast Asian region. The program focused on collating historical bacteriological data for qualitative and quantitative analyses. The team gathered standard data on the quality of laboratories and clinics and the quality and quantity of retrospective historical AMR data. In addition, retrospective data on antimicrobial use and consumption were analyzed. While standard protocols guided the project, a tailored approach for stakeholder engagement was implemented to work with countries and secure data-sharing agreements. The program also had to navigate the challenges of the COVID-19 pandemic, making some innovative adaptations to overcome logistical barriers. From 2018 through 2022, a large body of data was collected that was used to base a series of recommended key measures for strengthening the development of standardized national surveillance programs and to support alignment with international efforts