Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

: The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS® v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 ± 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 ± 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 ± 4.9 and 7.8 ± 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 ± 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity > 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)—giving infants only breast-milk for the first 6 months of life—is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization’s Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030

Forensic Accounting - A Game Changing Approach for Holistic Corporate Sector Development in India

Forensic accounting is the prominent instrument in the field of accounting area to tackle the rampant situation of financial fraud. Forensic accounting is a specific branch of accounting. It involves the application of special skills such as accounting, auditing procedures, finance, quantitative methods, research, and investigations in accounting activities. With the rapid growth of technology in India after globalization, the trend of accounting is also changing as per the demand of stakeholders due to facing these complex natures of fraud. Forensic accounting is one of the transcendent examples in the area of accounting. It is capable to find out all kinds of fraud; if we use it attentively. The techniques of forensic accounting are also developing with the need of time. Modern technologies are more powerful in comparison to conventional technologies. In the dynamic cyber world, the complex natures of frauds are creating a need for research in the forensic accounting area. Since independence, the Incremental growth of voluminous financial scams is a black spot in the Indian economy. Moreover, the list of challenges to better practices of forensic accounting in India is too extensive. There are few agencies in India, which are dedicated to the mission of combating fraud for example- SFIO, FEMA, RBI, CBI (Economic Office Wing) deals with big financial scams, Central Vigilance Commission deals with corruption. In view of India, the better practices of forensic accounting should be observed by stakeholders carefully to boost economic growth.&#x0D; The present study discusses the conceptual framework of forensic accounting, the implementation &amp; progress of forensic accounting, the authorities involved, and suggestions for better implementation of forensic accounting from the Indian perspective.</jats:p

Parametric Optimization of WEDM Characteristics on Inconel 825 using Desirability Research

The present research focuses on the optimization of wire-cut electric discharge machining (WEDM) parameters. In this study, RSM based multi-response desirability method is used to optimize the WEDM characteristics for single and multiple responses. Input parameters of WEDM viz. pulse-on time, pulse-off time, spark gap voltage, wire tension, peak current, wire feed and performance was measured in terms of material removal rate (MRR) and surface roughness (SR). WEDM is a nontraditional method uses the spark erosion principle to produce the intricate shape and profiles of difficult-to-cut material. Inconel 825 is increasing in demand in the aerospace industry for more heat resistant and tough material. Because of its robust nature, it is difficult to be machined with conventional methods. WEDM is best alternate to overcome this problem. It has been observed that at Ton 111 MU, Toff 35 MU, SV 46V, IP 140A, WT 9 MU and WF 6 m/min, the values obtained for MRR and SR are 32.015mm2/min and 2.528 μm respectively.</jats:p

Data Pre Processing for Machine Learning Models using Python Libraries

Data pre-processing is the process of transforming the raw data into useful dataset. Data pre-processing is one of the most important phase of any machine learning model because the quality and efficiency of any machine learning model directly depends upon the data-set, if we skip this step and design a model with data sets containing missing values then the model we have designed will not be that efficient and will be inconsistent model. This paper describes the methodology for pre-processing the data in seven sequence of steps using python powerful libraries which are open source machine learning libraries that support both supervised and unsupervised learning like pandas is a high level data manipulation tool, scikit learn which provides various tools for model fitting, data pre-processing, model selection and many other utilities. These steps include dealing with missing value, categorical values, importing data sets etc. This analysis helps in cleaning and transforming the datasets which future applied to any learning model and produce a efficient machine learning model.</jats:p

Chemical Synthesis of Cobalt Nanoparticles and Determination of its Minimal Inhibitory Concentrations and Minimal Bactericidal Concentrations against S. aureus and E. coli

The indiscriminate usage of antibiotics in the past few years is one of the main reasons behind increased incidences of antimicrobial resistance. The development of potent antibacterial agents to combat this problem is the need of present era. In view of this, in present study, cobalt (Co) nanoparticles were chemically synthesized by standard method. The synthesized Co nanoparticles were tested against the S. aureus and E. coli bacterial strains, and the minimal inhibitory concentrations (MIC) and minimal bactericidal concentrations (MBC) values of Co nanoparticles were determined against these bacterial strains on the day of Co nanoparticles synthesis and after their storage for 30 and 60 days. The Co nanoparticles showed antibacterial actions against S. aureus and E. coli bacterial strains. The MIC values of fresh chemically synthesized Co nanoparticles in this study for S. aureus and E. coli were 140.0 μg/ml and 100.0 μg/ml, respectively. The MBC values of these nanoparticles for S. aureus and E. coli were 260.0 μg/ml and 220.0 μg/ml, respectively. The MIC and MBC values of Co nanoparticles increased on storage of its suspensions for 30 as well as 60 days. It might be considered as potent antibacterial candidate in future after some additional investigations.</jats:p