Codevelopment of a model of care for adults living with cystic fibrosis-related diabetes.

BACKGROUND: Cystic fibrosis (CF) related diabetes affects up to half of all adults with CF and is associated with higher morbidity and mortality. Our aim is to codevelop an ideal model of care that integrates diabetes technology and better meets the needs of adults living with the condition to improve attendance, engagement, service satisfaction, and clinical outcomes. METHODS: Using qualitative research methods, we evaluated disease perceptions, barriers, and enablers to optimal CF-related diabetes management and service delivery. Integration of continuous glucose monitoring (CGM) was also explored. An initial broad purposive consumer survey was followed by focus groups with end-users. Grounded theory approach was utilized with major problem areas identified then explored, coded, and grouped into requisites for an "ideal model of care" for adults living with CF-related diabetes. RESULTS: Two key themes emerged (i) an ideal model of care consisted of a dual-specialty service co-led by endocrinology and CF physicians and supported by diabetes educator and CF dietitian with a goal to provide consistent and personalized diabetes management and (ii) CGM was acceptable for use in adults with CF-related diabetes with many perceived benefits and should be integrated into the model of care. Barriers to optimizing glycemic control included diet, finger-prick testing, reduced access to CGM, and pulmonary exacerbations. End-user feedback on CGM was overwhelmingly positive with regard to operability. CGM was also identified as a tool that could be used to engage, educate, and empower adults living with CF-related diabetes and facilitate constructive and personalized clinical decision-making by healthcare providers. CONCLUSION: For adults living with CF, a diagnosis of diabetes is associated with increased treatment burden. Our findings suggest an "ideal model of care" for CF-related diabetes would be co-led by endocrinology services integrated within a pre-existing CF service, incorporating CGM.

Effects of modulator therapies on endocrine complications in adults with cystic fibrosis: a narrative review.

Cystic fibrosis is a monogenic disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) protein, which transports chloride ions in secretory organs. Modulator therapies are small molecules that correct CFTR dysfunction and can lead to a wide range of benefits for both pulmonary and extrapulmonary complications of cystic fibrosis. With advancements in airway, antimicrobial and nutritional therapies and now introduction of modulator therapies, most people living with cystic fibrosis in Australia are now adults. For adults with cystic fibrosis, endocrine manifestations such as cystic fibrosis-related diabetes, metabolic bone disease, and reproductive health are becoming increasingly important, and emerging evidence on the endocrine effects of CFTR modulator therapies is promising and is shifting paradigms in our understanding and management of these conditions. The management of cystic fibrosis-related diabetes will likely need to pivot for high responders to modulator therapy with dietary adaptions and potential use of medications traditionally reserved for adults with type 2 diabetes, but evidence to support changing clinical care needs is currently lacking. Increased attention to diabetes-related complications screening will also be required. Increased exercise capacity due to improved lung function, nutrition and potentially direct modulator effect may have a positive impact on cystic fibrosis-related bone disease, but supporting evidence to date is limited. Fertility can improve in women with cystic fibrosis taking modulator therapy. This has important implications for pregnancy and lactation, but evidence is lacking to guide pre-conception and antenatal management. Provision of multidisciplinary clinical care remains ever-important to ensure the emergence of endocrine and metabolic complications are optimised in adults with cystic fibrosis.

Temporal validation and updating of a prediction model for the diagnosis of gestational diabetes mellitus.

OBJECTIVE: The original Monash gestational diabetes mellitus (GDM) risk prediction in early pregnancy model is internationally externally validated and clinically implemented. We temporally validate and update this model in a contemporary population with a universal screening context and revised diagnostic criteria and ethnicity categories, thereby improving model performance and generalizability. STUDY DESIGN AND SETTING: The updating dataset comprised of routinely collected health data for singleton pregnancies delivered in Melbourne, Australia from 2016 to 2018. Model predictors included age, body mass index, ethnicity, diabetes family history, GDM history, and poor obstetric outcome history. Model updating methods were recalibration-in-the-large (Model A), intercept and slope re-estimation (Model B), and coefficient revision using logistic regression (Model C1, original ethnicity categories; Model C2, revised ethnicity categories). Analysis included 10-fold cross-validation, assessment of performance measures (c-statistic, calibration-in-the-large, calibration slope, and expected-observed ratio), and a closed-loop testing procedure to compare models' log-likelihood and akaike information criterion scores. RESULTS: In 26,474 singleton pregnancies (4,756, 18% with GDM), the original model demonstrated reasonable temporal validation (c-statistic = 0.698) but suboptimal calibration (expected-observed ratio = 0.485). Updated model C2 was preferred, with a high c-statistic (0.732) and significantly better performance in closed testing. CONCLUSION: We demonstrated updating methods to sustain predictive performance in a contemporary population, highlighting the value and versatility of prediction models for guiding risk-stratified GDM care.

A surge in serum mucosal cytokines associated with seroconversion in children at risk for type 1 diabetes.

AIMS/INTRODUCTION: Autoantibodies to pancreatic islet antigens identify young children at high risk of type 1 diabetes. On a background of genetic susceptibility, islet autoimmunity is thought to be driven by environmental factors, of which enteric viruses are prime candidates. We sought evidence for enteric pathology in children genetically at-risk for type 1 diabetes followed from birth who had developed islet autoantibodies ("seroconverted"), by measuring mucosa-associated cytokines in their sera. MATERIALS AND METHODS: Sera were collected 3 monthly from birth from children with a first-degree type 1 diabetes relative, in the Environmental Determinants of Islet Autoimmunity (ENDIA) study. Children who seroconverted were matched for sex, age, and sample availability with seronegative children. Luminex xMap technology was used to measure serum cytokines. RESULTS: Of eight children who seroconverted, for whom serum samples were available at least 6 months before and after seroconversion, the serum concentrations of mucosa-associated cytokines IL-21, IL-22, IL-25, and IL-10, the Th17-related cytokines IL-17F and IL-23, as well as IL-33, IFN-γ, and IL-4, peaked from a low baseline in seven around the time of seroconversion and in one preceding seroconversion. These changes were not detected in eight sex- and age-matched seronegative controls, or in a separate cohort of 11 unmatched seronegative children. CONCLUSIONS: In a cohort of children at risk for type 1 diabetes followed from birth, a transient, systemic increase in mucosa-associated cytokines around the time of seroconversion lends support to the view that mucosal infection, e.g., by an enteric virus, may drive the development of islet autoimmunity.

Experiences of Caregivers and At-Risk Children Enrolled in a Prospective Pregnancy-Birth Cohort Study into the Causes of Type 1 Diabetes: The ENDIA Study.

BACKGROUND: We sought research experiences of caregivers and their children were enrolled in the Environmental Determinants of Islet Autoimmunity (ENDIA) study. METHODS: ENDIA is a pregnancy-birth cohort investigating early-life causes of type 1 diabetes (T1D). Surveys were sent to 1090 families between June 2021 and March 2022 with a median participation of >5 years. Caregivers completed a 12-item survey. Children ≥ 3 years completed a four-item survey. RESULTS: The surveys were completed by 550/1090 families (50.5%) and 324/847 children (38.3%). The research experience was rated as either "excellent" or "good" by 95% of caregivers, and 81% of children were either "ok", "happy" or "very happy". The caregivers were motivated by contributing to research and monitoring their children for T1D. Relationships with the research staff influenced the experience. The children most liked virtual reality headsets, toys, and "helping". Blood tests were least liked by the children and were the foremost reason that 23.4% of the caregivers considered withdrawing. The children valued gifts more than their caregivers. Only 5.9% of responses indicated dissatisfaction with some aspects of the protocol. The self-collection of samples in regional areas, or during the COVID-19 pandemic restrictions, were accepted. CONCLUSIONS: This evaluation identified modifiable protocol elements and was conducted to further improve satisfaction. What was important to the children was distinct from their caregivers.

Protocol for a nested case-control study design for omics investigations in the Environmental Determinants of Islet Autoimmunity cohort.

Background: The Environmental Determinants of Islet Autoimmunity (ENDIA) pregnancy-birth cohort investigates the developmental origins of type 1 diabetes (T1D), with recruitment between 2013 and 2019. ENDIA is the first study in the world with comprehensive data and biospecimen collection during pregnancy, at birth and through childhood from at-risk children who have a first-degree relative with T1D. Environmental exposures are thought to drive the progression to clinical T1D, with pancreatic islet autoimmunity (IA) developing in genetically susceptible individuals. The exposures and key molecular mechanisms driving this progression are unknown. Persistent IA is the primary outcome of ENDIA; defined as a positive antibody for at least one of IAA, GAD, ZnT8 or IA2 on two consecutive occasions and signifies high risk of clinical T1D.Method: A nested case-control (NCC) study design with 54 cases and 161 matched controls aims to investigate associations between persistent IA and longitudinal omics exposures in ENDIA. The NCC study will analyse samples obtained from ENDIA children who have either developed persistent IA or progressed to clinical T1D (cases) and matched control children at risk of developing persistent IA. Control children were matched on sex and age, with all four autoantibodies absent within a defined window of the case's onset date. Cases seroconverted at a median of 1.37 years (IQR 0.95, 2.56). Longitudinal omics data generated from approximately 16,000 samples of different biospecimen types, will enable evaluation of changes from pregnancy through childhood.Conclusions: This paper describes the ENDIA NCC study, omics platform design considerations and planned univariate and multivariate analyses for its longitudinal data. Methodologies for multivariate omics analysis with longitudinal data are discovery-focused and data driven. There is currently no single multivariate method tailored specifically for the longitudinal omics data that the ENDIA NCC study will generate and therefore omics analysis results will require either cross validation or independent validation.KEY MESSAGESThe ENDIA nested case-control study will utilize longitudinal omics data on approximately 16,000 samples from 190 unique children at risk of type 1 diabetes (T1D), including 54 who have developed islet autoimmunity (IA), followed during pregnancy, at birth and during early childhood, enabling the developmental origins of T1D to be explored.

Disposition of patients utilising the virtual emergency department service in southeast region of Melbourne (SERVED-1).

OBJECTIVE: Supported by the state government, three health networks partnered to initiate a virtual ED (VED), as part of a broader roll-out of emergency telehealth services in Victoria. The aim of the present study (Southeast Region Virtual Emergency Department-1 [SERVED-1]) was to report the initial 5-month experience and included all patients assessed through the service over the first 5 months (1 February 2022 to 30 June 2022). METHODS: VED consults occurred after referral from paramedics in the pre-hospital setting. Electronic medical records were retrospectively reviewed for demographic, presenting complaint and outcome data. The primary outcome was the count of VED consultations. The secondary outcome was the proportion of patients where physical ED attendance was avoided within 72 h. The proportion of physical ED attendances avoided sub-grouped by primary presenting complaints were reported. RESULTS: There were 1748 patients who had a VED consultation, of which 1261 (72.1%; 95% confidence interval [CI] 70.0-74.2) patients had physical presentation to an ED avoided in the 72 h following the consult. There was a significant increase in consultations over the 5-month period (incidence rate ratio 1.27; 95% CI 1.23-1.31, P < 0.001) that was consistent in the three health services. The most common presenting complaints were COVID-19 and shortness of breath, and physical presentation was avoided most often among younger patients and those with COVID-19. CONCLUSIONS: Initial experience demonstrated a significant increase in adoption of the service and an overall avoidance of physical ED attendance by a majority of patients. These results support ongoing VED consultations, complemented by follow up and health economic evaluations.

Continuous glucose monitoring versus self-monitoring of blood glucose in the management of cystic fibrosis related diabetes: A systematic review and meta-analysis.

BACKGROUND: Treatment of cystic fibrosis related diabetes (CFRD) can improve outcomes and use of continuous glucose monitoring (CGM) can positively impact glycemic control. We conducted a systematic review to assess current evidence on CGM compared to self-monitoring of blood glucose (SMBG) in the management of CFRD to determine its effect on glycemic, pulmonary, non-pulmonary and quality of life outcomes. METHODS: Using pre-defined selection criteria, we searched MEDLINE, Embase, CENTRAL, Evidence-Based Medicine Reviews, grey literature and six relevant journals for studies using CGM and/or SMBG in CFRD with greater than 6 weeks of follow-up and reported change in HbA1c. The primary outcome was weighted mean difference (WMD) in plasma HbA1c between CGM and SMBG groups. Secondary outcomes included exploring interrelationships between CGM metrics and effects on disease-specific pulmonary, non-pulmonary and quality of life outcomes. RESULTS: A total of 1671 references were retrieved, 862 studies screened and 124 full-texts assessed for eligibility. No studies directly compared CGM to SMBG. A meta-analysis of seventeen studies of 416 individuals (CGM = 138, SMBG = 278) found CGM group had 4.1 mmol/mol (95% CI -7.9 to -0.30, p = 0.034) lower HbA1c compared to SMBG group. Most studies demonstrated moderate-to-high risk of bias. Publication bias was also present. Heterogeneity was high and meta-regression identified duration of follow-up in SMBG group as main contributor. CONCLUSION: Our findings suggest use of CGM may be associated with improved glycemic control compared to SMBG in CFRD, however evidence of benefit on pulmonary, non-pulmonary and psychosocial outcomes are lacking.

A Long-Term Evaluation of Facebook for Recruitment and Retention in the ENDIA Type 1 Diabetes Pregnancy-Birth Cohort Study.

BACKGROUND: The Environmental Determinants of Islet Autoimmunity (ENDIA) study is an Australia-wide pregnancy-birth cohort study following children who have a first-degree relative with type 1 diabetes (ACTRN1261300794707). A dedicated ENDIA Facebook page was established in 2013 with the aim of enhancing recruitment and supporting participant retention through dissemination of study information. To measure the impact of Facebook, we evaluated the sources of referral to the study, cohort demographics, and withdrawal rates. We also investigated whether engagement with Facebook content was associated with specific post themes. METHODS: Characteristics of Facebook versus conventional recruits were compared using linear, logistic, and multinomial logistic regression models. Logistic regression was used to determine the risk of study withdrawal. Data pertaining to 794 Facebook posts over 7.5 years were included in the analysis. RESULTS: Facebook was the third largest source of referral (300/1511; 19.9%). Facebook recruits were more frequently Australian-born (P < .001) enrolling postnatally (P = .01) and withdrew from the study at a significantly lower rate compared with conventional recruits (4.7% vs 12.3%; P < .001) after a median of follow-up of 3.3 years. Facebook content featuring stories and images of participants received the highest engagement even though <20% of the 2337 Facebook followers were enrolled in the study. CONCLUSIONS: Facebook was a valuable recruitment tool for ENDIA. Compared with conventional recruits, Facebook recruits were three times less likely to withdraw during long-term follow-up and had different sociodemographic characteristics. Facebook content featuring participants was the most engaging. These findings inform social media strategies for future cohort and type 1 diabetes studies. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry: ACTRN1261300794707.

Comparison of continuous glucose monitoring to reference standard oral glucose tolerance test for the detection of dysglycemia in cystic Fibrosis: A systematic review.

Aims: Increasing evidence for benefit of early detection of cystic fibrosis related diabetes (CFRD) coupled with limitations of current diagnostic investigations has led to interest and utilisation of continuous glucose monitoring (CGM). We conducted a systematic review to assess current evidence on CGM compared to reference standard oral glucose tolerance test for the detection of dysglycemia in people with cystic fibrosis without confirmed diabetes. Methods: MEDLINE, Embase, CENTRAL, Evidence-Based Medicine Reviews, grey literature and six relevant journals were searched for studies published after year 2000. Studies reporting contemporaneous CGM metrics and oral glucose tolerance test results were included. Outcomes on oral glucose tolerance tests were categorised into a) normal, b) abnormal (indeterminate and impaired) or c) diabetic as defined by American Diabetes Association criteria. CGM outcomes were defined as hyperglycemia (≥1 peak sensor glucose ≥ 200 mg/dL), dysglycemia (≥1 peak sensor glucose ≥ 140-199 mg/dL) or normoglycemia (all sensor glucose peaks < 140 mg/dL). CGM hyperglycemia in people with normal or abnormal glucose tolerances was used to define an arbitrary CGM-diagnosis of diabetes. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess risk of bias. Primary outcome was relative risk of an arbitrary CGM-diagnosis of diabetes compared to the oral glucose tolerance test. Results: We identified 1277 publications, of which 19 studies were eligible comprising total of 416 individuals with contemporaneous CGM and oral glucose tolerance test results. Relative risk of an arbitrary CGM-diagnosis of diabetes compared to oral glucose tolerance test was 2.92. Studies analysed were highly heterogenous, prone to bias and inadequately assessed longitudinal associations between CGM and relevant disease-specific sequela. Conclusions: A single reading > 200 mg/dL on CGM is not appropriate for the diagnosis of CFRD. Prospective studies correlating CGM metrics to disease-specific outcomes are needed to determine appropriate cut-points.

Development, validation and clinical utility of a risk prediction model for adverse pregnancy outcomes in women with gestational diabetes: The PeRSonal GDM model.

Background: The ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with gestational diabetes mellitus (GDM) would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. We aimed to develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM. Methods: A prediction model development and validation study was conducted on data from a observational cohort. Participants included all women with GDM from three metropolitan tertiary teaching hospitals in Melbourne, Australia. The development cohort comprised those who delivered between 1 July 2017 to 30 June 2018 and the validation cohort those who delivered between 1 July 2018 to 31 December 2018. The main outcome was a composite of critically important maternal and perinatal complications (hypertensive disorders of pregnancy, large-for-gestational age neonate, neonatal hypoglycaemia requiring intravenous therapy, shoulder dystocia, perinatal death, neonatal bone fracture and nerve palsy). Model performance was measured in terms of discrimination and calibration and clinical utility evaluated using decision curve analysis. Findings: The final PeRSonal (Prediction for Risk Stratified care for women with GDM) model included body mass index, maternal age, fasting and 1-hour glucose values (75-g oral glucose tolerance test), gestational age at GDM diagnosis, Southern and Central Asian ethnicity, East Asian ethnicity, nulliparity, past delivery of an large-for-gestational age neonate, past pre-eclampsia, GWG until GDM diagnosis, and family history of diabetes. The composite adverse pregnancy outcome occurred in 27% (476/1747) of women in the development (1747 women) and in 26% (244/955) in the validation (955 women) cohorts. The model showed excellent calibration with slope of 0.99 (95% CI 0.75 to 1.23) and acceptable discrimination (c-statistic 0.68; 95% CI 0.64 to 0.72) when temporally validated. Decision curve analysis demonstrated that the model was useful across a range of predicted probability thresholds between 0.15 and 0.85 for adverse pregnancy outcomes compared to the alternatives of managing all women with GDM as if they will or will not have an adverse pregnancy outcome. Interpretation: The PeRSonal GDM model comprising of routinely available clinical data shows compelling performance, is transportable across time, and has clinical utility across a range of predicted probabilities. Further external validation of the model to a more disparate population is now needed to assess the generalisability to different centres, community based care and low resource settings, other healthcare systems and to different GDM diagnostic criteria. Funding: This work is supported by the Mothers and Gestational Diabetes in Australia 2 NHMRC funded project #1170847.

Under-utilisation of cardioprotective glucose-lowering medication in diabetics living with HIV.

Diabetes is an increasingly common co-morbidity in people living with HIV (PLWH). Given new evidence demonstrating cardiovascular benefits of sodium glucose transporter 2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP1RA) in diabetic patients, we reviewed medical charts of 262 PLWH at Monash Health through a 1-year retrospective cohort study to determine the rates of their use. Prevalence of diabetes was 13.4% (35) and 60% (21) had microvascular and macrovascular complications. Only 4% (95% CI 0.1%-19.6%) of diabetic patients were receiving SGLT2i and 19% (95% CI 6%-39.4%) were receiving GLP1RA. Prescribers should carefully consider their choice of glucose-lowering medication when treating PLWH.

Mental Health During Late Pregnancy and Postpartum in Mothers With and Without Type 1 Diabetes: The ENDIA Study.

OBJECTIVE: Pregnancy and type 1 diabetes are each associated with increased anxiety and depression, but the combined impact on well-being is unresolved. We compared the mental health of women with and without type 1 diabetes during pregnancy and postpartum and examined the relationship between mental health and glycemic control. RESEARCH DESIGN AND METHODS: Participants were women enrolled from 2016 to 2020 in the Environmental Determinants of Islet Autoimmunity (ENDIA) study, a pregnancy to birth prospective cohort following children with a first-degree relative with type 1 diabetes. Edinburgh Postnatal Depression Scale (EPDS) and Perceived Stress Scale (PSS) were completed during the third trimester (T3) (median [interquartile range] 34 [32, 36] weeks) and postpartum (14 [13, 16] weeks) by 737 women (800 pregnancies) with (n = 518) and without (n = 282) type 1 diabetes. RESULTS: EPDS and PSS scores did not differ between women with and without type 1 diabetes during T3 and postpartum. EPDS scores were marginally higher in T3: predicted mean (95% CI) 5.7 (5.4, 6.1) than postpartum: 5.3 (5.0, 5.6), independent of type 1 diabetes status (P = 0.01). HbA1c levels in type 1 diabetes were 6.3% [5.8, 6.9%] in T3 and did not correlate with EPDS or PSS scores. Reported use of psychotropic medications was similar in women with (n = 44 of 518 [8%]) and without type 1 diabetes (n = 17 of 282 [6%]), as was their amount of physical activity. CONCLUSIONS: Overall, mental health in late pregnancy and postpartum did not differ between women with and without type 1 diabetes, and mental health scores were not correlated with glycemic control.

Women with type 1 diabetes exhibit a progressive increase in gut Saccharomyces cerevisiae in pregnancy associated with evidence of gut inflammation.

AIMS: Studies of the gut microbiome have focused on its bacterial composition. We aimed to characterize the gut fungal microbiome (mycobiome) across pregnancy in women with and without type 1 diabetes. METHODS: Faecal samples (n = 162) were collected from 70 pregnant women (45 with and 25 without type 1 diabetes) across all trimesters. Fungi were analysed by internal transcribed spacer 1 amplicon sequencing. Markers of intestinal inflammation (faecal calprotectin) and intestinal epithelial integrity (serum intestinal fatty acid binding protein; I-FABP), and serum antibodies to Saccharomyces cerevisiae (ASCA) were measured. RESULTS: Women with type 1 diabetes had decreased fungal alpha diversity by the third trimester, associated with an increased abundance of Saccharomyces cerevisiae that was inversely related to the abundance of the anti-inflammatory butyrate-producing bacterium Faecalibacterium prausnitzii. Women with type 1 diabetes had higher concentrations of calprotectin, I-FABP and ASCA. CONCLUSIONS: Women with type 1 diabetes exhibit a shift in the gut mycobiome across pregnancy associated with evidence of gut inflammation and impaired intestinal barrier function. The relevance of these findings to the higher rate of pregnancy complications in type 1 diabetes warrants further study.

Type 1 diabetes in pregnancy is associated with distinct changes in the composition and function of the gut microbiome.

BACKGROUND: The gut microbiome changes in response to a range of environmental conditions, life events and disease states. Pregnancy is a natural life event that involves major physiological adaptation yet studies of the microbiome in pregnancy are limited and their findings inconsistent. Pregnancy with type 1 diabetes (T1D) is associated with increased maternal and fetal risks but the gut microbiome in this context has not been characterized. By whole metagenome sequencing (WMS), we defined the taxonomic composition and function of the gut bacterial microbiome across 70 pregnancies, 36 in women with T1D. RESULTS: Women with and without T1D exhibited compositional and functional changes in the gut microbiome across pregnancy. Profiles in women with T1D were distinct, with an increase in bacteria that produce lipopolysaccharides and a decrease in those that produce short-chain fatty acids, especially in the third trimester. In addition, women with T1D had elevated concentrations of fecal calprotectin, a marker of intestinal inflammation, and serum intestinal fatty acid-binding protein (I-FABP), a marker of intestinal epithelial damage. CONCLUSIONS: Women with T1D exhibit a shift towards a more pro-inflammatory gut microbiome during pregnancy, associated with evidence of intestinal inflammation. These changes could contribute to the increased risk of pregnancy complications in women with T1D and are potentially modifiable by dietary means. Video abstract.

Continuous glucose monitoring indices predict poor FEV1 recovery following cystic fibrosis pulmonary exacerbations.

BACKGROUND: Little is known about the effect of dysglycemia during cystic fibrosis pulmonary exacerbation (PEx) on recovery of FEV1 percentage predicted (ppFEV1) METHODS: Continuous glucose monitoring (CGM) was commenced at the time of admission to hospital for PEx and continued for 6 weeks. The CGM indices, percentage of time glucose greater than 7.8 mmol/L (%T>7.8) and mean glucose were evaluated as predictors of absolute ppFEV1 change following treatment of PEx. RESULTS: Of the 20 participants who completed the study 13 (65%) had cystic fibrosis related diabetes (CFRD). The mean of both CGM indices were highest during the first week of pulmonary exacerbation and continued to decline over the first 4 weeks at which point they plateaued. Using multivariate regression models, factors which were predictive of maximum attained ppFEV1 change over 6 weeks were %T>7.8, mean glucose, HbA1c and preadmission ppFEV1 change from baseline. These relationships were independent of a diagnosis of CFRD, which was not associated with ppFEV1 recovery. In a longitudinal model of ppFEV1 change at weeks 1, 2 and 6, the CGM index %T>7.8 approached significance as a predictive variable. CONCLUSIONS: Hyperglycemia during PEx in adult CF patients is associated with poorer ppFEV1 recovery. Conversely, there was no association observed between CFRD diagnosis and ppFEV1 improvement, suggesting that optimization of glycemic control in CFRD patients may positively influence recovery of lung function. Further clinical trials are required to evaluate the merits of intensive glycemic control in CFRD during PEx.

Protocol for development and validation of a clinical prediction model for adverse pregnancy outcomes in women with gestational diabetes.

INTRODUCTION: Gestational diabetes (GDM) is a common yet highly heterogeneous condition. The ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with GDM would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. The Prediction for Risk-Stratified care for women with GDM (PeRSonal GDM) study will develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM. METHODS AND ANALYSIS: We undertook formative research to conceptualise and design the prediction model. Informed by these findings, we will conduct a model development and validation study using a retrospective cohort design with participant data collected as part of routine clinical care across three hospitals. The study will include all pregnancies resulting in births from 1 July 2017 to 31 December 2018 coded for a diagnosis of GDM (estimated sample size 2430 pregnancies). We will use a temporal split-sample development and validation strategy. A multivariable logistic regression model will be fitted. The performance of this model will be assessed, and the validated model will also be evaluated using decision curve analysis. Finally, we will explore modes of model presentation suited to clinical use, including electronic risk calculators. ETHICS AND DISSEMINATION: This study was approved by the Human Research Ethics Committee of Monash Health (RES-19-0000713 L). We will disseminate results via presentations at scientific meetings and publication in peer-reviewed journals. TRIAL REGISTRATION DETAILS: Systematic review proceeding this work was registered on PROSPERO (CRD42019115223) and the study was registered on the Australian and New Zealand Clinical Trials Registry (ACTRN12620000915954); Pre-results.

The Unrealised Potential for Predicting Pregnancy Complications in Women with Gestational Diabetes: A Systematic Review and Critical Appraisal.

Gestational diabetes (GDM) increases the risk of pregnancy complications. However, these risks are not the same for all affected women and may be mediated by inter-related factors including ethnicity, body mass index and gestational weight gain. This study was conducted to identify, compare, and critically appraise prognostic prediction models for pregnancy complications in women with gestational diabetes (GDM). A systematic review of prognostic prediction models for pregnancy complications in women with GDM was conducted. Critical appraisal was conducted using the prediction model risk of bias assessment tool (PROBAST). Five prediction modelling studies were identified, from which ten prognostic models primarily intended to predict pregnancy complications related to GDM were developed. While the composition of the pregnancy complications predicted varied, the delivery of a large-for-gestational age neonate was the subject of prediction in four studies, either alone or as a component of a composite outcome. Glycaemic measures and body mass index were selected as predictors in four studies. Model evaluation was limited to internal validation in four studies and not reported in the fifth. Performance was inadequately reported with no useful measures of calibration nor formal evaluation of clinical usefulness. Critical appraisal using PROBAST revealed that all studies were subject to a high risk of bias overall driven by methodologic limitations in statistical analysis. This review demonstrates the potential for prediction models to provide an individualised absolute risk of pregnancy complications for women affected by GDM. However, at present, a lack of external validation and high risk of bias limit clinical application. Future model development and validation should utilise the latest methodological advances in prediction modelling to achieve the evolution required to create a useful clinical tool. Such a tool may enhance clinical decision-making and support a risk-stratified approach to the management of GDM. Systematic review registration: PROSPERO CRD42019115223.