Diagnosis
Why gestational diabetes underdiagnosis is a women’s health crisis
By James Jackson, CEO at Digostics
Gestational diabetes (GDM) is one of the most under-recognised challenges in maternity care today.
Despite affecting around one in five pregnancies in the UK, GDM remains a blind spot in policy and practice, with devastating consequences for women and their children.
New research continues to expose the scale of the problem.
A recent NIHR-funded study published in Diabetic Medicine found that standard NHS testing methods miss over 50 per cent of cases.
Put simply: thousands of women each year go undiagnosed, untreated, and exposed to avoidable risks.
For a condition we know how to diagnose and manage, this represents a serious failure in women’s healthcare.
The human cost of missed diagnosis
When gestational diabetes is not picked up, the consequences are immediate and long-term.
During pregnancy, women face higher risks of preeclampsia, larger babies, emergency C-sections, and stillbirth. Babies are more likely to need neonatal intensive care due to breathing difficulties or low blood sugar.
The risks don’t end at birth.
Mothers who have had GDM are up to 50 per cent more likely to develop type 2 diabetes within 5–10 years. Their children also face an increased lifetime risk of obesity and diabetes.
These outcomes are not rare, nor are they inevitable. They are the product of a testing system that is not fit for purpose.
An unequal system
Current UK pathways rely on risk-factor–based screening rather than universal testing.
James Jackson
This already puts women at a disadvantage compared with countries such as Spain, Italy, and many others, where all pregnant women are routinely screened.
But even within this narrower approach, the NHS faces a further problem: in-clinic oral glucose tolerance tests (OGTTs), used to test for GDM, are prone to delays in blood sample processing, leading to false negatives.
Research shows that when samples are processed correctly diagnoses increase from 9 per cent to 22 per cent — more than double.
The burden of this diagnostic failure falls hardest on women from disadvantaged backgrounds.
Attending early-morning, hospital-based tests is more difficult for women juggling shift work, childcare, or long travel times.
Women from ethnic minority groups, who already face higher rates of maternal complications, are also more likely to be missed. In this way, testing failures are not just a clinical problem but a driver of health inequalities.
The case for innovation
This is where innovation can play a transformative role.
We have seen in other areas of healthcare — from remote monitoring to home blood pressure checks — how new approaches can increase accuracy, improve access, and reduce inequalities.
Gestational diabetes testing should be no different. Technologies such as at-home oral glucose tolerance tests (OGTTs) are designed to meet the same clinical standards as hospital testing, while overcoming the practical barriers of travel, fasting, and sample degradation.
By enabling women to test from home, results can be processed immediately and shared directly with care teams, reducing missed cases and ensuring timely diagnosis.
Early work with NHS Trusts has already shown that this model not only identifies more cases but also improves access for diverse patient groups, including those typically underserved.
From evidence to action
Despite clear data, progress has been slow. Part of the challenge is that more accurate testing uncovers more cases — and more cases mean more workload for already stretched maternity services.
But failing to diagnose does not make the problem go away; it only delays care and worsens outcomes.
In the long run, undiagnosed gestational diabetes costs the NHS more through emergency interventions, neonatal intensive care, later-life type 2 diabetes, and the ongoing workload and cost pressures this creates for primary care.
The evidence is clear. Now it must translate into policy. That means:
- Recognising underdiagnosis as a patient safety issue on par with other maternity scandals.
- Guaranteeing that all women offered testing receive accurate, reliable results, rather than being failed by flawed processes.
- Supporting innovation that improves accuracy and equity, whether in the clinic or at home.
- Embedding the patient voice in service design, especially from women in disadvantaged and minority communities most affected by current failures.
A call to prioritise women’s health
Gestational diabetes is not a niche concern; it is a mainstream women’s health issue with lifelong consequences.
Every undiagnosed case represents not just a missed number, but a mother at risk of preeclampsia or birth trauma, a baby at risk of intensive care, or a family facing preventable illness later in life.
As maternity services undergo yet another review, it is striking that the diagnostic gap in GDM remains so little discussed.
We cannot claim to be serious about women’s health while ignoring one of the most widespread and preventable sources of harm in pregnancy.
Innovation has a role to play — but innovation must be matched by policy will.
If we are to modernise maternity care, we must start by ensuring that every woman has access to accurate, timely, and equitable testing for gestational diabetes.
Because every mother deserves certainty. And every baby deserves the best start in life.
AI may help speed breast cancer diagnosis for high-risk women after abnormal mammograms, a study suggests.
Women with abnormal mammograms often wait weeks to learn whether they have breast cancer.
Researchers at UC San Francisco and UC Berkeley said an AI-guided workflow could help reduce that wait by quickly identifying those most likely to have the disease. Some women could move from imaging to evaluation, and sometimes biopsy, in a single day.
Dr Maggie Chung, first author of the study, said: “This is a really an exciting time.
“This moves us closer to personalised care, where we can tailor a plan so that each patient gets the right intervention at the right time.”
The study used an open-source AI model called Mirai.
The model was trained on hundreds of thousands of mammograms linked to patients’ cancer outcomes.
A mammogram is an X-ray scan of the breast used to look for signs of cancer. A biopsy involves taking a small tissue sample to test for disease.
The AI tool is designed to detect subtle patterns in screening mammograms and predict a woman’s cancer risk.
Researchers at UC San Francisco and UC Berkeley applied the model to more than 4,100 screening mammograms at Zuckerberg San Francisco General Hospital and Trauma Center.
Mirai identified 525 women, about 12.7 per cent of screened patients, as high risk.
Those patients could receive an interpretation of their mammograms immediately after the scan and have additional diagnostic imaging for suspicious areas on the same day.
Some women who needed biopsies were also able to have them on the same day.
The researchers said Mirai reduced the wait time for diagnostic evaluation from several weeks to about an hour.
For women who were ultimately diagnosed with breast cancer, it reduced the average wait for biopsy from more than two months to fewer than 10 days.
The researchers stressed that Mirai does not replace radiologists or make diagnoses on its own.
Instead, it acts as a triage tool to help physicians identify the patients who can benefit most from accelerated care.
The team analysed more than 114,000 archival mammograms before launching the programme, to ensure the model would capture enough high-risk patients without overloading the clinic with too many expedited evaluations.
The researchers said they hope AI will support a more personalised approach to breast cancer screening tailored to each patient’s breast cancer risk.
Chung said: “Right now, many women follow the same screening schedule but their individual risk can be very different.
“AI risk assessment gives us the chance to identify the women most likely to benefit from expedited care and get them what they need.”
Adam Yala, senior author of the study and a data scientist at UC Berkeley, said: “This is a powerful example of how AI can be a collaborative partner for physicians.
“It shows how we can improve care when we bring clinicians and data scientists together to design these systems.”
Type 2 diabetes diagnoses are rising twice as fast in women under 40 as in women over 40, new data shows.
Type 2 diabetes is a serious condition and can lead to complications such as heart attacks and strokes. When it develops in younger people, it can be more aggressive and have more severe and acute effects.
Diagnoses in women under 40 rose by 47 per cent between 2017/18 and 2023/24. By comparison, diagnoses rose by 22 per cent in women aged 40 to 79.
During the same period, type 2 diabetes diagnoses in men under 40 increased by 34 per cent.
Diabetes UK said it is concerned about the follow-up care offered to women who have had gestational diabetes, also known as GDM, which increases the risk of developing type 2 diabetes after pregnancy.
Gestational diabetes is high blood sugar that develops during pregnancy and usually goes away after birth, but it raises the risk of type 2 diabetes later.
Colette Marshall, chief executive at Diabetes UK, said: “These figures should be a wake-up call. Type 2 diabetes is rising twice as fast in younger women compared to older women, and a crucial opportunity for prevention is being missed. Every diagnosis is life-changing, but when it develops in younger people, type 2 diabetes is even more aggressive.
“Pregnancy shouldn’t be a pathway to ill health. Yet despite facing a much higher risk of type 2 diabetes, too many women with GDM receive little or no follow-up care after pregnancy.
“As the Government turns its Strategy into action, support for women who have had gestational diabetes must not be overlooked.”
Last year, the NHS published the first national GDM audit for England in 2024/25, which revealed inconsistencies in follow-up care.
Only 57 per cent of women with GDM received an annual HbA1c test, which should be offered to every woman with GDM.
An HbA1c test measures average blood sugar levels over the previous two to three months.
Only 4.5 per cent of women had received support through the NHS Diabetes Prevention Programme.
The report also found that 11 per cent of women developed prediabetes within five years of having GDM, while 15 per cent developed type 2 diabetes within 10 years.
Prediabetes means blood sugar levels are higher than normal and a person has a higher risk of developing type 2 diabetes.
A recent survey funded by Diabetes UK also found that more than a third of women with GDM felt abandoned by healthcare services after giving birth.
If you live in England and have had gestational diabetes, you can self-refer to the NHS Diabetes Prevention Programme, which supports people at risk of developing type 2 diabetes. If you live in Northern Ireland, Scotland or Wales, you can speak to your GP about support.
Diabetes UK has written to women’s health minister Baroness Merron calling for urgent improvements to postnatal support for those diagnosed with GDM during pregnancy.
GDM affects between 10 and 20 per cent of pregnant women, but Diabetes UK said cases have long been underreported and UK-wide data on the condition has not been readily available.
The charity said poor follow-up care for women who have had GDM may be contributing to rising rates of type 2 diabetes in younger women.
It is calling for consistent postnatal follow-ups for women after GDM, more referrals to the NHS Diabetes Prevention Programme, greater accountability for improvements in postnatal care, and action on inequalities affecting women from deprived and minority ethnic communities.
A genomic test may help some women with breast cancer avoid chemotherapy, with near-identical outcomes in an international trial.
The findings suggest patients with a low test score could be treated with hormone therapy alone without increasing the risk of their cancer returning.
Researchers said the results could support more personalised treatment decisions and spare some women the side-effects of chemotherapy.
Prof Rob Stein, the trial’s chief investigator and a professor of breast oncology at UCL, said: “Optima addresses a longstanding challenge in breast cancer care: identifying who truly benefits from chemotherapy and who does not.
“Our findings show that many patients can safely avoid chemotherapy without compromising their outcomes.
“These results mark an important and significant step toward more personalised treatment.
“The trial has successfully used tumour biology to guide decisions rather than relying solely on traditional clinical features.”
Breast cancer treatment usually involves surgery to remove tumours. Chemotherapy is then often recommended if doctors believe there is a risk the disease will return.
Chemotherapy can cause side-effects including hair loss, rashes, nausea, insomnia and fatigue. Some women may also face longer-term consequences such as infertility, cognitive impairment or early menopause.
The Optima trial followed more than 4,000 patients with newly diagnosed breast cancer in the UK, Norway, Sweden, Australia, New Zealand and Thailand.
The trial was led by University College London.
One woman who took part in the trial told the Guardian that being able to skip chemotherapy felt “like Christmas”. Nine years after being diagnosed, taking the test and skipping chemotherapy, she is healthy and enjoying a full and active life.
The trial tested whether a genomic test could identify which patients need chemotherapy and which could safely avoid it.
The Prosigna test, made by diagnostics company Veracyte, analyses the activity of 50 genes in tumour tissue. It identifies the molecular subtype of the cancer and gives a score estimating the risk of breast cancer returning in the next 10 years.
The randomised trial involved 4,429 patients aged 40 or over with hormone-positive breast cancer. Hormone-positive breast cancer grows in response to hormones such as oestrogen or progesterone. It is the most common form of breast cancer, accounting for up to 80 per cent of cases globally.
Participants were assigned to one of two groups. In the standard treatment group, patients received chemotherapy followed by hormone therapy.
In the second group, patients had their tumours analysed using the genomic test. Those with a high score received chemotherapy and hormone therapy. Those with a low score received hormone therapy alone.
Radiotherapy and other treatments were given as usual in both groups.
In the second group, outcomes were very similar whether chemotherapy was given or not. Five years after treatment, 95 per cent of patients who had chemotherapy and hormone therapy were alive and free from breast cancer recurrence, while 94 per cent of those who skipped chemotherapy were also alive and recurrence-free.
The findings suggest chemotherapy offered little or no additional benefit for patients with low test scores.
Some men also took part in the study, but researchers said there were too few to draw firm conclusions for this group.
The trial received funding from the National Institute for Health and Care Research, Veracyte and cancer charities.
Prof Iain MacPherson, a co-chief investigator and professor of breast oncology at the University of Glasgow, said: “Optima provides robust, practice-changing evidence that we can safely reduce the use of chemotherapy for many patients with hormone-sensitive breast cancer.
“These findings represent a major step forward in delivering more personalised, precise care, ensuring that treatment decisions are driven by what will genuinely improve outcomes for patients, while avoiding unnecessary toxicity.
“The potential impact for both patients and health services is substantial.”
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