First trimester serum biomarkers to predict gestational diabetes in a high-risk cohort: Striving for clinically useful thresholds

Objectives: Screening and diagnosis of gestational diabetes (GDM) has been a source of controversy. The prevalence has increased in line with an obesity epidemic and a trend towards delayed child-bearing. Treatment of even modest glycaemic impairment in pregnancy has been shown to be beneficial in preventing its clinical sequalae. However the cumbersome nature and timing of the oral glucose tolerance test coupled with debate around universal versus risk factor based screening have been problematic. This group aimed to investigate a panel of biomarkers which have shown promise in the literature to predict GDM from the first trimester in a group of high risk women. Methods: Serum samples were drawn on 248 women deemed at risk of GDM before 15 weeks\u27 gestation to measure C-reactive protein, sex hormone binding globulin, adiponectin and 1,5 anhydroglucitol. Patients underwent an oral glucose tolerance test as per IADPSG criteria at 28 weeks\u27 gestation. Multiple logistic regression was used to examine the link between incidence of GDM and early pregnancy serum biomarkers. Results: Adiponectin levels in the first trimester are independently linked to the risk of GDM. Serum adiponectin \u3c8.9 μg/ml gives an odds ratio of 3.3 for GDM.Mean 1,5 AG levels are significantly lower in those that go on to develop GDM. SHBG levels measured in the first trimester were linked to the risk of GDM. However, this was no longer statistically significant once BMI, ethnicity and family history were taken into consideration. First trimester measurement of CRP is not a useful indicator of GDM risk. Conclusions: First trimester measurement of Adiponectin and 1,5 Anhydroglucitol are potential early biomarkers for the later onset of GDM. Risk stratification using these biomarkers may facilitate early diagnosis and management of GDM to mitigate against its complications

Popular neuroscience: the new frontier, or an exercise in misdirection?

“People often accept inaccurate explanations because they feel right.” Functional neuroimages made their popular debut in a 1983 Vogue magazine article. The headline, ‘High-tech breakthrough in medicine: new seeing-eye machines… look inside your body, can save your life’ was accompanied by a graphic of three brilliantly coloured brains labelled “NORMAL,” “SCHIZO,” and “DEPRESSED”. By presenting the images this way, the magazine’s editors condensed a great deal of cultural content about concepts of human nature into concrete and distinct categories. Placing them next to each other asked the viewer to see their differences as the essential characteristics of the labels that describe them. With no other explanatory text, this display insisted that there are at least three kinds of brain. Viewers were persuaded to equate person with brain, brain with scan, and scan with diagnosis. We tend not to question the effect neuroimages have on us because there is something intuitively right about a machine being able to show us the difference between schizophrenic brains, depressed brains and normal brains. They seem to provide an objective way to distinguish ‘them’ (the mentally abnormal) from ‘us’. Without our realising it, the position of these images against each other compels us to see one as negative and the other as positive. When presented with both, we align the positive with the ideal.</p

First trimester serum biomarkers to predict gestational diabetes in a high-risk cohort: Striving for clinically useful thresholds

Objectives: Screening and diagnosis of gestational diabetes (GDM) has been a source of controversy. The prevalence has increased in line with an obesity epidemic and a trend towards delayed child-bearing. Treatment of even modest glycaemic impairment in pregnancy has been shown to be beneficial in preventing its clinical sequalae. However the cumbersome nature and timing of the oral glucose tolerance test coupled with debate around universal versus risk factor based screening have been problematic. This group aimed to investigate a panel of biomarkers which have shown promise in the literature to predict GDM from the first trimester in a group of high risk women. Methods: Serum samples were drawn on 248 women deemed at risk of GDM before 15 weeks\u27 gestation to measure C-reactive protein, sex hormone binding globulin, adiponectin and 1,5 anhydroglucitol. Patients underwent an oral glucose tolerance test as per IADPSG criteria at 28 weeks\u27 gestation. Multiple logistic regression was used to examine the link between incidence of GDM and early pregnancy serum biomarkers. Results: Adiponectin levels in the first trimester are independently linked to the risk of GDM. Serum adiponectin \u3c8.9 μg/ml gives an odds ratio of 3.3 for GDM.Mean 1,5 AG levels are significantly lower in those that go on to develop GDM. SHBG levels measured in the first trimester were linked to the risk of GDM. However, this was no longer statistically significant once BMI, ethnicity and family history were taken into consideration. First trimester measurement of CRP is not a useful indicator of GDM risk. Conclusions: First trimester measurement of Adiponectin and 1,5 Anhydroglucitol are potential early biomarkers for the later onset of GDM. Risk stratification using these biomarkers may facilitate early diagnosis and management of GDM to mitigate against its complications

Pre-existing traits associated with Covid-19 illness severity

IMPORTANCE: Certain individuals, when infected by SARS-CoV-2, tend to develop the more severe forms of Covid-19 illness for reasons that remain unclear. OBJECTIVE: To determine the demographic and clinical characteristics associated with increased severity of Covid-19 infection. DESIGN: Retrospective observational study. We curated data from the electronic health record, and used multivariable logistic regression to examine the association of pre-existing traits with a Covid-19 illness severity defined by level of required care: need for hospital admission, need for intensive care, and need for intubation. SETTING: A large, multihospital healthcare system in Southern California. PARTICIPANTS: All patients with confirmed Covid-19 infection (N = 442) RESULTS: Of all patients studied, 48% required hospitalization, 17% required intensive care, and 12% required intubation. In multivariable-adjusted analyses, patients requiring a higher levels of care were more likely to be older (OR 1.5 per 10 years, P&lt;0.001), male (OR 2.0, P = 0.001), African American (OR 2.1, P = 0.011), obese (OR 2.0, P = 0.021), with diabetes mellitus (OR 1.8, P = 0.037), and with a higher comorbidity index (OR 1.8 per SD, P&lt;0.001). Several clinical associations were more pronounced in younger compared to older patients (Pinteraction&lt;0.05). Of all hospitalized patients, males required higher levels of care (OR 2.5, P = 0.003) irrespective of age, race, or morbidity profile

Pre-existing traits associated with Covid-19 illness severity

ImportanceCertain individuals, when infected by SARS-CoV-2, tend to develop the more severe forms of Covid-19 illness for reasons that remain unclear.ObjectiveTo determine the demographic and clinical characteristics associated with increased severity of Covid-19 infection.DesignRetrospective observational study. We curated data from the electronic health record, and used multivariable logistic regression to examine the association of pre-existing traits with a Covid-19 illness severity defined by level of required care: need for hospital admission, need for intensive care, and need for intubation.SettingA large, multihospital healthcare system in Southern California.ParticipantsAll patients with confirmed Covid-19 infection (N = 442).ResultsOf all patients studied, 48% required hospitalization, 17% required intensive care, and 12% required intubation. In multivariable-adjusted analyses, patients requiring a higher levels of care were more likely to be older (OR 1.5 per 10 years, P&lt;0.001), male (OR 2.0, P = 0.001), African American (OR 2.1, P = 0.011), obese (OR 2.0, P = 0.021), with diabetes mellitus (OR 1.8, P = 0.037), and with a higher comorbidity index (OR 1.8 per SD, P&lt;0.001). Several clinical associations were more pronounced in younger compared to older patients (Pinteraction&lt;0.05). Of all hospitalized patients, males required higher levels of care (OR 2.5, P = 0.003) irrespective of age, race, or morbidity profile.Conclusions and relevanceIn our healthcare system, greater Covid-19 illness severity is seen in patients who are older, male, African American, obese, with diabetes, and with greater overall comorbidity burden. Certain comorbidities paradoxically augment risk to a greater extent in younger patients. In hospitalized patients, male sex is the main determinant of needing more intensive care. Further investigation is needed to understand the mechanisms underlying these findings