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The feasibility and acceptability of self-testing for proteinuria during pregnancy: A mixed methods approach.
The feasibility and acceptability of self-testing for proteinuria during pregnancy: A mixed methods approach.
OBJECTIVE: To investigate feasibility and acceptability of self-testing for proteinuria during pregnancy. STUDY DESIGN: Mixed methods approach which included: an accuracy study where pregnant women (n = 100) and healthcare professionals (n = 96) tested seven synthetic protein samples and completed a questionnaire, a feasibility study where pregnant women who were self-monitoring their blood pressure were asked to self-test for proteinuria (n = 30), and an online questionnaire about women's experiences of self-testing (n = 200). MAIN OUTCOME MEASURES: Sensitivity and specificity of testing and questionnaire results. RESULTS: There were no significant differences in the accuracy of synthetic sample testing by pregnant women (sensitivity 0.81 (95% confidence intervals (CI) 0.78-0.85), specificity 0.93 (95% CI 0.91-0.95)) and healthcare professionals: (sensitivity 0.83 (95% CI 0.79-0.86), specificity 0.92 (95% CI 0.90-0.94)). Automated readers had significantly better sensitivity (0.94 (0.91-0.97) (p ≤ .001 in each case), but worse specificity 0.78 (0.69-0.85). Similar results were gained using self-tested urine samples compared to staff-testing using a reference standard of laboratory urine protein-creatinine ratio (uPCR). Women who completed the online survey with experience of self-testing (n = 39, 20%) generally found it easy, and with support from healthcare professionals felt it improved involvement in their care and reduced anxiety. CONCLUSIONS: Self-testing for proteinuria by pregnant women had similar accuracy to healthcare professional testing and was acceptable to both groups. Self-testing of urine combined with self-monitoring of blood pressure could provide a useful adjunct to clinic-based surveillance for the detection of pre-eclampsia. Such novel strategies warrant further research
Whole-genome sequencing reveals host factors underlying critical COVID-19
Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease