Publications by authors named "S H Abidi"

330 Publications

Factors associated with HIV infection among children in Larkana District, Pakistan: a matched case-control study.

Lancet HIV 2021 Jun;8(6):e342-e352

Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK.

Background: In April, 2019, an HIV outbreak predominantly affecting children occurred in Larkana District, Sindh, Pakistan. By December, 2019, 881 (4·0%) of 21 962 children screened for HIV had tested positive. We aimed to assess factors associated with HIV infection in this outbreak.

Methods: In this individually matched case-control study, we sampled 406 cases (individuals aged <16 years who had registered for paediatric HIV care at the HIV Treatment Centre at Shaikh Zayed Children's Hospital in Larkana City, Pakistan) and 406 controls (individuals without HIV matched by age, sex, and neighbourhood residence, recruited through doorknocking at houses adjacent to case participants). An interviewer-administered questionnaire was used to collect data on possible risk factors for HIV acquisition and a blood sample was collected from all participants for hepatitis B and hepatitis C serology. Mothers of all participants underwent HIV testing. Odds ratios were estimated using conditional logistic regression to assess factors associated with HIV infection.

Findings: 406 case-control pairs were recruited between July 3 and Dec 26, 2019. Five pairs were excluded (three pairs had an age mismatch and two pairs were duplicate cases) and 401 were analysed. The prevalence of hepatitis B surface antigen was 18·2% (95% CI 14·5-22·3) among cases and 5·2% (3·3-7·9) among controls, and the prevalence of hepatitis C antibodies was 6·5% (95% CI 4·3-9·4) among cases and 1·0% (0·3-2·5) among controls. 28 (7%) of 397 mothers of cases for whom we had data, and no mothers of 394 controls, were HIV positive. In the 6 months before recruitment, 226 (56%) of 401 cases and 32 (8%) of 401 controls reported having more than ten injections, and 291 (73%) cases and 78 (19%) controls had received an intravenous infusion. At least one blood transfusion was reported in 56 (14%) cases and three (1%) controls in the past 2 years. HIV infection was associated with a history of more injections and infusions (adjusted odds ratio 1·63; 95% CI 1·30-2·04, p<0·0001), blood transfusion (336·75; 23·69-4787·01, p<0·0001), surgery (399·75, 13·99-11 419·39, p=0·0005), the child's mother being HIV positive or having died (3·13, 1·20-8·20, p=0·020), and increased frequency of private clinic (p<0·0001) and government hospital visits (p<0·0001), adjusting for confounders.

Interpretation: The predominant mode of HIV transmission in this outbreak was parenteral, probably due to unsafe injection practices and poor blood safety practices. General practitioners across Pakistan need training and systems support in reducing injection use, and in providing safe injections and transfusions only when necessary.

Funding: Department of Pediatrics and Child Health, the Aga Khan University, Karachi, Pakistan.
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http://dx.doi.org/10.1016/S2352-3018(21)00049-7DOI Listing
June 2021

Using Knowledge Graphs to Plausibly Infer Missing Associations in EMR Data.

Stud Health Technol Inform 2021 May;281:417-421

NICHE Research Group, Faculty of Computer Science, Dalhousie University, Canada.

Electronic Medical Records (EMRs) are increasingly being deployed at primary points of care and clinics for digital record keeping, increasing productivity and improving communication. In practice, however, there still exists an often incomplete picture of patient profiles, not only because of disconnected EMR systems but also due to incomplete EMR data entry - often caused by clinician time constraints and lack of data entry restrictions. To complete a patient's partial EMR data, we plausibly infer missing causal associations between medical EMR concepts, such as diagnoses and treatments, for situations that lack sufficient raw data to enable machine learning methods. We follow a knowledge-based approach, where we leverage open medical knowledge sources such as SNOMED-CT and ICD, combined with knowledge-based reasoning with explainable inferences, to infer clinical encounter information from incomplete medical records. To bootstrap this process, we apply a semantic Extract-Transform-Load process to convert an EMR database into an enriched domain-specific Knowledge Graph.
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http://dx.doi.org/10.3233/SHTI210192DOI Listing
May 2021

A Knowledge Graph of Mechanistic Associations Between COVID-19, Diabetes Mellitus and Kidney Diseases.

Stud Health Technol Inform 2021 May;281:392-396

NICHE Research Group, Faculty of Computer Science, Dalhousie University.

This paper proposes an automated knowledge synthesis and discovery framework to analyze published literature to identify and represent underlying mechanistic associations that aggravate chronic conditions due to COVID-19. We present a literature-based discovery approach that integrates text mining, knowledge graphs and ontologies to discover semantic associations between COVID-19 and chronic disease concepts that were represented as a complex disease knowledge network that can be queried to extract plausible mechanisms by which COVID-19 may be exacerbated by underlying chronic conditions.
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http://dx.doi.org/10.3233/SHTI210187DOI Listing
May 2021

Using Interactive Visual Analytics to Optimize in Real-Time Blood Products Inventory at a Blood Bank.

Stud Health Technol Inform 2021 May;281:223-227

NICHE Research Group, Faculty of Computer Science, Dalhousie University, Halifax, Canada.

Blood products and their derivatives are perishable commodities that require an efficient inventory management to ensure both a low wastage rate and a high product availability rate. To optimize blood product inventory, blood transfusion services need to reduce wastage by avoiding outdates and improve availability of different blood products. We used advance visualization techniques to design and develop a highly interactive real-time web-based dashboard to monitor the blood product inventory and the on-going blood unit transactions in near-real-time based on analysis of transactional data. Blood transfusion staff use the dashboard to locate units with specific characteristics, investigate the lifecycle of the units, and efficiently transfer units between facilities to minimize outdates.
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http://dx.doi.org/10.3233/SHTI210153DOI Listing
May 2021

Analyzing Association Rules for Graft Failure Following Deceased and Live Donor Kidney Transplantation.

Stud Health Technol Inform 2021 May;281:188-192

Department of Computer Science, Dalhousie University, Halifax, NS, Canada.

This paper investigates the clinical attributes that contribute to kidney graft failure following live and deceased donor transplantation using an association rule mining approach. The generated rules are used to analyze the distinctive co-occurrence of attributes for those with or without all-cause graft failure. Analysis of a kidney transplantation dataset acquired from the Scientific Registry of Transplant Recipients that included over 95000 deceased and live donor recipients over 5-years was performed. Using an association rule mining approach, we were able to confirm established risk factors for graft loss after live and deceased donor transplantation and identify novel combinations of factors that may have implications for clinical care and risk prediction post kidney transplantation. Using lift as the metric to evaluate association rules, our results indicate that advanced recipient age (i.e. over 60 years), end stage kidney disease due to diabetes, the presence of recipient peripheral vascular disease and recipient coronary artery disease have a high likelihood of graft failure within 5 years after transplantation.
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http://dx.doi.org/10.3233/SHTI210146DOI Listing
May 2021