Three novel F8 mutations in sporadic haemophilia A cases

Letter to the editorRashid Hussain, Noman Bin Abid, Sajjad Hussain, Zeeshan Shaukat, Mudassir Altaf, Sara Altaf, and Gulzar Niaz

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist

PANC Study (Pancreatitis: A National Cohort Study): national cohort study examining the first 30 days from presentation of acute pancreatitis in the UK

Abstract Background Acute pancreatitis is a common, yet complex, emergency surgical presentation. Multiple guidelines exist and management can vary significantly. The aim of this first UK, multicentre, prospective cohort study was to assess the variation in management of acute pancreatitis to guide resource planning and optimize treatment. Methods All patients aged greater than or equal to 18 years presenting with acute pancreatitis, as per the Atlanta criteria, from March to April 2021 were eligible for inclusion and followed up for 30 days. Anonymized data were uploaded to a secure electronic database in line with local governance approvals. Results A total of 113 hospitals contributed data on 2580 patients, with an equal sex distribution and a mean age of 57 years. The aetiology was gallstones in 50.6 per cent, with idiopathic the next most common (22.4 per cent). In addition to the 7.6 per cent with a diagnosis of chronic pancreatitis, 20.1 per cent of patients had a previous episode of acute pancreatitis. One in 20 patients were classed as having severe pancreatitis, as per the Atlanta criteria. The overall mortality rate was 2.3 per cent at 30 days, but rose to one in three in the severe group. Predictors of death included male sex, increased age, and frailty; previous acute pancreatitis and gallstones as aetiologies were protective. Smoking status and body mass index did not affect death. Conclusion Most patients presenting with acute pancreatitis have a mild, self-limiting disease. Rates of patients with idiopathic pancreatitis are high. Recurrent attacks of pancreatitis are common, but are likely to have reduced risk of death on subsequent admissions. </jats:sec

TKIFRPM: A Novel Approach for Topmost-K Identical Frequent Regular Patterns Mining from Incremental Datasets

The regular frequent pattern mining (RFPM) approaches are aimed to discover the itemsets with significant frequency and regular occurrence behavior in a dataset. However, these approaches mainly suffer from the following two issues: (1) setting the frequency threshold parameter for the discovery of regular frequent patterns technique is not an easy task because of its dependency on the characteristics of a dataset, and (2) RFPM approaches are designed to mine patterns from the static datasets and are not able to mine dynamic datasets. This paper aims to solve these two issues by proposing a novel top-K identical frequent regular patterns mining (TKIFRPM) approach to function on online datasets. The TKIFRPM maintains a novel synopsis data structure with item support index tables (ISI-tables) to keep summarized information about online committed transactions and dataset updates. The mining operation can discover top-K regular frequent patterns from online data stored in the ISI-tables. The TKIFRPM explores the search space in recursive depth-first order and applies a novel progressive node’s sub-tree pruning strategy to rapidly eliminate a complete infrequent sub-tree from the search space. The TKIFRPM is compared with the MTKPP approach, and it found that it outperforms its counterpart in terms of runtime and memory usage to produce designated topmost-K frequent regular pattern mining on the datasets following incremental updates

TKIFRPM: A Novel Approach for Topmost-K Identical Frequent Regular Patterns Mining from Incremental Datasets

The regular frequent pattern mining (RFPM) approaches are aimed to discover the itemsets with significant frequency and regular occurrence behavior in a dataset. However, these approaches mainly suffer from the following two issues: (1) setting the frequency threshold parameter for the discovery of regular frequent patterns technique is not an easy task because of its dependency on the characteristics of a dataset, and (2) RFPM approaches are designed to mine patterns from the static datasets and are not able to mine dynamic datasets. This paper aims to solve these two issues by proposing a novel top-K identical frequent regular patterns mining (TKIFRPM) approach to function on online datasets. The TKIFRPM maintains a novel synopsis data structure with item support index tables (ISI-tables) to keep summarized information about online committed transactions and dataset updates. The mining operation can discover top-K regular frequent patterns from online data stored in the ISI-tables. The TKIFRPM explores the search space in recursive depth-first order and applies a novel progressive node&rsquo;s sub-tree pruning strategy to rapidly eliminate a complete infrequent sub-tree from the search space. The TKIFRPM is compared with the MTKPP approach, and it found that it outperforms its counterpart in terms of runtime and memory usage to produce designated topmost-K frequent regular pattern mining on the datasets following incremental updates

Prominence of Filtering Techniques for Harmonics Mitigation in Advanced Power Electronics Systems

With the advancement in technology, non-linear loads, continue to increase, and the enigma of harmonics is getting more and more serious. The huge addition of electronic loads in power systems has formed the problem of harmonic generation that has resulted in many associated drawbacks. This paper aims to analyze the harmonics in advanced power electronics-based systems and describes a solution to mitigate them through two distinguished filtering techniques. A rigorous analysis is done concerning the generation of harmonic distortion through different types of loads and harmonic mitigation by employing passive and active power filters. The active power (adaptive) filtering method mitigates all sorts of undesirable frequency components using artificial intelligence (AI) based algorithms by calculating the weight of the fundamental component and generating a harmonics replica to subtract it from the original periodic wave. The simulations that were done show that the indicated techniques can mitigate undesirable harmonics and can lower the total harmonic distortion (THD) effectively according to the statutory limit of the IEEE 519-2014 standard, thus lowering the associated drawbacks of harmonic generation in advanced power electronics systems

Prominence of Filtering Techniques for Harmonics Mitigation in Advanced Power Electronics Systems

With the advancement in technology, non-linear loads, continue to increase, and the enigma of harmonics is getting more and more serious. The huge addition of electronic loads in power systems has formed the problem of harmonic generation that has resulted in many associated drawbacks. This paper aims to analyze the harmonics in advanced power electronics-based systems and describes a solution to mitigate them through two distinguished filtering techniques. A rigorous analysis is done concerning the generation of harmonic distortion through different types of loads and harmonic mitigation by employing passive and active power filters. The active power (adaptive) filtering method mitigates all sorts of undesirable frequency components using artificial intelligence (AI) based algorithms by calculating the weight of the fundamental component and generating a harmonics replica to subtract it from the original periodic wave. The simulations that were done show that the indicated techniques can mitigate undesirable harmonics and can lower the total harmonic distortion (THD) effectively according to the statutory limit of the IEEE 519-2014 standard, thus lowering the associated drawbacks of harmonic generation in advanced power electronics systems

Which curve is better? A comparative analysis of trauma scoring systems in a South Asian country

Objectives: A diverse set of trauma scoring systems are used globally to predict outcomes and benchmark trauma systems. There is a significant potential benefit of using these scores in low and middle-income countries (LMICs); however, its standardized use based on type of injury is still limited. Our objective is to compare trauma scoring systems between neurotrauma and polytrauma patients to identify the better predictor of mortality in low-resource settings.Methods: Data were extracted from a digital, multicenter trauma registry implemented in South Asia for a secondary analysis. Adult patients (≥18 years) presenting with a traumatic injury from December 2021 to December 2022 were included in this study. Injury Severity Score (ISS), Trauma and Injury Severity Score (TRISS), Revised Trauma Score (RTS), Mechanism/GCS/Age/Pressure score and GCS/Age/Pressure score were calculated for each patient to predict in-hospital mortality. We used receiver operating characteristic curves to derive sensitivity, specificity and area under the curve (AUC) for each score, including Glasgow Coma Scale (GCSResults :The mean age of 2007 patients included in this study was 41.2±17.8 years, with 49.1% patients presenting with neurotrauma. The overall in-hospital mortality rate was 17.2%. GCS and RTS proved to be the best predictors of in-hospital mortality for neurotrauma (AUC: 0.885 and 0.874, respectively), while TRISS and ISS were better predictors for polytrauma patients (AUC: 0.729 and 0.722, respectively).Conclusion :Trauma scoring systems show differing predictability for in-hospital mortality depending on the type of trauma. Therefore, it is vital to take into account the region of body injury for provision of quality trauma care. Furthermore, context-specific and injury-specific use of these scores in LMICs can enable strengthening of their trauma system

Exploring the long-term disability outcomes in trauma patients: Study protocol

Objectives: Post-discharge patient-reported outcomes from trauma registries can be used to measure trauma care quality. However, studies reflecting the Asian experience are limited. Therefore, we aim to develop a digital trauma registry to prospectively capture patient-reported outcomes (PROs) at one-, three-, six-, and twelve-months post-injury in Pakistan.Methods: We will use a cohort study design to develop a digital trauma registry at two tertiary care facilities (Aga Khan University Hospital & Jinnah Postgraduate Medical Center) in Karachi, Pakistan. The registry will include all admitted adult trauma patients (≥18 years). Data collection will be digital using tablets, with mortality, level of disability, and functional status, quality of life being the outcomes. Telephonic interviews will be conducted with the patients and caregivers for follow-up data collection.Discussion: The high disability burden following accidental trauma imposes a significant burden and cost on individuals and society. Therefore, the trauma registry would fill this gap by capturing post-discharge long-term PROs. It will provide the injured patient\u27s post-discharge situation, challenges, and future directions for incorporating long-term PROs in low-resource settings. Including long-term measures in routine follow-ups will provide insights into physical, social, and policy barriers and help advance injury care research