pub2post

@Pub2Post
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Test 1 : 15th May
🌍 Regional Variation - Progress varies, with South Sudan and Burundi focused on infrastructure
πŸ“Š Monitoring - Close evaluation needed to assess benefits and risks

#HIV #NCD #EastAfrica
https://tnyp.me/bEqoVfN6/m

Workspace : Test 2
// 15 May Testing
πŸ”Ž Identify 66 unique variants in RNU6 genes.
#RetinitisPigmentosa #GeneticResearch #NoncodingRNA https://tnyp.me/88HARY97/m

πŸ“’ Insights into early COVID-19 clinical characteristics

A Wuhan-based study explores the clinical features and epidemiology of novel coronavirus-infected pneumonia (NCIP) in

πŸ”— Read more: https://tnyp.me/WWGkouNh/m

Trade-offs in Medical AI

πŸ€– Lack of relevant metrics hinders AI integration.
πŸ”¬Absence of clinical trials affects validation.
πŸ‘₯ Need for patient and physician involvement.

#MedAI #Healthcare #SustainableAI

https://tnyp.me/cSdVDMf8/m

T1
Examining policies for managing T2D and NCDs in Kenya and Tanzania during COVID-19:

Kenya and Tanzania updated NCD policies but gaps remain
Disasters require robust healthcare integration and resource planning
#T2D #NCD #COVID19 #Kenya #Tanzania

https://tnyp.me/bIKdrgBl/m

Policies for type 2 diabetes and non-communicable disease management during the COVID-19 pandemic in Kenya and Tanzania: a desk review and views of decision-makers

Background The COVID-19 pandemic caused disruptions in care that adversely affected the management of non-communicable diseases (NCDs) globally. Countries have responded in various ways to support people with NCDs during the pandemic. This study aimed to identify policy gaps, if any, in the management of NCDs, particularly diabetes, during COVID-19 in Kenya and Tanzania to inform recommendations for priority actions for NCD management during any future similar crises. Methods We undertook a desk review of pre-existing and newly developed national frameworks, policy models and guidelines for addressing NCDs including type 2 diabetes. This was followed by 13 key informant interviews with stakeholders involved in NCD decision-making: six in Kenya and seven in Tanzania. Thematic analysis was used to analyse the documents. Results Seventeen guidance documents were identified (Kenya=10; Tanzania=7). These included pre-existing and/or updated policies/strategic plans, guidelines, a letter, a policy brief and a report. Neither country had comprehensive policies/guidelines to ensure continuity of NCD care before the COVID-19 pandemic. However, efforts were made to update pre-existing documents and several more were developed during the pandemic to guide NCD care. Some measures were put in place during the COVID-19 period to ensure continuity of care for patients with NCDs such as longer supply of medicines. Inadequate attention was given to monitoring and evaluation and implementation issues. Conclusion Kenya and Tanzania developed and updated some policies/guidelines to include continuity of care in emergencies. However, there were gaps in the documents and between policy/guideline documents and practice. Health systems need to establish disaster preparedness plans that integrate attention to NCD care to enable them to better handle severe disruptions caused by emergencies such as pandemics. Such guidance needs to include contingency planning to enable adequate resources for NCD care and must also address evaluation of implementation effectiveness. Data are available upon reasonable request. Only the qualitative data can be made available upon reasonable request. All other relevant data are available publicly.

BMJ Open

T 2

Impact of 3D-Printed Models in RCC with VTE:
πŸ₯ Reduced surgical complications by 28% (OR: 5.40)
https://tnyp.me/zIbdmx0q/m

Study of NLCS Impact on ASR Performance:
πŸ“Š 135,647 words analyzed, 3284 NLCS (2.4%)
❓ 76 NLCS used for key info (0.06%)
πŸ” WER: Google 11.8%, Amazon 12.8%
⚠️ NLCS misrecognized at 40.8% (Google), 57.2% (Amazon)
#ASR #ClinicalDocumentation #PatientSafety https://tnyp.me/uTyoMoyV/m
Comparative trial on AI scribes easing documentation burden:
πŸ“‰ 38% of notes used ambient AI
πŸ₯ Work exhaustion reduced by 0.44 points
⏰ Documentation time decreased by 0.36 hours/day
πŸ” Diagnostic coding accuracy improved
#AI #Healthcare #Burnout https://tnyp.me/JrTZkSzb/m