STK3 higher expression association with clinical characteristics in intrinsic subtypes of breast cancer invasive ductal carcinoma patients.

PURPOSE: STK3 has a central role in maintaining cell homeostasis, proliferation, growth, and apoptosis. Previously, we investigated the functional link between STK3/MST2, and estrogen receptor in MCF-7 breast cancer cells. To expand the investigation, this study evaluated STK3's higher expression and associated genes in breast cancer intrinsic subtypes using publicly available data. METHODS: The relationship between clinical pathologic features and STK3 high expression was analyzed using descriptive and multivariate analysis. RESULTS: Increased STK3 expression in breast cancer was significantly associated with higher pathological cancer stages, and a different expression level was observed in the intrinsic subtypes of breast cancer. Kaplan-Meier analysis showed that breast cancer with high STK3 had a lower survival rate in IDC patients than that with low STK3 expression (p < 0.05). The multivariate analysis unveiled a strong correlation between STK3 expression and the survival rate among IDC patients, demonstrating hazard ratios for lower expression. In the TCGA dataset, the hazard ratio was 0.56 (95% CI 0.34-0.94, p = 0.029) for patients deceased with tumor, and 0.62 (95% CI 0.42-0.92, p = 0.017) for all deceased patients. Additionally, in the METABRIC dataset, the hazard ratio was 0.76 (95% CI 0.64-0.91, p = 0.003) for those deceased with tumor. From GSEA outcomes 7 gene sets were selected based on statistical significance (FDR < 0.25 and p < 0.05). Weighted Sum model (WSM) derived top 5% genes also have higher expression in basal and lower in luminal A in association with STK3. CONCLUSION: By introducing a novel bioinformatics approach that combines GSEA and WSM, the study successfully identified the top 5% of genes associated with higher expression of STK3.

Introducing ACTFAiREST2 to implement online assessments amid COVID-19: a case study from a low resource setting.

BACKGROUND: Amid COVID-19, soon after the closure of academic institutions, academia was compelled to implement teaching and assessments virtually. The situation was not the same for all countries. This transition was much more challenging in low-resource settings like Pakistan, where the students were geographically distant with minimal connectivity. A private university in Pakistan instituted a systematic approach for ensuring quality assurance and reliability before launching online assessments amid the COVID-19. The purpose of this study was to reflect on the phased transition to online/remote assessments to facilitate continuous student learning through distance modalities during the pandemic. METHOD: To assist faculty in re-designing their assessments, a workshop was conducted which was based on the modified Walker's nine principles. The principles coded as "ACTFAiREST2" were introduced to ensure that the faculty understands and adapts these principles in designing online assessments. The faculty modified and re-designed their course assessments, from face to face to online modality and submitted their proposals to the Curriculum Committee (CC). To guide the process of approving modified and re-designed assessments, a checklist was adapted. All the pre and -post workshop assessment proposals were analyzed using a content analysis approach to ensure the alignment of course learning outcomes with the assessments. RESULTS: A total of 45 undergraduate courses' assessment proposals were approved by the CC after deliberations ensuring their applicability in a virtual environment. From the analysis of the course outlines and assessment proposals submitted to the CC, faculty made four key changes to their assessment tasks in the light of ACT FAiREST2 principles (a) alternative to performance exams; (b) alternative to knowledge exams; (c) change in the mode of assessment administration; and (d) minimizing the overall assessment load. CONCLUSION: This transition provided an impetus for the faculty from a low resource setting to build momentum towards improved and innovative ways of online teaching and assessments for future nursing education to adapt to the new normal situation. This development will serve as a resource in similar contexts with planned and evidence-based approaches for enhancing faculty readiness and preparedness for online/remote assessments.

COVID-19 Knowledge Resource Categorization and Tracking: Conceptual Framework Study.

BACKGROUND: Since the declaration of COVID-19 as a global pandemic by the World Health Organization, the disease has gained momentum with every passing day. Various private and government sectors of different countries allocated funding for research in multiple capacities. A significant portion of efforts has been devoted to information technology and service infrastructure development, including research on developing intelligent models and techniques for alerts, monitoring, early diagnosis, prevention, and other relevant services. As a result, many information resources have been created globally and are available for use. However, a defined structure to organize these resources into categories based on the nature and origin of the data is lacking. OBJECTIVE: This study aims to organize COVID-19 information resources into a well-defined structure to facilitate the easy identification of a resource, tracking information workflows, and to provide a guide for a contextual dashboard design and development. METHODS: A sequence of action research was performed that involved a review of COVID-19 efforts and initiatives on a global scale during the year 2020. Data were collected according to the defined structure of primary, secondary, and tertiary categories. Various techniques for descriptive statistical analysis were employed to gain insights into the data to help develop a conceptual framework to organize resources and track interactions between different resources. RESULTS: Investigating diverse information at the primary, secondary, and tertiary levels enabled us to develop a conceptual framework for COVID-19-related efforts and initiatives. The framework of resource categorization provides a gateway to access global initiatives with enriched metadata, and assists users in tracking the workflow of tertiary, secondary, and primary resources with relationships between various fragments of information. The results demonstrated mapping initiatives at the tertiary level to secondary level and then to the primary level to reach firsthand data, research, and trials. CONCLUSIONS: Adopting the proposed three-level structure allows for a consistent organization and management of existing COVID-19 knowledge resources and provides a roadmap for classifying future resources. This study is one of the earliest studies to introduce an infrastructure for locating and placing the right information at the right place. By implementing the proposed framework according to the stated guidelines, this study allows for the development of applications such as interactive dashboards to facilitate the contextual identification and tracking of interdependent COVID-19 knowledge resources.

Retention of knowledge regarding mathematics and drug dosage calculation among undergraduate nursing students of a private school of nursing in Pakistan.

This study aimed to assess the level of retention of knowledge regarding calculation of drug dose among undergraduate nursing students studying at a private school of nursing. This was a pre- and post-comparison design conducted at the Aga Khan University, Pakistan, from August 2017 to September 2019. All the students enrolled in Bachelor of Science in Nursing (BScN) (Class of 2019) were included in the study. Mean test scores of 141 fourth year BScN students were compared with their own performance in the second year. Mean scores on mathematics and drug dosage calculation test decreased significantly from 21 in second year to 17.97 in the final year of studies. Modifications in assessments as well as curriculum are suggested to improve retention of dose calculation skills among undergraduate nursing students.

Community stakeholders' views on reducing violence against women in Pakistan.

BACKGROUND: Nearly half of the women experience violence across their lifespan in all the provinces of Pakistan at an alarming rate. Despite knowing the prevalence, there has been meager progress in developing strategies to combat violence at individual, family, or community level. Many interventions suggested in other countries have been pilot tested but the effects of those interventions had been limited. Therefore, the aim of this study is to understand the voices of stakeholders to reduce Violence Against Women (VAW) and to explore the possible community-based strategies that could be implemented in Pakistan. METHODS: A total of 14 Key Informant Interviews (KIIs) and 18 Focus Group Discussions (FGDs) were held across all four provinces of Pakistan. Participants were purposefully recruited and all the interviews were audio-recorded. Transcriptions were open coded and content analysis was done to emerge codes, categories and themes. Ethical approval was obtained from Aga Khan University Ethics Review Committee. RESULTS: Three major themes emerged on community members and stakeholders' views on VAW: a) community's perception of VAW b) the repercussions of VAW, and c) multiple voices regarding strategies to reduce VAW. Participants voiced the need of standing against the status quo, role of awareness and education: regarding capacity building skills, promotion of women rights and women empowerment through Life Skills Based Education (LSBE) through national health works program, has been proposed as an innovative strategy to reduce VAW. CONCLUSIONS: The responsibility to bring about a substantial change in behavior and attitudes must begin with engaging men in all the interventions that aim to reduce violence. Since, VAW is very much linked with the cultural norms, so, without community stakeholder's involvement and participation it could never be reduced. Keeping the existing socio-cultural dynamics in mind, the need of time is to design and implement innovative interventions that are culturally and contextually appropriate and can be expanded across the country.

Community stakeholders' perspectives regarding acceptability of a life skills building intervention to empower women in Pakistan.

Violence against women (VAW) is a major determinant in the assessment of a women's mental health. Many interventions have addressed strategies to reduce VAW, however, little information is available regarding effectiveness in the local context, particularly the role of men in women's empowerment. In Pakistan, a qualitative approach was undertaken in all four of its provinces to describe the community residents', both men and women, perceptions regarding the acceptability of a proposed life skills building (LSB) intervention involving men's engagement with regards to women's empowerment and VAW. Eighteen focus group discussions were conducted with men and women from locales within each province of Pakistan, averaging 6-10 participants per group. Fourteen key informant interviews were conducted with community stakeholders. The analysis identified three major themes: family life and male engagement, LSB training as an empowerment tool, and operationalization of the proposed LSB intervention. The proposed LSB intervention was well accepted by the participants with a strong urge to engage men in receiving the LSB training sessions. Men's engagement has been identified as an important element to facilitate women's empowerment. Participants suggested that these sessions should be held for two and a half hours per week within the community public spaces. In addition, these sessions should be based on an interactive approach. The focus of these sessions should include ideas surrounding positive relationships and economic skills building. Moreover, men's engagement will help to reduce VAW and improve the mental health of women in a patriarchal country like Pakistan.

Smart Extraction and Analysis System for Clinical Research.

BACKGROUND: With the increasing use of electronic health records (EHRs), there is a growing need to expand the utilization of EHR data to support clinical research. The key challenge in achieving this goal is the unavailability of smart systems and methods to overcome the issue of data preparation, structuring, and sharing for smooth clinical research. MATERIALS AND METHODS: We developed a robust analysis system called the smart extraction and analysis system (SEAS) that consists of two subsystems: (1) the information extraction system (IES), for extracting information from clinical documents, and (2) the survival analysis system (SAS), for a descriptive and predictive analysis to compile the survival statistics and predict the future chance of survivability. The IES subsystem is based on a novel permutation-based pattern recognition method that extracts information from unstructured clinical documents. Similarly, the SAS subsystem is based on a classification and regression tree (CART)-based prediction model for survival analysis. RESULTS: SEAS is evaluated and validated on a real-world case study of head and neck cancer. The overall information extraction accuracy of the system for semistructured text is recorded at 99%, while that for unstructured text is 97%. Furthermore, the automated, unstructured information extraction has reduced the average time spent on manual data entry by 75%, without compromising the accuracy of the system. Moreover, around 88% of patients are found in a terminal or dead state for the highest clinical stage of disease (level IV). Similarly, there is an ∼36% probability of a patient being alive if at least one of the lifestyle risk factors was positive. CONCLUSION: We presented our work on the development of SEAS to replace costly and time-consuming manual methods with smart automatic extraction of information and survival prediction methods. SEAS has reduced the time and energy of human resources spent unnecessarily on manual tasks.

The Mining Minds digital health and wellness framework.

BACKGROUND: The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people's conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main engine of this change, with an increasing number of domain-specific applications and devices commercialized every year; however, there is an apparent lack of frameworks capable of orchestrating and intelligently leveraging, all the data, information and knowledge generated through these systems. METHODS: This work presents Mining Minds, a novel framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized support. Mining Minds embraces some of the most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, as well as modern concepts and methods, such as context-awareness, knowledge bases or analytics, to holistically and continuously investigate on people's lifestyles and provide a variety of smart coaching and support services. RESULTS: This paper comprehensively describes the efficient and rational combination and interoperation of these technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support. Moreover, this work presents a realization of the key architectural components of Mining Minds, as well as various exemplary user applications and expert tools to illustrate some of the potential services supported by the proposed framework. CONCLUSIONS: Mining Minds constitutes an innovative holistic means to inspect human behavior and provide personalized health and wellness support. The principles behind this framework uncover new research ideas and may serve as a reference for similar initiatives.

The role of micro health insurance in providing financial risk protection in developing countries--a systematic review.

BACKGROUND: Out of pocket payments are the predominant method of financing healthcare in many developing countries, which can result in impoverishment and financial catastrophe for those affected. In 2010, WHO estimated that approximately 100 million people are pushed below the poverty line each year by payments for healthcare. Micro health insurance (MHI) has been used in some countries as means of risk pooling and reducing out of pocket health expenditure. A systematic review was conducted to assess the extent to which MHI has contributed to providing financial risk protection to low-income households in developing countries, and suggest how the findings can be applied in the Pakistani setting. METHODS: We conducted a systematic search for published literature using the search terms "Community based health insurance AND developing countries", "Micro health insurance AND developing countries", "Mutual health insurance AND developing countries", "mutual OR micro OR community based health insurance" "Health insurance AND impact AND poor" "Health insurance AND financial protection" and "mutual health organizations" on three databases, Pubmed, Google Scholar and Science Direct (Elsevier). Only those records that were published in the last ten years, in English language with their full texts available free of cost, were considered for inclusion in this review. Hand searching was carried out on the reference lists of the retrieved articles and webpages of international organizations like World Bank, World Health Organization and International Labour Organization. RESULTS: Twenty-three articles were eligible for inclusion in this systematic review (14 from Asia and 9 from Africa). Our analysis shows that MHI, in the majority of cases, has been found to contribute to the financial protection of its beneficiaries, by reducing out of pocket health expenditure, catastrophic health expenditure, total health expenditure, household borrowings and poverty. MHI also had a positive safeguarding effect on household savings, assets and consumption patterns. CONCLUSION: Our review suggests that MHI, targeted at the low-income households and tailored to suit the cultural and geographical structures in the various areas of Pakistan, may contribute towards providing protection to the households from catastrophe and impoverishment resulting from health expenditures. This paper emphasizes the need for further research to fill the knowledge gap that exists about the impact of MHI, using robust study designs and impact indicators.

H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus.

Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body's resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1) restricted one type of diabetes; (2) lack understandability and explanatory power of the techniques and decision; (3) limited either to prediction purpose or management over the structured contents; and (4) lack competence for dimensionality and vagueness of patient's data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM) that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM) and type-2 diabetes mellitus (T2DM). For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST) based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies.

Knowledge-Based Query Construction Using the CDSS Knowledge Base for Efficient Evidence Retrieval.

Finding appropriate evidence to support clinical practices is always challenging, and the construction of a query to retrieve such evidence is a fundamental step. Typically, evidence is found using manual or semi-automatic methods, which are time-consuming and sometimes make it difficult to construct knowledge-based complex queries. To overcome the difficulty in constructing knowledge-based complex queries, we utilized the knowledge base (KB) of the clinical decision support system (CDSS), which has the potential to provide sufficient contextual information. To automatically construct knowledge-based complex queries, we designed methods to parse rule structure in KB of CDSS in order to determine an executable path and extract the terms by parsing the control structures and logic connectives used in the logic. The automatically constructed knowledge-based complex queries were executed on the PubMed search service to evaluate the results on the reduction of retrieved citations with high relevance. The average number of citations was reduced from 56,249 citations to 330 citations with the knowledge-based query construction approach, and relevance increased from 1 term to 6 terms on average. The ability to automatically retrieve relevant evidence maximizes efficiency for clinicians in terms of time, based on feedback collected from clinicians. This approach is generally useful in evidence-based medicine, especially in ambient assisted living environments where automation is highly important.

Recommendations service for chronic disease patient in multimodel sensors home environment.

With advanced technologies in hand, there exist potential applications and services built around monitoring activities of daily living (ADL) of elderly people at nursing homes. Most of the elderly people in these facilities are suffering from different chronic diseases such as dementia. Existing technologies are mainly focusing on non-medication interventions and monitoring of ADL for addressing loss of autonomy or well-being. Monitoring and managing ADL related to cognitive behaviors for non-medication intervention are very effective in improving dementia patients' conditions. However, cognitive functions of patients can be improved if appropriate recommendations of medications are delivered at a particular time. Previously we developed the Secured Wireless Sensor Network Integrated Cloud Computing for Ubiquitous-Life Care (SC(3)). SC(3) services were limited to monitoring ADL of elderly people with Alzheimer's disease and providing non-medication recommendations to the patient. In this article, we propose a system called the Smart Clinical Decision Support System (CDSS) as an integral part of the SC(3) platform. Using the Smart CDSS, patients are provided with access to medication recommendations of expert physicians. Physicians are provided with an interface to create clinical knowledge for medication recommendations and to observe the patient's condition. The clinical knowledge created by physicians as the knowledge base of the Smart CDSS produces recommendations to the caregiver for medications based on each patient's symptoms.

A comparative study of Ru(II) cyclometallated complexes versus thiocyanated heteroleptic complexes: thermodynamic force for efficient dye regeneration in dye-sensitized solar cells and how low could it be?

Four novel Ru(II) bipyridyl complexes MH12­15 were synthesized and characterized for dye-sensitized solar cells (DSSCs). Their photovoltaic performance including incident photon-to-current conversion efficiency (IPCE), total solar-to-power conversion efficiency (η%) and ground and excited state oxidation potentials and photoelectrochemical properties were evaluated on mesoporous nanocrystalline TiO2 and compared with the benchmark N719-dye under the same experimental conditions. MH12­15 showed stronger MLCT with significantly higher molar extinction coefficient for the lower energy absorption bands at 553 nm (27,500 M(−1) cm(−1)), 554 nm (34,605 M(−1) cm(−1)), 577 nm (23,300 M(−1) cm(−1)), and 582 nm (39,000 M(−1) cm(−1)), respectively, than that of N719 (14,200 M(−1) cm(−1)). The introduction of a cyclometallated ligand in dyes MH14 and 15 improved the optical properties and red-shifts of 24 nm and 28 nm, respectively, compared to the non-cyclometallated analogs MH12 and 13. The red shift in the UV-Vis spectra of MH14 and 15 can be attributed to the destabilization of the HOMO t2g of Ru(II). However, the destabilization of the HOMO furnished an upward shift of the ground state oxidation potentials (GSOPs) of MH14 and 15 at −5.44 eV and −5.36 eV against vacuum, respectively, which resulted in a driving force of only 0.22 and 0.16 eV for regeneration of dyes MH14 and 15, respectively. In the case of NCS analogs, MH12 and 13, the GSOPs, however, were −5.56 and −5.51 eV, respectively, which produced a driving force of more than 0.25 eV for dye regeneration. The nanosecond transient absorbance measurements showed that the time needed for the oxidized forms of MH12­MH15 to regenerate the neutral dye is 6 µs, 4 µs, 13 µs and 18 µs, respectively, compared to N719 (2.3 µs). These kinetic data confirmed that the weak thermodynamic force, small negative free energy (−ΔG), for regeneration of MH14 and 15 neutral dyes makes the dye regeneration process kinetically sluggish, which contributed significantly to the loss of both photocurrent and photovoltage. This study clearly elucidated that although cyclometallation may produce significantly better light harvesting, the driving force of less than 0.25 eV is not sufficiently enough for effective dye regeneration.

An adaptive semantic based mediation system for data interoperability among Health Information Systems.

Heterogeneity in the management of the complex medical data, obstructs the attainment of data level interoperability among Health Information Systems (HIS). This diversity is dependent on the compliance of HISs with different healthcare standards. Its solution demands a mediation system for the accurate interpretation of data in different heterogeneous formats for achieving data interoperability. We propose an adaptive AdapteR Interoperability ENgine mediation system called ARIEN, that arbitrates between HISs compliant to different healthcare standards for accurate and seamless information exchange to achieve data interoperability. ARIEN stores the semantic mapping information between different standards in the Mediation Bridge Ontology (MBO) using ontology matching techniques. These mappings are provided by our System for Parallel Heterogeneity (SPHeRe) matching system and Personalized-Detailed Clinical Model (P-DCM) approach to guarantee accuracy of mappings. The realization of the effectiveness of the mappings stored in the MBO is evaluation of the accuracy in transformation process among different standard formats. We evaluated our proposed system with the transformation process of medical records between Clinical Document Architecture (CDA) and Virtual Medical Record (vMR) standards. The transformation process achieved over 90 % of accuracy level in conversion process between CDA and vMR standards using pattern oriented approach from the MBO. The proposed mediation system improves the overall communication process between HISs. It provides an accurate and seamless medical information exchange to ensure data interoperability and timely healthcare services to patients.

Structure-property relationship of extended π-conjugation of ancillary ligands with and without an electron donor of heteroleptic Ru(II) bipyridyl complexes for high efficiency dye-sensitized solar cells.

Two new heteroleptic Ru(II) bipyridyl complexes MH06 and MH11 were designed, synthesized and characterized for DSSCs. While the ancillary ligand of MH06 was molecularly engineered with a strong electron donating group coupled with an extended π-conjugated system, the ancillary ligand of MH11 contained a longer π-conjugated system only. Molecular modeling, photophysical, and photovoltaic properties were compared under the same experimental conditions against the benchmark N719. In an effort to understand the structure-property relationship, their photovoltaic and photoelectrochemical properties including Jsc, Voc, ground and excited state oxidation potentials, UV-Vis absorption, and molar extinction coefficients were studied. The UV-Vis results showed intense MLCT absorption peaks of MH06 and MH11 in the visible region with a red shift of 12 and 18 nm, respectively, with significantly higher molar extinction coefficients compared to N719. Tetrabutylammonium (TBA) substituted MH11-TBA demonstrated the most efficient IPCE of over 90% in the plateau region covering the entire visible spectrum and extending into the near IR region (ca. 890 nm), which showed a solar-to-power conversion efficiency (η) of 10.06%, significantly higher than that of the benchmark N719 dye (9.32%). The superior performance in terms of the IPCE and Jsc of MH11 can be attributed to the bulky and highly hydrophobic nature of the pyrene-based ancillary ligand, which behaves as a shielding barrier for hole-transport recombination between TiO2 and the electrolyte. In addition, the IMPS results showed that the contribution of dyes to the conduction band shift of the TiO2 level is almost similar, regardless of different substitutions on the bipy-moiety. This implies that the open-circuit photovoltage (Voc) increases with reduced charge recombination in the presence of a thick layer of tetrabutyl ammonium ions (TBA) of the dye anchored on the surface of TiO2.

Personalized-detailed clinical model for data interoperability among clinical standards.

OBJECTIVE: Data interoperability among health information exchange (HIE) systems is a major concern for healthcare practitioners to enable provisioning of telemedicine-related services. Heterogeneity exists in these systems not only at the data level but also among different heterogeneous healthcare standards with which these are compliant. The relationship between healthcare organization data and different heterogeneous standards is necessary to achieve the goal of data level interoperability. We propose a personalized-detailed clinical model (P-DCM) approach for the generation of customized mappings that creates the necessary linkage between organization-conformed healthcare standards concepts and clinical model concepts to ensure data interoperability among HIE systems. MATERIALS AND METHODS: We consider electronic health record (EHR) standards, openEHR, and HL7 CDA instances transformation using P-DCM. P-DCM concepts associated with openEHR and HL7 CDA help in transformation of instances among these standards. We investigated two datasets: (1) data of 100 diabetic patients, including 50 each of type 1 and type 2, from a local hospital in Korea and (2) data of a single Alzheimer's disease patient. P-DCMs were created for both scenarios, which provided the basis for deriving instances for HL7 CDA and openEHR standards. RESULTS: For proof of concept, we present case studies of encounter information for type 2 diabetes mellitus patients and monitoring of daily routine activities of an Alzheimer's disease patient. These reflect P-DCM-based customized mappings generation with openEHR and HL7 CDA standards. Customized mappings are generated based on the relationship of P-DCM concepts with CDA and openEHR concepts. CONCLUSIONS: The objective of this work is to achieve semantic data interoperability among heterogeneous standards. This would lead to effective utilization of resources and allow timely information exchange among healthcare systems.

Clinical presentation, risk factors and outcome of stroke at a district level teaching hospital.

BACKGROUND: Stroke is a fatal clinical syndrome with mortality rate ranging up to 25%. Hypertension, smoking and diabetes mellitus are common preventable risk factors which are associated with serious outcome. Objective of this study was to determine the clinical presentation, risk factors and outcome of stroke. METHODS: A cross-sectional study was conducted in the Medical Wards of DHQ Teaching Hospital, Mirpur Azad Kashmir from March 2010 to January 2011. A questionnaire was prepared in accordance with the objectives of the study. Frequency of risk factors in patients with stroke were studied. Different clinical features were also noted and response to the given treatment was checked in the form of mortality and recovery. Frequencies and percentages were calculated using SPSS-12. RESULTS: Two hundred patients with stroke were selected. Of the total, 136 (68%) had hypertension, 55 (27.5%) were smokers, 53 (26.5%) had diabetes and 25 (12.5%) patients had ischemic heart disease. One hundred and two (51%) patients presented with headache, 99 (49.5%) developed hemiplegia and 94 (47%) had loss of consciousness. CT brain showed infarction in 144 (72%) patients while 56 (28%) had haemorrhage. Observed mortality in this study was 18 (9%) while 182 (91%) patients were discharged after treatment. CONCLUSION: Hypertension, smoking and diabetes mellitus are major modifiable risk factors for stroke. Headache, hemiplegia and loss of consciousness are major clinical features. Ischemic stroke is much common compared to hemorrhagic stroke. With proper care stroke is manageable satisfactorily.

Secondary findings in a large Pakistani cohort tested with whole genome sequencing.

Studies on genomic secondary findings (SFs) are diverse in participants' characteristics, sequencing methods, and versions of the ACMG SF list. Based on whole genome sequencing and the version 3.1 of the ACMG SF list, we studied SFs in 863 individuals from five different regions in Pakistan. We identified 24 ACMG SFs in 23 (2.7%) of 863 individuals: 18 of 24 were related to cardiovascular disease and four to cancer syndromes. In addition to ACMG SFs, we identified 16 (1.9%) participants with pathogenic and likely pathogenic variants in genes that were not related to the participants' clinical conditions but with clear medical actionability (non-ACMG SFs): 4 of 16 were related to eye diseases, two to metabolic disorders, and two to urinary system disorders. By testing a large Pakistani cohort with whole genome sequencing, we concluded that in countries such as Pakistan, the ACMG SF list could be expanded, and our non-ACMG SF list is one example.

Diagnostic Value Of Serum Urea, Creatinine, Sodium And Potassium For Complicated Appendicitis - A One Year Retrospective Study.

BACKGROUND: Acute appendicitis is a common surgical emergency and if complicated, manifesting as abscess, perforation, suppurative or gangrenous appendicitis, carries significant morbidity and mortality. Its early preoperative diagnosis can improve outcome in patients and reduce incidence of negative appendectomies. It, however, mandates identification of new diagnostic parameters for it. This retrospective study evaluates diagnostic accuracy of serum urea, creatinine, sodium and potassium for complicated appendicitis. METHODS: Sixty patients with suspected appendicitis were grouped into complicated and uncomplicated appendicitis based on histological reports. Preoperative laboratory results for serum urea, creatinine, sodium and potassium levels were obtained from hospital records. Diagnostic strength of these markers was calculated as specificity, sensitivity and area under curve. ROC curve analysis was used for their diagnostic accuracy. RESULTS: The levels of serum urea, creatinine and K were not significantly different in uncomplicated and complicated appendicitis. However, sodium was significantly higher in complicated appendicitis. ROC curve analysis showed AUC values for all the studied variables to be greater than 0.5. However, none of the markers had good capability to differentiate complicated appendicitis from uncomplicated appendicitis. CONCLUSIONS: Serum urea, creatinine, sodium and potassium levels have shown a tendency to be predictive of complicated appendicitis but a strong association could not have been established. Hence, further investigation is warranted.