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Burden and predictors of age-related macular degeneration among old age patients with diabetes attending comprehensive specialised hospitals in Northwest Ethiopia: a multicentre cross-sectional prospective study

Por: Shumye · A. F. · Desalegn · G. K. · Tegegn · M. T. · Worku · E. M. · Lorato · M. M. · Bogale · Z. M. · Tegegne · M. M. · Alimaw · Y. A. · Mengistu · H. G. · Bekele · M. M. · Bayabil · A. Z. · Birhan · G. S. · Eticha · B. L.
Objective

This study aims to assess the burden and predictors of age-related macular degeneration (AMD) among older age patients with diabetes attending comprehensive specialised hospitals in Northwest Ethiopia.

Design

A multicentre cross-sectional study was conducted among older patients with diabetes using a systematic random sampling technique.

Setting

The study was conducted at five comprehensive specialised hospitals in Northwest Ethiopia from 8 May to 8 June 2023.

Participants

The study included 832 diabetic individuals aged 40 years and above.

Main outcome measures

Data were collected using a pretested structured questionnaire and physical examinations.

Result

In this study, a total of 832 participants were involved, with a response rate of 96.85%. The burden of AMD was 15.4% (95% CI 13.0% to 18.0%). Male sex (adjusted OR (AOR) 2.04, 95% CI 1.17 to 3.56), older age (AOR 6.91, 95% CI 3.17 to 15.08), diabetes duration of 10 and more years (AOR 3.00, 95% CI 1.91 to 4.69), higher body mass index (AOR 2.56, 95% CI 1.15 to 5.71), presence of hypertension (AOR 2.45, 95% CI 1.56 to 3.85) and family history of diabetes mellitus (DM) (AOR 2.29, 95% CI 1.40 to 3.76) were positively associated with AMD.

Conclusions

This study found that the prevalence of AMD among patients with diabetes was 15.4%. Older age, male sex, longer DM duration, higher body mass index, presence of hypertension and family history of DM were significantly associated with AMD. Targeted screening of at-risk individuals for AMD, public health awareness campaigns focusing on these factors and further research to understand the burden and underlying mechanisms of these associations with AMD are recommended.

Adverse pregnancy outcomes and associated factors among mothers who had operative vaginal delivery in Amhara Region Comprehensive Specialized Hospitals: multicentre cross-sectional study

Por: Misker · A. D. · Melesew · A. A. · Gobezie · N. Z. · Wubet · H. B. · Diress · G. M. · Abuhay · A. G. · Demite · D. G. · Tadesse · M. A. · Mihretie · G. N. · Abate · A. T. · Asmare · T. B. · Goshu · Y. A. · Siyoum · T. M. · Mekuriaw · B. Y. · Gedefaw · G. D. · Kebede · S. D. · Demissie
Objective

Assess the magnitude of adverse pregnancy outcomes and associated factors among mothers who had operative vaginal delivery in Amhara Region Comprehensive Specialized Hospitals, 2024.

Study design

A cross-sectional study was conducted from 1 November 2024 to 20 February 2025.

Study setting

Seven comprehensive specialised hospitals were included in the study.

Participants

The study was employed on 389 mothers who had operative vaginal delivery.

Methods

Systematic sampling was used. Data were collected via questionnaires, chart reviews and observation. Data were entered into Epi Data V.4.6 and analysed using V.25 statistical package of social sciences. Variables with p

Outcome

Adverse pregnancy outcomes of operative vaginal delivery.

Results

Adverse pregnancy outcomes of operative vaginal delivery were 42.2%. Among them, 46 (11.8%) had only maternal complications, 55 (14.1%) had only neonatal complications and 63 (16.2%) had both maternal and neonatal complications. Perineal tear 29 (7.5%) and episiotomy extension 31 (8%) were the most common maternal complications, while caput succedaneum 45 (11.6%) was the most neonatal complication. The most common indication of operative vaginal delivery was prolonged second stage 203 (52.2%). Vacuum-assisted delivery (AOR 0.53; 95% CI 0.29 to 0.96), two tractions (AOR 2.19; 95% CI 1.23 to 3.90), birth weight less than 2.5 kg (AOR 1.85; 95% CI 1.21 to 2.83) and mid fetal station (AOR 2.9; 95% CI 1.49 to 5.64) were significantly associated with adverse pregnancy outcomes.

Conclusions

Adverse pregnancy outcomes following operative vaginal delivery were high. Type of instrumental vaginal delivery, number of tractions, fetal birth weight and fetal station were significantly increased risks. Therefore, operators should minimise traction attempts during operative vaginal delivery to reduce adverse outcomes.

Time to full recovery and its predictors among children with complicated severe acute malnutrition admitted to inpatient and subsequently to outpatient therapeutic care, Sanaa city, Yemen, a prospective follow-up study

Por: Al Amad · M. A. · Rajaa · Y. A. · Algendari · K.
Objective

To determine the time to full recovery and its predictors among children with severe acute malnutrition (SAM) admitted to therapeutic feeding centres (TFCs) in Sana’a, Yemen.

Design

A prospective cohort study conducted from August 2023 to November 2024.

Setting

Two public hospitals in Sana’a City (Al-Sabeen and Al-Zubairi hospital) that provide therapeutic feeding services for children with SAM.

Participants

Children aged 6–59 months who were admitted to TFCs based on WHO SAM criteria and successfully transferred to outpatient therapeutic programmes (OTPs).

Outcome measures

The primary outcome was time to full recovery from SAM, defined as the normalisation of both weight-for-height z-score (WHZ) and mid-upper arm circumference (MUAC). Secondary outcomes included identification of predictors associated with recovery time.

Results

Among 267 children, 51% were aged 6 to

Conclusion

Three months and a half were the median time to full recovery from complicated SAM. Concurrent WHZ and MUAC deficits, antibiotic use and the absence of diarrhoea were the significant predictors. Standardising the use of combined WHZ and MUAC recovery is recommended to improve comparability across programmes and better reflect nutritional outcomes.

Integrating artificial intelligence and machine learning in nursing practice: opportunities, methods and challenges

Por: Chen · L.-Y. A.
Introduction

Artificial intelligence (AI), defined as the simulation of human intelligence in machines designed to replicate human cognitive processes, is becoming increasingly prevalent in nursing practice and research. Recent reviews have examined the application of AI across various nursing domains, highlighting its role in clinical decision support, administrative efficiency and educational advancements.1 2

AI techniques, including machine learning and natural language processing, are being employed to address a range of clinical, managerial and educational challenges in nursing.2–4 These advancements have demonstrated potential in improving patient monitoring, optimising workload distribution and supporting clinical decision-making.2 5 However, despite AI’s increasing presence in nursing practice, a structured framework guiding its integration remains non-existent.

Machine learning, a core component of AI, is instrumental in various nursing applications. It enables pattern recognition and predictive analysis through the examination of...

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