Testing effectiveness of the revised Cape Town modified early warning and SBAR systems: a pilot pragmatic parallel group randomised controlled trial

CT-based radiomics signature of visceral adipose tissue and bowel lesions for identifying patients with Crohn's disease resistant to infliximab

PURPOSE

To develop a CT-based radiomics model combining with VAT and bowel features to improve the predictive efficacy of IFX therapy on the basis of bowel model.

METHODS

This retrospective study included 231 CD patients (training cohort, n = 112; internal validation cohort, n = 48; external validation cohort, n = 71) from two tertiary centers. Machine-learning VAT model and bowel model were developed separately to identify CD patients with primary nonresponse to IFX. A comprehensive model incorporating VAT and bowel radiomics features was further established to verify whether CT features extracted from VAT would improve the predictive efficacy of bowel model. Area under the curve (AUC) and decision curve analysis were used to compare the prediction performance. Clinical utility was assessed by integrated differentiation improvement (IDI).

RESULTS

VAT model and bowel model exhibited comparable performance for identifying patients with primary nonresponse in both internal (AUC: VAT model vs bowel model, 0.737 (95% CI, 0.590-0.854) vs. 0.832 (95% CI, 0.750-0.896)) and external validation cohort [AUC: VAT model vs. bowel model, 0.714 (95% CI, 0.595-0.815) vs. 0.799 (95% CI, 0.687-0.885)), exhibiting a relatively good net benefit. The comprehensive model incorporating VAT into bowel model yielded a satisfactory predictive efficacy in both internal (AUC, 0.840 (95% CI, 0.706-0.930)) and external validation cohort (AUC, 0.833 (95% CI, 0.726-0.911)), significantly better than bowel alone (IDI = 4.2% and 3.7% in internal and external validation cohorts, both p < 0.05).

CONCLUSION

VAT has an effect on IFX treatment response. It improves the performance for identification of CD patients at high risk of primary nonresponse to IFX therapy with selected features from RM.

CRITICAL RELEVANCE STATEMENT

Our radiomics model (RM) for VAT-bowel analysis captured the pathophysiological changes occurring in VAT and whole bowel lesion, which could help to identify CD patients who would not response to infliximab at the beginning of therapy.

KEY POINTS

• Radiomics signatures with VAT and bowel alone or in combination predicting infliximab efficacy. • VAT features contribute to the prediction of IFX treatment efficacy. • Comprehensive model improved the performance compared with the bowel model alone.

Pulse oximetry training landscape for healthcare workers in low- and middle-income countries: A scoping review

Background

Pulse oximetry has been used in medical care for decades. Its use quickly became standard of care in high resource settings, with delayed widespread availability and use in lower resource settings. Pulse oximetry training initiatives have been ongoing for years, but a map of the literature describing such initiatives among health care workers in low- and middle-income countries (LMICs) has not previously been conducted. Additionally, the coronavirus disease 2019 (COVID-19) pandemic further highlighted the inequitable distribution of pulse oximetry use and training. We aimed to characterise the landscape of pulse oximetry training for health care workers in LMICs prior to the COVID-19 pandemic as described in the literature.

Methods

We systematically searched six databases to identify studies reporting pulse oximetry training among health care workers, broadly defined, in LMICs prior to the COVID-19 pandemic. Two reviewers independently assessed titles and abstracts and relevant full texts for eligibility. Data were charted by one author and reviewed for accuracy by a second. We synthesised the results using a narrative synthesis.

Results

A total of 7423 studies were identified and 182 screened in full. A total of 55 training initiatives in 42 countries met inclusion criteria, as described in 66 studies since some included studies reported on different aspects of the same training initiative. Five overarching reasons for conducting pulse oximetry training were identified: 1) anaesthesia and perioperative care, 2) respiratory support programme expansion, 3) perinatal assessment and monitoring, 4) assessment and monitoring of children and 5) assessment and monitoring of adults. Educational programmes varied in their purpose with respect to the types of patients being targeted, the health care workers being instructed, and the depth of pulse oximetry specific training.

Conclusions

Pulse oximetry training initiatives have been ongoing for decades for a variety of purposes, utilising a multitude of approaches to equip health care workers with tools to improve patient care. It is important that these initiatives continue as pulse oximetry availability and knowledge gaps remain. Neither pulse oximetry provision nor training alone is enough to bolster patient care, but sustainable solutions for both must be considered to meet the needs of both health care workers and patients.

The effectiveness of education strategies for nurses to recognise and manage clinical deterioration: A systematic review

OBJECTIVES

To identify, critically appraise and synthesise evidence on the efficacy of education strategies for nurses to recognise and manage clinical deterioration, as well as provide recommendations for standardised educational programmes.

DESIGN

A systematic review of quantitative studies.

METHODS

Quantitative studies published in English between 1 January 2010 and 14 February 2022 were chosen from nine databases. Studies were included if they reported education strategies for nurses to recognise and manage clinical deterioration. The quality appraisal was performed using the Quality Assessment Tool for Quantitative Studies, developed by the Effective Public Health Practice Project. The data were extracted and the findings were integrated into a narrative synthesis.

RESULTS

Altogether, 37 studies published in 39 eligible papers were included in this review, encompassing 3632 nurses. Most education strategies were determined to be effective, and outcome measures can be divided into three types: nurse outcomes; system outcomes; and patient outcomes. The education strategies could be divided into simulation and non-simulation interventions, and six interventions were in-situ simulations. Retention of knowledge and skills during the follow-up after education was determined in nine studies, with the longest follow-up interval totalling 12 months.

CONCLUSIONS

Education strategies can improve nurses' ability and practice to recognise and manage clinical deterioration. Simulation combined with a structured prebrief and debrief design can be viewed as a routine simulation procedure. Regular in-situ education determined long-term efficacy in response to clinical deterioration, and future studies can use an education framework to guide regular education practice and focus more on nurses' practice and patient outcomes.

Wavelet Transform Artificial Intelligence Algorithm-Based Data Mining Technology for Norovirus Monitoring and Early Warning

Norovirus monitoring and early warning can be used for diagnosis without etiological testing, and the treatment of this disease does not require the antibiotics. It often occurs in preschool children and affects their growth and development, so the coping measures for this disease are more prevention than treatment. In this study, the clinical data of 2133 children with diarrhea were collected. Based on the artificial intelligence (AI) algorithm of wavelet transform, a related model for data mining and processing of children's intestinal ultrasound images and stool specimens was constructed. Then, the norovirus infection trend was warned based on the wavelet analysis algorithm model. The results showed that the intestinal ultrasound image processed by the wavelet transform algorithm was clearer. The positive detection rate of norovirus in children with clinical diarrhea was as high as 59%, and the children had different degrees of body damage, of which the probability of compensatory metabolic acidosis was the highest. The epidemiological analysis found that children with norovirus infection were mainly concentrated in the age group under 2 years old and over 5 years old and showed a peak of infection in December. In summary, the intelligent algorithm based on wavelet transform can realize the noise reduction of intestinal ultrasound, and it should protect children with susceptible age and susceptible seasons to reduce the clinical infection rate of norovirus.