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This study aimed to develop and validate a machine-learning (ML) model to predict iron deficiency without anaemia (IDWA) using routinely collected electronic health record (EHR) data. The primary hypothesis was that an ML model could achieve better accuracy in identifying low ferritin levels (
A retrospective cohort study.
Data were derived from secondary and tertiary care facilities within the eight-hospital Mount Sinai Health System, an urban academic health system.
The study included 211 486 adult patients (aged ≥18 years) with normal haemoglobin levels (≥130 g/L for men and ≥120 g/L for women) and recorded ferritin measurements.
The primary outcome was the prediction of low ferritin levels (
Data from 211 486 Mount Sinai Health System patients with normal haemoglobin levels and ferritin testing were analysed. The model used demographic data, blood count indices and chemistry results to identify low ferritin levels (
Of the 211 486 patients analysed, 19.56% (n=41 368) of the patients had low ferritin levels. In the low ferritin group, the mean age was 41.28 years with 89.64% females. In contrast, the normal ferritin group had a mean age of 50.14 years with 62.02% females. The model achieved an area under the curve (AUC) of 0.814. At a sensitivity threshold of 70%, the model had a specificity of 75.85%, with a positive predictive value of 37.6% and a negative predictive value of 92.41%. The model outperformed an alternative model based only on complete blood count indices (AUC 0.814 vs 0.741). Subgroup analysis showed that model accuracy varied by sex and age, with lower performance in premenopausal women (AUC 0.736) compared with postmenopausal women (AUC 0.793) and men (AUC of 0.832 in those under 60 years and 0.806 in those aged 60 and above).
The ML model provides an effective approach to screening for IDWA using readily available EHR data. Implementing this tool in clinical settings may facilitate early diagnosis of IDWA.
This study aimed to assess the proportion of nutrition-related information-seeking behaviour and its associated factors among pregnant women attending antenatal care at public hospitals in Bahir Dar City, northwest Ethiopia, 2023.
A cross-sectional quantitative supplemented with qualitative study design was conducted from March to April 2023 among 406 pregnant women. Pre-tested structured interviewer-administered and semistructured open-ended questionnaires were used to collect quantitative and qualitative data, respectively. Data were collected using the Kobo toolbox, and SPSS V.25 was used for analysis. Descriptive statistics were used to describe study subjects, and multivariate logistic regression analysis was employed to investigate the associated factors. The strength of associations was described using the OR with the corresponding 95% CI.
The study included 406 pregnant mothers with a median age of 28 with an IQR of 8 and 212 (52.2%) from rural settings. Of the total respondents, 173 (42.6%; 95% CI 37.7 to 47.6) of pregnant mothers were nutrition-related information seekers. Educational status, residence, monthly income and nutrition information literacy were significantly associated with nutrition-related information-seeking behaviour.
The proportion of nutrition information seeking among pregnant mothers in Bahir Dar City public hospitals was low. Lower educational status, low nutrition information literacy level, being from a rural residence and low monthly income are significantly associated factors.
Awareness creation for pregnant mothers from rural areas and with low educational status and improving nutrition information literacy of pregnant mothers are important activities to improve their nutrition information-seeking behaviour.
This study explored the experience of stigma and access to healthcare by persons with long COVID from the majority Dutch and two ethnic minority populations (Turkish and Moroccan) living in the Netherlands.
This was a cross-sectional qualitative study that employed inductive and deductive thematic approaches to data analysis using MAXQDA.
Between October 2022 and January 2023, 23 semi-structured interviews were conducted with participants of Dutch, Moroccan and Turkish ethnic origins with long COVID living in the Netherlands. Participants were men and women aged 30 years and above.
Guided by the concepts of stigma and candidacy, the findings are structured according to the broader themes of stigma and access to care. The findings show that people with long COVID suffer self and public stigma resulting from the debilitating illness and symptoms. Especially among Turkish and Moroccan ethnic minority participants, strong filial obligations and gendered expectations of responsibility and support within their communities further worsen self-stigma. This experience of stigma persisted within healthcare where lack of information and appropriate care pathways led to feelings of frustration and abandonment, especially for participants with pre-existing health conditions which further complicate candidacy. Under the access to healthcare theme, the findings show multiple challenges in accessing healthcare for long COVID due to several multifaceted factors related to the various stages of candidacy which impacted access to care. Particularly for Turkish and Moroccan ethnic minority participants, additional challenges resulting from limited access to information, pre-existing structural challenges and experience of stereotyping based on ethnicity or assumed migrant identity by health professionals further complicate access to health information and long COVID care.
The findings call for urgent attention and research to identify and coordinate healthcare for long COVID. There is also a need for accessible, informative and tailored support systems to facilitate patients’ access to information and care pathways for long COVID. Providing tailored information and support, addressing the various barriers that hinder optimal operating conditions in healthcare and leveraging on social networks is crucial for addressing stigma and facilitating candidacy for persons with long COVID towards improving access to care.
Targeted oxygenation protocols in mechanically ventilated patients are critical in avoiding the deleterious effects of hypoxaemia and hyperoxaemia. Peripheral oxygen saturation (SpO2) is a practical metric that commonly drives oxygen titration protocols and guidelines but has inaccuracies attributable to patient variability that can lead to occult hypoxaemia. Conversely, arterial oxygen saturation (SaO2) offers accuracy but is costly and invasive. We aim to develop a novel approach to targeted oxygenation that collectively uses the accuracy of SaO2 and the feasibility of SpO2 to mitigate occult hypoxaemia and prevent hyperoxaemia.
The Optimization of Inspired Oxygen during Mechanical Ventilation trial is a pragmatic stepped wedge, open label, cluster-randomised controlled trial of an algorithm-based SpO2-SaO2 electronic alert-based oxygen titration protocol. The intervention arm includes targeted oxygenation via an electronic SpO2-SaO2 driven alert protocol. The control group will be subjected to oxygen titration according to standard practice. Within the intervention arm, patients will be assigned to groups with different SpO2 targets based on the degree of SpO2-SaO2 difference. In the ‘Conserve O2’ group, where SpO2
The protocol was approved by The Ohio State University Institutional Review Board (Protocol # 2023H0016) and is registered at ClinicalTrials.gov (NCT 05923853). Progress and safety of the trial are monitored by an independent Data and Safety Monitoring Board. Study results will be published in peer-reviewed medical journals. This study is being carried out with a waiver of consent as participation in the study presents no more than minimal incremental risk compared with routine clinical care for mechanically ventilated critically ill adults outside of the study.
Paediatric cervical spine injury (CSI) is uncommon but can have devastating consequences. Many children, however, present to emergency departments (EDs) for the assessment of possible CSI. While imaging can be used to determine the presence of injuries, these tests are not without risks and costs, including exposure to radiation and associated life-time cancer risks. Clinical decision rules (CDRs) to guide imaging decisions exist, although two of the existing rules, the National Emergency X-Radiography Low Risk Criteria and the Canadian C-Spine Rule (CCR), focus on adults and a newly developed paediatric rule from the Pediatric Emergency Care Applied Research Network (PECARN) is yet to be externally validated. This study aims to externally validate these three CDRs in children.
This is a multicentre prospective observational study of children younger than 16 years presenting with possible CSI following blunt trauma to 1 of 14 EDs across Australia, New Zealand and Singapore. Data will be collected on presenting features (history, injury mechanism, physical examination findings) and management (diagnostic imaging, admission, interventions, outcomes). The performance accuracy (sensitivity, specificity, negative and positive predictive values) of three existing CDRs in identifying children with study-defined CSIs and the specific CDR defined outcomes will be determined, along with multiple secondary outcomes including CSI epidemiology, investigations and management of possible CSI.
Ethics approval for the study was received from the Royal Children’s Hospital Melbourne Human Research Ethics Committee in Australia (HREC/69436/RCHM-2020) with additional approvals from the New Zealand Human and Disability Ethics Committee and the SingHealth Centralised Institutional Review Board. Findings will be disseminated through peer-reviewed publications and future management guidelines.
Registration with the Australian New Zealand Clinical Trials Registry prior to the commencement of participant recruitment (ACTRN12621001050842). 50% of expected patients have been enrolled to date.
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