The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

An Introduction to Computer Forensics

The diversity in cyber crime is vast and it is a challenge to solve the cases related to data theft, misuse of intellectual property and email spam. Computer forensics is the method of investigating crimes by using computers and software to uncover electronic evidence which were involved in crimes such as information theft, abuse, drugs, software piracy and phishing. Three prominent definitions for computer forensics are: "Computer forensics is the collection of techniques and tools used to find evidence on a computer that can be used to its user's disadvantage. [1]" "Computer forensics is the process of methodically examining computer media (hard disks, diskettes, tapes etc.) for evidence. [2]" "Computer forensics involves the preservation, identification, extraction, documentation and interpretation of computer media for evidentiary and/or root cause analysis. [3]" Computer forensics according to the Digital Forensic Research Workshop is "The use of scientifically derived and proven methods toward the preservation, collection, validation, identification, analysis, interpretation, documentation and presentation of digital evidence derived from digital sources for the purpose of facilitating or furthering the reconstruction of events found to be criminal, or helping to anticipate unauthorized actions shown to be disruptive to planned operations. [4]" Collectively, computer forensics is the process of collecting digital evidence and methodically analyzing the preserved evidence in order to trace computer misuse activities.School of Computing, Communication and Electronic

Evolutionary Perspectives on Obesity and Associated Metabolic Conditions, and a Test of the Ancestral Diet Hypothesis

Obesity, type 2 diabetes and other associated metabolic diseases have become blatant epidemic diseases over the last few decades. All of these diseases have a negative impact on human well-being and function at all stages of the life-cycle. Does evolutionary theory provide any utility towards understanding these conditions? Could these dysfunctional conditions be studied as any other functional traits—like the beaks of Darwin’s finches? How has evolutionary theory been invoked to explain the etiology and prevalence of these diseases? Could one use an evolutionary framework to organize the various evolutionary hypothesis of obesity and associated metabolic conditions? These are some of the questions this dissertation has attempted to answer. This dissertation provides a framework to study any trait from an evolutionary perspective; whether biological or cultural. This framework is then utilized to organize existing evolutionary hypotheses of obesity. Many of these invoke natural selection, some invoke constraints-based processes, some highlight the importance of developmental and maternal environment and one of the hypothesis points towards the importance of genetic drift. Majority of the hypotheses see obesity as a consequence of an evolutionary mismatch between humans and the drastically novel environment they inhabit in comparison to their ancestors. Five of these hypotheses were reviewed to unravel how they explain the mechanism, development, function, and phylogeny of obesity—thrifty genotype, thrifty phenotype, protein leverage, microbiome and the Ancestral diet hypothesis. Ancestral diet hypothesis, a hypothesis of dietary mismatch, is identified as a well-rounded hypothesis. This hypothesis argues the human dietary needs were shaped during the origin and evolution of Homo genus. This dietary environment changed rapidly with the onset of agriculture and industrial revolution which introduced novel foods in the human diet (grains, dairy and refined products) and is hypothesized to be the root cause of obesity and associated metabolic conditions. Results of a test of the Ancestral diet hypothesis in the form a dietary trial is provided where it is shown that dietary carbohydrates and their sources—grains, sugar and vegetables—are major predictors of changes in health-related anthropometric markers

Sudden cardiac death early after ST elevation myocardial infarction with and without severe left ventricular dysfunction

Introduction: There is high incidence of SCD in the early period following STEMI. We compared the temporal patterns and predictors of SCD amongst patients with LVEF ≤35% and LVEF >35%. Methods: Data from STEMI patients was prospectively collected. SCD cases formed the study cohort and were categorized into 2 groups based on their LV function. Results: There were 929 patients (mean age 55 ± 17 years) with a follow up of 41 ± 16 months. 154 pts (16.6%) had LVEF ≤35% (Group A, LVEF-29.9% ± 6%) and 775 pts had LVEF >35% (Group B, LVEF – 49% ± 14%). The two groups were similar with respect to sex distribution, age, prevalence of hypertension, and mean period of presentation. They differed in incidence of anterior wall MI (77.2% vs 55%), reperfusion (69% vs. 75%), prevalence of diabetes (50.6% vs 42%), and medication non-compliance (34% vs. 13%). The total SCD was 78 [Gp A, 25 (16.2%); Gp B, 53 (6.8%); p < 0.001]. The temporal cumulative SCD related mortality in the 2 groups was 1st month (8% vs. 4% p = 0.075), 3 months (14% vs. 5%, p < 0.001), 6 months (17% vs. 5%, p < 0.001), 1 year (18% vs. 6%, p < 0.001), at end of follow up (27% vs. 8%, p < 0.001). Multivariate predictors of SCD were medication compliance in the first month, and severe LV dysfunction with medication compliance beyond 1st month. Conclusion: The incidence of SCD is high in first month after STEMI, irrespective of LV function. The number of SCD is higher in Group B patients. Algorithms to assess risk of SCD in early post STEMI period are urgently needed

QT-prolongation as an indicator of complications in malaria

Introduction: There has always been a search for marker for predicting the complications of malaria. Electrocardiography (ECG) is a simple, easily available investigation, and QT-prolongation on ECG is a known marker of severity in many diseases. Aim: This study aimed to assess the association between QT interval prolongation and complications in malaria. Materials and Methods: This retrospective record-based study included 92 patients diagnosed with malaria by smear and was conducted from January to December 2013. The normal-corrected QT interval (QTC) was taken as 0.44 s (440 ms). Data were analyzed for association using Chi-square test and multivariate logistic regression model. Results: Mean QTC of the study group was 413.08 ± 34.8 ms. A total of 12 patients had QTC >440 ms, of them 10 had associated complications. Among 80 patients with normal QTC, 17 had complications associated with P < 0.001. Specificity of prolonged QTC for identifying complicated malaria was 83.33%, and sensitivity was 37.03%. On multivariate logistic regression model with QTC interval as the dependent variable, QTC was significantly associated with acute kidney injury (AKI) (P = 0.036) and Plasmodium vivax malaria (P = 0.01). Conclusions: Prolonged QTC has high specificity and low sensitivity for patients with complicated malaria. Prolonged QTC is significantly associated with vivax malaria and AKI in malaria. Hence, malaria patients with prolonged QTC should be more carefully watched for complications