Sharmala Thuraisingam

Dr. Sharmala Thuraisingam

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 December 2018 in BMC Public Health
Verified
Journal Article
Open access
PDF file
LTLaura Tarzia
Laura Tarzia
STSharmala Thuraisingam
Sharmala Thuraisingam
KNKitty Novy
Kitty Novy
JVJodie Valpied
Jodie Valpied
RQRebecca Quake
Rebecca Quake
KHKelsey Hegarty
Kelsey Hegarty
Research supports the association between adult sexual violence (SV) and poor mental health. However, most studies focus on rape and physical sexual assault. Little is known about how more subtle forms of SV affect women’s well-being. Furthermore, evidence for the impact of the perpetrator’s identity is mixed. There is also little data from clinical populations to help health practitioners identify SV. This paper addresses these gaps by exploring the associations between different types of adult SV, perpetrator identity, and women’s mental health in the Australian primary care setting. We conducted a descriptive, cross-sectional study in general practice clinics. Adult women completed an anonymous survey while waiting for the doctor. Measures included PHQ-9 (depression), GAD-7 (anxiety) and PCL-C (post-traumatic stress disorder). SV was measured using items from the National Intimate Partner and Sexual Violence Survey and categorised into three groups (rape/sexual assault; coercive behaviours and/or reproductive control; and unwanted sexual contact). We found significant associations between rape/sexual assault and poor mental health, and between coercion and/or reproductive control and higher PTSD and anxiety scores, compared to women with no SV experiences. SV perpetrated by an intimate partner was associated with significantly higher mean PTSD scores than SV perpetrated by a stranger, and significantly higher depression scores than SV perpetrated by another known person. Findings suggest that associations between SV and mental health are mediated by type of SV and perpetrator identity. Health practitioners should enquire about different types of SV beyond stranger rape as a cause of poor mental health, and about perpetrator identity to inform them about the likelihood of ongoing symptoms.

30 October 2021 in BMC Medical Informatics and Decision Making
Verified
Journal Article
Open access
PDF file
STSharmala Thuraisingam
Sharmala Thuraisingam
PCPatty Chondros
Patty Chondros
MDMichelle Maree Dowsey
Michelle Maree Dowsey
TSTim Spelman
Tim Spelman
SGStephanie Garies
Stephanie Garies
JMJo-Anne Manski-Nankervis
Jo-Anne Manski-Nankervis
Background: The use of general practice electronic health records (EHRs) for research purposes is in its infancy in Australia. Given these data were collected for clinical purposes, questions remain around data quality and whether these data are suitable for use in prediction model development. In this study we assess the quality of data recorded in 201,462 patient EHRs from 483 Australian general practices to determine its usefulness in the development of a clinical prediction model for total knee replacement (TKR) surgery in patients with osteoarthritis (OA). Methods: Variables to be used in model development were assessed for completeness and plausibility. Accuracy for the outcome and competing risk were assessed through record level linkage with two gold standard national registries, Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) and National Death Index (NDI). The validity of the EHR data was tested using participant characteristics from the 2014–15 Australian National Health Survey (NHS). Results: There were substantial missing data for body mass index and weight gain between early adulthood and middle age. TKR and death were recorded with good accuracy, however, year of TKR, year of death and side of TKR were poorly recorded. Patient characteristics recorded in the EHR were comparable to participant characteristics from the NHS, except for OA medication and metastatic solid tumour. Conclusions: In this study, data relating to the outcome, competing risk and two predictors were unfit for prediction model development. This study highlights the need for more accurate and complete recording of patient data within EHRs if these data are to be used to develop clinical prediction models. Data linkage with other gold standard data sets/registries may in the meantime help overcome some of the current data quality challenges in general practice EHRs when developing prediction models.

22 January 2021 in BMJ Open
Verified
Journal Article
Open access
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DGDaniel Gould
Daniel Gould
STSharmala Thuraisingam
Sharmala Thuraisingam
CSCade Shadbolt
Cade Shadbolt
JKJosh Knight
Josh Knight
Jesse YoungJesse Young
Jesse Young
MDMichelle Maree Dowsey
Michelle Maree Dowsey
Purpose The St Vincent’s Melbourne Arthroplasty Outcomes (SMART) Registry is an institutional clinical registry housed at a tertiary referral hospital in Australia. The SMART Registry is a pragmatic prospective database, which was established to capture a broad range of longitudinal clinical and patient-reported outcome data to facilitate collaborative research that will improve policy and practice relevant to arthroplasty surgery for people with advanced arthritis of the hip or knee. The purpose of this cohort profile paper is to describe the rationale for the SMART Registry’s creation, its methods, baseline data and future plans for the Registry. A full compilation of the data is provided as a reference point for future collaborators. Participants The SMART Registry cohort comprises over 13 000 consecutive arthroplasty procedures in more than 10 000 patients who underwent their procedure at St Vincent’s Hospital Melbourne, since January 1998. Participant recruitment, data collection and follow-up is ongoing and currently includes up to 20 years follow-up data. Findings to date SMART Registry data are used for clinical audit and feedback, as well as for a broad range of research including epidemiological studies, predictive statistical modelling and health economic evaluations. At the time of writing, there were 46 publications from SMART Registry data, with contributions from more than 67 coauthors. Future plans With the recent linking of the SMART Registry with Medicare Benefits Schedule and Pharmaceutical Benefits Scheme data through the Australian Institute of Health and Welfare, research into prescribing patterns and health system utilisation is currently underway. The SMART Registry is also being updated with the Clavien-Dindo classification of surgical complications.

17 October 2019 in JMIR Mental Health
Verified
Journal Article
Open access
LSLena Sanci
Lena Sanci
SKSylvia Kauer
Sylvia Kauer
STSharmala Thuraisingam
Sharmala Thuraisingam
SDSandra Davidson
Sandra Davidson
ADAnn-Maree Duncan
Ann-Maree Duncan
KBKerrie Buhagiar
Kerrie Buhagiar
Background: Mental health and substance use disorders are the main causes of disability among adolescents and young adults yet fewer than half experiencing these problems seek professional help. Young people frequently search the Web for health information and services, suggesting that Web-based modalities might promote help-seeking among young people who need it. To support young people in their help-seeking, we developed a Web-based mental health service navigation website called Link. Link is based on the Theory of Planned Behavior and connects young people with treatment based on the type and severity of mental health symptoms that they report. Objective: The study aimed to investigate the effect of Link on young people’s positive affect (PA) compared with usual help-seeking strategies immediately post intervention. Secondary objectives included testing the effect of Link on negative affect (NA), psychological distress, barriers to help-seeking, and help-seeking intentions. Methods: Young people, aged between 18 and 25 years, were recruited on the Web from an open access website to participate in a randomized controlled trial. Participants were stratified by gender and psychological distress into either the intervention arm (Link) or the control arm (usual help-seeking strategies). Baseline, immediate postintervention, 1-month, and 3-month surveys were self-reported and administered on the Web. Measures included the PA and NA scales, Kessler psychological distress scale (K10), barriers to adolescent help-seeking scale (BASH), and the general help-seeking questionnaire (GHSQ). Results: In total 413 young people were recruited to the trial (intervention, n=205; control, n=208) and 78% (160/205) of those randomized to the intervention arm visited the Link website. There was no evidence to support a difference between the intervention and control arms on the primary outcome, with PA increasing equally by approximately 30% between baseline and 3 months in both arms. NA decreased for the intervention arm compared with the control arm with a difference of 1.4 (95% CI 0.2-2.5) points immediately after the intervention and 2.6 (95% CI 1.1-4.1) at 1 month. K10 scores were unchanged and remained high in both arms. No changes were found on the BASH or GHSQ; however, participants in the intervention arm appeared more satisfied with their help-seeking process and outcomes at 1 and 3 months postintervention. Conclusions: The process of prompting young people to seek mental health information and services appears to improve their affective state and increase help-seeking intentions, regardless of whether they use a Web-based dedicated youth-focused tool, such as Link, or their usual search strategies. However, young people report greater satisfaction using tools designed specifically for them, which may encourage future help-seeking. The ability of Web-based tools to match mental health needs with appropriate care should be explored further. Clinical Trial: Australian New Zealand Clinical Trials Registry ACTRN12614001223628; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366731

18 February 2019 in BMC Family Practice
Verified
Journal Article
Open access
PDF file
JMJo-Anne Manski-Nankervis
Jo-Anne Manski-Nankervis
STSharmala Thuraisingam
Sharmala Thuraisingam
Janet SluggettJanet Sluggett
Janet Sluggett
GKGary Kilov
Gary Kilov
JFJohn Furler
John Furler
AJAlicia Jenkins
Alicia Jenkins
Previous studies in general practice and hospital settings have identified that prescribing of non-insulin diabetes medications may be sub-optimal in people with type 2 diabetes (T2D) and renal impairment. Since these publications, a number of new medications have become available for the management of T2D. Study aims were to, in a cohort of Australians with T2D and renal impairment attending general practice, (1) investigate whether the prescribing of non-insulin diabetes medications is consistent with dosing adjustments recommended within current Australian Diabetes Society (ADS) guidelines; and (2) identify patient socio-demographic and clinical factors associated with at least one prescription of a non-insulin diabetes medication inconsistent with current ADS guidelines for medication doses. Cross-sectional study using data from the MedicineInsight general practice database managed by NPS MedicineWise. Patients with T2D who were aged 18 years and over, with an average eGFR< 60 ml/min/1.73m2 and at least one prescription of a non-insulin diabetes medication between 1st January 2015 and 30th June 2017 were included. Descriptive statistics were used to summarise patient characteristics and medication use. Marginal logistic regression models were used to estimate associations between sociodemographic and clinical factors and prescribing of ≥1non-insulin diabetes medicine not consistent with ADS guidelines. The majority of the 3505 patients included (90.4%) had an average eGFR of 30-59 ml/min/1.73m2. In terms of absolute numbers, metformin was the medication most frequently prescribed at a dose not consistent with current ADS guidelines for dosing in renal impairment (n = 1601 patients), followed by DPP4 inhibitors (n = 611) and sulphonylureas (n = 278). The drug classes with the highest proportion of prescriptions with dosage not consistent with ADS guidelines were SGLT2 inhibitors (83%), followed by biguanides (58%) and DPP4 inhibitors (46%). Higher HbA1c, longer known diabetes duration and diagnosis of retinopathy were associated with receiving ≥1prescription with a dosage not consistent with guidelines. Prescribing of non-insulin diabetes medications at doses inconsistent with current ADS guideline recommendations for dosing adjustments for people with renal impairment was common. Further research is needed to understand how general practitioners access, interpret and apply the ADS guidelines and the impact this may have on patient outcomes.

21 July 2018 in BMC Endocrine Disorders
Verified
Journal Article
Open access
PDF file
MTMei Lyn Tan
Mei Lyn Tan
JMJo-Anne Manski-Nankervis
Jo-Anne Manski-Nankervis
STSharmala Thuraisingam
Sharmala Thuraisingam
AJAlicia Jenkins
Alicia Jenkins
DODavid O’nEal
David O’nEal
JFJohn Furler
John Furler
Optimal glycaemia, reflected by glycated haemoglobin (HbA1c) levels, is key in reducing type 2 diabetes (T2D) complications. However, most people with T2D have suboptimal recall and understanding of HbA1c. Continuous glucose monitoring (CGM) measures glucose levels every 5 to 15-min over days and may be more readily understood. Given that T2D is more common in lower socioeconomic settings, we aim to study relationships between socioeconomic status (SES) and percentage time in glucose target range (TIR) which is a key metric calculated from CGM. Analysis of baseline data from the General Practice Optimising Structured MOnitoring To Improve Clinical outcomes (GP-OSMOTIC) randomised controlled trial (October 2016 – November 2017) of 300 people with T2D from 25 Victorian General Practices. FreeStyle Libre Pro® sensor patch was used for this study. SES was defined by the Index of Relative Socio-economic Disadvantage (IRSD) and educational attainment. Univariable and multivariable mixed-effects linear regression analyses controlling for age, BMI, diet, exercise and study arm were performed. One hundred and sixty-seven (60.1%) participants were male, the mean (SD) participant age was 61.0 (9.7) years, and the mean (SD) duration of CGM use was 12.3 (2.5) days. The 10th IRSD decile (least disadvantaged) was associated with a 15% higher TIR vs. the 1st decile (most disadvantaged) (95% CI 5, 25; p = 0.003) and a 0.6% lower HbA1c (95% CI 0.1, 1; p = 0.03). There was no evidence of an association between educational attainment and TIR/HbA1c. Higher SES measured at an area level is associated with better achievement of glycaemic target using complementary measures of HbA1c and TIR in the GP-OSMOTIC cohort. Given that TIR may be more easily used in patient education and self-management support compared to HbA1c values, the social gradient identified in TIR provides an opportunity for clinicians and policy makers to address health inequities in T2D. Australian and New Zealand Clinical Trials Registry Trial ACTRN12616001372471 , prospective, Date registered 4/10/2016.