Delivery of maternal health care in Indigenous primary care services: baseline data for an ongoing quality improvement initiative

Extent: 10p.BACKGROUND: Australia's Aboriginal and Torres Strait Islander (Indigenous) populations have disproportionately high rates of adverse perinatal outcomes relative to other Australians. Poorer access to good quality maternal health care is a key driver of this disparity. The aim of this study was to describe patterns of delivery of maternity care and service gaps in primary care services in Australian Indigenous communities. METHODS: We undertook a cross-sectional baseline audit for a quality improvement intervention. Medical records of 535 women from 34 Indigenous community health centres in five regions (Top End of Northern Territory 13, Central Australia 2, Far West New South Wales 6, Western Australia 9, and North Queensland 4) were audited. The main outcome measures included: adherence to recommended protocols and procedures in the antenatal and postnatal periods including: clinical, laboratory and ultrasound investigations; screening for gestational diabetes and Group B Streptococcus; brief intervention/advice on health-related behaviours and risks; and follow up of identified health problems. RESULTS: The proportion of women presenting for their first antenatal visit in the first trimester ranged from 34% to 49% between regions; consequently, documentation of care early in pregnancy was poor. Overall, documentation of routine antenatal investigations and brief interventions/advice regarding health behaviours varied, and generally indicated that these services were underutilised. For example, 46% of known smokers received smoking cessation advice/counselling; 52% of all women received antenatal education and 51% had investigation for gestational diabetes. Overall, there was relatively good documentation of follow up of identified problems related to hypertension or diabetes, with over 70% of identified women being referred to a GP/Obstetrician. CONCLUSION: Participating services had both strengths and weaknesses in the delivery of maternal health care. Increasing access to evidence-based screening and health information (most notably around smoking cessation) were consistently identified as opportunities for improvement across services.Alice R. Rumbold, Ross S. Bailie, Damin Si, Michelle C. Dowden, Catherine M. Kennedy, Rhonda J. Cox, Lynette O’Donoghue, Helen E. Liddle, Ru K. Kwedza, Sandra C. Thompson, Hugh P. Burke, Alex D. H. Brown, Tarun Weeramanthri and Christine M. Connor

Fatigue in primary Sjögren's syndrome (pSS) is associated with lower levels of proinflammatory cytokines: a validation study

Primary Sjögren’s syndrome (pSS) is a chronic autoimmune rheumatic disease with symptoms including dryness, fatigue, and pain. The previous work by our group has suggested that certain proinflammatory cytokines are inversely related to patient-reported levels of fatigue. To date, these findings have not been validated. This study aims to validate this observation. Blood levels of seven cytokines were measured in 120 patients with pSS from the United Kingdom Primary Sjögren’s Syndrome Registry and 30 age-matched healthy non-fatigued controls. Patient-reported scores for fatigue were classified according to severity and compared to cytokine levels using analysis of variance. The differences between cytokines in cases and controls were evaluated using Wilcoxon test. A logistic regression model was used to determine the most important identifiers of fatigue. Five cytokines, interferon-γ-induced protein-10 (IP-10), tumour necrosis factor-α (TNFα), interferon-α (IFNα), interferon-γ (IFN-γ), and lymphotoxin-α (LT-α) were significantly higher in patients with pSS (n = 120) compared to non-fatigued controls (n = 30). Levels of two proinflammatory cytokines, TNF-α (p = 0.021) and LT-α (p = 0.043), were inversely related to patient-reported levels of fatigue. Cytokine levels, disease-specific and clinical parameters as well as pain, anxiety, and depression were used as predictors in our validation model. The model correctly identifies fatigue levels with 85% accuracy. Consistent with the original study, pain, depression, and proinflammatory cytokines appear to be the most powerful predictors of fatigue in pSS. TNF-α and LT-α have an inverse relationship with fatigue severity in pSS challenging the notion that proinflammatory cytokines directly mediate fatigue in chronic immunological conditions