GRADE-ADOLOPMENT of clinical practice guidelines and creation of clinical pathways for the primary care management of chronic respiratory conditions in Pakistan.

INTRODUCTION: In Pakistan, chronic respiratory conditions contribute a large burden of morbidity and mortality. A major reason for this is the lack of availability of local evidence-based clinical practice guidelines (EBCPGs) in Pakistan, particularly at the primary care level. Thus, we developed EBCPGs and created clinical diagnosis and referral pathways for the primary care management of chronic respiratory conditions in Pakistan. METHODS: The source guidelines were selected by two local expert pulmonologists after a thorough literature review on PubMed and Google Scholar from 2010 to December 2021. The source guidelines covered idiopathic pulmonary fibrosis, asthma, chronic obstructive pulmonary disorders, and bronchiectasis. The GRADE-ADOLOPMENT process consists of three key elements: adoption (using recommendations as is or with minor changes), adaptation (effective context-specific changes to recommendations) or additions (including new recommendations to fill a gap in the EBCPG). We employed the GRADE-ADOLOPMENT process to adopt, adapt, adopt with minor changes, or exclude recommendations from a source guideline. Additional recommendations were added to the clinical pathways based on a best-evidence review process. RESULTS: 46 recommendations were excluded mainly due to the unavailability of recommended management in Pakistan and scope beyond the practice of general physicians. Clinical diagnosis and referral pathways were designed for the four chronic respiratory conditions, explicitly delineating the role of primary care practitioners in the diagnosis, basic management, and timely referral of patients. Across the four conditions, 18 recommendations were added (seven for IPF, three for bronchiectasis, four for COPD, and four for asthma). CONCLUSION: The widespread use of the newly created EBCPGs and clinical pathways in the primary healthcare system of Pakistan can help alleviate the morbidity and mortality related to chronic respiratory conditions disease in the country.

An fMRI framework for identifying statistical differences in blood oxygenated level dependent response levels: a brain injury demonstration.

OBJECTIVE: The general concept surrounding fMRI data analysis for decision support is leveraging previously hidden knowledge from publicly available metadata sources with a high degree of precision. METHODS AND MATERIALS: Normalized fMRI scans are used to calculate cumulative voxel intensity curves for every subject in the dataset that fits chosen demographic criteria. The voxel intensity curve has a direct linear relationship to the subject's neuronal activity. In the case of head trauma, a subject's voxel intensity curve would be statistically compared to the weighted average curve for every subject in dataset that is demographically similar. If the new subject's neuronal activity falls below the threshold for their demographic group, the brain injury detection (BID) system would then pinpoint the areas of deficiency based on Broadmann's cortical areas. ANALYSIS: The analysis presented in this paper indicates that statistical differences among demographic groups exist in BOLD fMRI responses. CONCLUSION: Useful knowledge can in fact be leveraged from mining stockpiled fMRI data without the need for unique human identifiers. The BID system offers the radiologist a statistically based decision support for brain injury.