Incidence of Port Site Infection After Laparoscopic Cholecystectomy: Our Experience at Hayatabad Medical Complex

OBJECTIVES This study aimed to assess the factors that affect post-laparoscopic cholecystectomies PSI and determine which characteristics can be changed to prevent PSI in a trial to maximize the benefits of laparoscopic surgery.METHODOLOGY The study included all patients who experienced port site infection following laparoscopic cholecystectomy. All patients received Inj Ceftriaxone 1gm pre-operatively & then twice a day postoperatively for 03 days. In all operations, the gallbladder is removed from the epigastric port without using a retrieval bag by skilled surgeons employing four-port methods and reusable equipment. Most patients had the sub-hepatic tube drain placed and were discharged the day after surgery.RESULTSAcute cholecystitis was the most common operative finding with port-site infection, i.e. 6(42.8%), second being empyema that was seen in 3(21.4%) patients, 2(14.3%) patients had bad adhesions, mucocele in 2(14.3%) patients and thick walled gall bladder with stones was found in 1(7.1%) patients respectively, indicating that the relationship between infection and acute cholecystitis is significant. Regarding the spills of bile, stones, or pus, 3(21.4%) patients had infections despite there being no spillage, while 11(78.6%) patients developed an infection while the spillage happened during their procedures. The p-value was 0.0001, meaning that the spillage might be considered a risk factor for the development of port site infection.CONCLUSIONThe spilling of bile, stones, or pus, the port of gallbladder removal, and acute cholecystitis are all strongly associated with port site infection. Given that Mycobacterium tuberculosis may be the source of chronic deep surgical site infections, more care should be exercised. The majority of PSIs are superficial and more prevalent in men

Benzodiazepine use in medical out-patient clinics: a study from a developing country

Objective: To estimate the prevalence of Benzodiazepine use in the outpatient setting of general medicine clinics at a single tertiary care centre. Methods: The prospective prevalence study was conducted in the outpatient setting of Internal Medicine Clinics at Aga Khan University Hospital, Karachi, from November to December 2009. All subjects were interviewed after informed consent and variables were recorded on a specially-designed proforma. Apart from basic demographics and comorbid conditions, duration, frequency and route of benzodiazepine use, as well as the reason and who initiated it was noted. Chi-square test and t test was applied to see the association of socio demographic or clinical factors with the use of benzodiazepine. Results: Of the 355 patients, 129 (36.33%) reported using the drug. The majority (n=86; 24.2%) were taking it on a daily basis. The highest numbers of patients using the drug were suffering from cardiovascular problems, 32 (25%) followed by 22 (17%) from endocrinology. Diazepam equivalent dose was around 7.04+4, with a inter-quartile range of 3-96 weeks. Alprazolam (9%) was the most frequently prescribed Benzodiazepine. CONCLUSION: Benzodiazepine use is alarmingly high in the outpatient clinics of General Internal Medicine Department. There is no implementation of law to prevent its hazardous sale. In this regard all concerned should work collectively for awareness and irrational drug sale and use

A Prediction Model Optimization Critiques through Centroid Clustering by Reducing the Sample Size, Integrating Statistical and Machine Learning Techniques for Wheat Productivity

Machine learning algorithms are rapidly deploying and have made manifold breakthroughs in various fields. The optimization of algorithms got abundant attention of researchers being a core component for deploying the machine learning model (MLM) abled to learn the parameters in significant ways for the given data. Modeling crop productivity through innumerable agronomical constraints has become a crucial task for evolving sustainable agricultural policies. The cross-sectional datasets of 26430 (D1) crop-cut experiments are taken by 2nd-stage area frame sampling, collected from crop reporting service. This research is taken as follows: firstly three more effective numerical optimized datasets are generated (D1, D2, and D3) from D1 by taking the centroid points of features which decrease the sample size; secondly MLM is integrated with the traditional statistical models (TSMs) for multiple linear regression (MLR), and thirdly decision tree regression (DTR) and random forest regression (RFR) are deployed to get the optimized models able to predict the wheat productivity well with 75% datasets to train and 25% to test the model using the evaluation metrics (R2, RMSE), information criterion (AIC) with weights (AICW), evidence ration (E.R), and decompositions of prediction error. The MLR outperformed for MLM than TSM. The performance capability of MLM and TSM got upswing for generated datasets. RFR got optimized and superperformed for D1, D2, D3, and D4. This study demonstrated strong evidences for deploying MLM for prediction of wheat productivity as an alternative of traditional statistical modeling

Evaluation of Shortest Paths in Road Network

Optimization is a key factor in almost all the topics of operations research / management science and economics.The road networks can be optimized within different constraints like time, distance, cost and traffic running onthe roads.This study is based on optimization of real road network by means of distances. Two main objectives arepursued in this research: 1) road distances among different routes are composed in detail; 2) two standardalgorithms (Dijkstra and Floyd-Warshall algoritms) are applied to optimize/minimize these distances for bothsingle-source and all-pairs shortest path problems

Evaluation of shortest paths in road network of Sindh-Pakistan

Optimization is a key factor in almost all the topics of operations research / management science and economics. The road networks can be optimized within different constraints like time, distance, cost and traffic running on the roads. This study is based on optimization of real road network by means of distances. Two main objectives are pursued in this research: 1) road distances among different routes are composed in detail; 2) two standard algorithms (Dijkstra and Floyd-Warshall algoritms) are applied to optimize/minimize these distances for both single-source and all-pairs shortest path problems

Development of some useful generators to obtain partially neighbor balanced designs

Neighbor balanced designs are robust to neighbor effects, therefore, these designs are used to balance out the neighbor effects. If a large number of experimental material is required for combinatorial neighbor balance then partially neighbor balanced designs should be recommended. In this study, some useful generators are developed to obtain the partially neighbor balanced designs in linear blocks of sizes 3–7. Keywords: Linear block, Neighbor effects, Neighbor balanced designs, Partially neighbor balanced design

Forecasting the population growth and wheat crop production in Pakistan with non-linear growth and ARIMA models

Food security as a major social concern and a global threat, requires better policy decisions based on empirical studies. This work presents a comparative statistical analysis of different methods to forecast wheat area, productivity, production, and population growth rate in Pakistan. Time series data from 1950 to 2020 were analyzed using various methods such as ARIMA, the compound growth exponential regression model (CGREM), Cuddy Della Valle instability index (CDVI), and decomposition analysis. The results show that CGREM performs better than other models. Periodic compound growth rates indicate that wheat area and yield decrease by about 67.0% and 40.0%, while the population decreases by 31.7%. For the period 2001-2020, the compound growth reaches the level of 0.60% for wheat area, 1.21% for yield, while it is high for the population and amounts to 2.22%. The overall compound growth rate for wheat area and yield (about 1.207%, 2.326%) is lower compared to the population (about 2.839%). The paper presents forecasts for wheat area, yield, and population in Pakistan will rise: 12.7%, 25.5%, 31.8% in 2030 and 43%, 97.8%, and 129% in 2050. The results of this study provide empirical evidence for the necessity of policy decisions addressing the problem of food security in Pakistan

Recent progress in layered double hydroxides (LDH)-containing hybrids as adsorbents for water remediation

<div>With rapidly growing industrial development worldwide, the need for a new class of nanoparticles and techniques for treating wastewater remains a major concern to protect the environment. Layered double hydroxides and particularly LDH-containing hybrids are emerging as potential nano-sized adsorbents for water treatment. Recent studies have demonstrated LDH-containing hybrids as promising multifunctional materials for potential utilization in various applications such as, photo-catalysis, energy storage, nanocomposites and water purification. This article reviews the recent applications of LDH-containing hybrids as adsorbents for water</div><div>remediation. The maximum adsorption capacities of various toxic heavy metals and dyes on different LDH hybrids were reported as 483 mg/g for Pb2+, 95 mg/g for Cd2+, 181 mg/g for Cu2+, 649 mg/g for Cr6+, 180 mg/g As5+, 813 mg/g for Hg2+, 450 for Ag+, 277 mg/g for U6+, 1062 mg/g for methyl orange, 185 mg/g for methylene blue, and 1250 mg/g for Congo red, which is comparatively higher than other commercial adsorbents. This review discusses the adsorption performance of manifold LDH-containing hybrids for treating various pollutants such as heavy metals and dyes. The mechanisms of interaction of LDH-containing hybrids with pollutants and the influence of key adsorption parameters such as pH, contact time, adsorbent dose and</div><div>temperature have been comprehensively discussed. Moreover, the regeneration potential and reuse of spent</div><div>LDH-containing hybrids and its toxicity effects have also been reviewed. </div

Incidence and Predictors of Outcome in the Treatment of In-Stent Restenosis with Drug-Eluting Balloons

In-stent restenosis (ISR) continues to pose a significant clinical challange after percutaneous coronary intervention (PCI), despite the use of drug-eluting stents (DES). Drug-eluting balloons (DEBs) have surfaced as a promising therapeutic solution for ISR, offering a non-stent-based approach to administer antiproliferative drugs directly to the vessel wall. This study aims to evaluate the incidence of major adverse cardiac events (MACE) and identify clinical and procedural predictors of outcomes in patients undergoing DEB treatment for ISR. Methods: This was a retrospective cohort study conducted at Pakistan Institute of Medical science, Islamabad, during study period from July 2022 to July 2023. All patinets with age ?18 years, angiographically confirmed restensosis were included. Results: A total of 264 patients were included in the study majority male (73.86%), with a mean age of 61.42± 9.74 years. Procedural success of 99.24%  was achieved, and    of patients within the 12-month. The cumulative incidence of MACE was 8%  at 12 months with diabetes mellitus (HR: 1.9, 95% CI: 1.1-3.2, p&lt;0.01), stent length &gt;20 mm (HR: 1.7, 95% CI: 1.0-2.8, p&lt;0.05), and suboptimal stent expansion (HR: 2.6, 95% CI: 1.7-4.8, p&lt;0.01). Moreover, age more than 65 years and multiple vessel disease were significant predictors of MACE. KM analysis revealed significantly higher ISR and lower MACE-free survival in patients with DM and longer stent (p&lt;0.01 and p&lt;0.05, respectively).   Conclusion In conclusion, the use of DEBs in the treatment of ISR shows a good procedural success rate along with a controllable restenosis recurrence rate. Significant predictors of unfavorable outcomes, such as diabetes mellitus, stent length, and poor stent expansion, were identified Keywords: coronary artery disease, In-stent restenosis drug-eluting balloons, percutaneous coronary intervention.