
A new report has provided a stepwise framework for allowing nonessential visitors to accompany patients to outpatient appointments, such as screening ultrasound scans. The document from National Health Service (NHS) England and NHS Improvement gives practical advice for reintroducing partners into labor and maternity care appointments.
The 8 September document covers risk assessment for allowing visitors in antenatal and postnatal inpatient and outpatient settings. It was written in conjunction with the U.K. Royal College of Obstetrics and Gynaecologists, Royal College of Midwives, and the Society and College of Radiographers (SCoR).
"Reintroducing visits is challenging during a pandemic, and the priority must be the safety of all service users (including pregnant women), staff, and visitors," the guidelines stated.
The guidelines provide a stepwise framework for allowing nonessential visitors to accompany patients to outpatient appointments, such screening ultrasound scans. The approach includes the following steps:
- Essential visitors only and single adults for consultations that may cause distress
- One adult for specific appointments, including antenatal, screening ultrasound scans, early pregnancy, antenatal or postnatal complications, birth planning, unscheduled attendances to maternity triage
- One adult for any appointment type
- Phased reintroduction of usual visiting policies, if different from the above
The guidelines also provide a similar stepwise approach for labor and birth settings and antenatal and postnatal inpatient settings. NHS England and NHS Improvement plan to review the document in November 2020.
In a release, the SCoR said it is addressing sonographer concerns related to risk assessments, including room size, physical distancing for partners, examination times, waiting room capacity, and ventilation. The society also emphasized the importance of applying a consistent approach when reintroducing partners.
"We would like to thank sonographers and other healthcare professionals for continuing to provide a safe and effective antenatal ultrasound service in addition to a wide range of nonobstetric services under challenging circumstances," the society wrote.

















![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)
