The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

멘델 무작위화(Mendelian randomization, MR) 연구는 조절 가능한 노출(modifiable exposure)이 건강결과에 미치는 인과효과(causal effect)를 더 잘 이해하게 해 주지만, 그 근거는 종종 보고가 불충분함으로 인하여연구 결과의 해석과 적용에 한계가 있을 수 있다. 보고지침은 흔히 무슨 연구를 하고 무엇을 발견했는지 독자가 쉽게 이해하도록 돕는다. STROBE-MR(관찰연구의 멘델 무작위화를 활용한 보고지침)은 MR 연구를 명확하고 투명하게 보고하도록 돕는다. STROBE-MR을 논문 작성에 활용하면 독자, 심사자, 학술지 편집인이 MR 연구의 보고 품질과 완성도를 평가하는 데 도움이 될 것이다. 이 글은 STROBE-MR 체크리스트 20개 항목의 의미와 근거를 설명하고, 각 항목마다 사례를 제시해 독자가 잘 이해할 수 있는 논문 작성법을 설명하려고 하였다.

Purpose: Prostate cancer (PCa) screening can lead to potential over-diagnosis/over-treatment of indolent cancers. There is a need to optimize practices to better risk-stratify patients. We examined initial longitudinal outcomes of mid-life men with an elevated baseline prostate-specific antigen (PSA) following initiation of a novel screening program within a system-wide network. Materials and Methods: We assessed our primary care network patients ages 40 to 49 years with a PSA measured following implementation of an electronic health record screening algorithm from 2/2/2017–2/21/2018. The multidisciplinary algorithm was developed taking factors including age, race, family history, and PSA into consideration to provide a personalized approach to urology referral to be used with shared decision-making. Outcomes of men with PSA ≥1.5 ng/mL were evaluated through 7/2021. Statistical analyses identified factors associated with PCa detection. Clinically significant PCa (csPCa) was defined as Gleason Grade Group (GGG) ≥2 or GGG1 with PSA ≥10 ng/mL. Results: The study cohort contained 564 patients, with 330 (58.5%) referred to urology for elevated PSA. Forty-nine (8.7%) underwent biopsy; of these, 20 (40.8%) returned with PCa. Eleven (2.0% of total cohort and 55% of PCa diagnoses) had csPCa. Early referral timing (odds ratio [OR], 4.58) and higher PSA (OR, 1.07) were significantly associated with PCa at biopsy on multivariable analysis (both p<0.05), while other risk factors were not. Referred patients had higher mean PSAs (2.97 vs. 1.98, p=0.001). Conclusions Preliminary outcomes following implementation of a multidisciplinary screening algorithm identified PCa in a small, important percentage of men in their forties. These results provide insight into baseline PSA measurement to provide early risk stratification and detection of csPCa in patients with otherwise extended life expectancy. Further follow-up is needed to possibly determine the prognostic significance of such mid-life screening and optimize primary care physician-urologist coordination.

INTRODUCTION: The COVID-19 pandemic forced Philippine medical schools to adapt their curriculum design to fit an online setup. This study aimed to analyze and interpret the lived experiences of medical students who experienced online learning during the COVID-19 pandemic and to explore the adaptations to online learning. METHODS: This is an interpretive phenomenological study using purposive sampling. Participants were 1st to 3rd year medical students enrolled for Academic Year 2020-2021. Participants were interviewed online by a psychologist who was not part of the research team using a 13-question guide. The interviews were recorded and transcribed. Interview data were analyzed and interpreted using interpretative phenomenological analysis (IPA). RESULTS: Nine medical students were interviewed. The IPA identified six superordinate themes: 1) positive adaptations through positive reframing; 2) resulting mental health concerns; 3) intrinsic and extrinsic concerns encountered; 4) self-awareness as a first step towards adjustment; 5) dual role of family; and 6) perceptions on systemic response. CONCLUSION Online medical education during the pandemic resulted in problems and mental health concerns among participants, and many developed self-awareness and positive adaptations specific to the online setup. Participants’ families helped some adjust, while others posed an additional challenge. Both positive and negative perceptions of the systemic response of the school also arose.

BACKGROUND AND PURPOSE: Prediction of intracranial aneurysm growth risk can assist physicians in planning of follow-up imaging of conservatively managed unruptured intracranial aneurysms. We therefore aimed to externally validate the ELAPSS (Earlier subarachnoid hemorrhage, aneurysm Location, Age, Population, aneurysm Size and Shape) score for prediction of the risk of unruptured intracranial aneurysm growth. METHODS: From 11 international cohorts of patients ≥18 years with ≥1 unruptured intracranial aneurysm and ≥6 months of radiological follow-up, we collected data on the predictors of the ELAPSS score, and calculated 3- and 5-year absolute growth risks according to the score. Model performance was assessed in terms of calibration (predicted versus observed risk) and discrimination (c-statistic). RESULTS: We included 1,072 patients with a total of 1,452 aneurysms. During 4,268 aneurysm-years of follow-up, 199 (14%) aneurysms enlarged. Calibration was comparable to that of the development cohort with the overall observed risks within the range of the expected risks. The c-statistic was 0.69 (95% confidence interval [CI], 0.64 to 0.73) at 3 years, compared to 0.72 (95% CI, 0.68 to 0.76) in the development cohort. At 5 years, the c-statistic was 0.68 (95% CI, 0.64 to 0.72), compared to 0.72 (95% CI, 0.68 to 0.75) in the development cohort. CONCLUSIONS: The ELAPSS score showed accurate calibration for 3- and 5-year risks of aneurysm growth and modest discrimination in our external validation cohort. This indicates that the score is externally valid and could assist patients and physicians in predicting growth of unruptured intracranial aneurysms and plan follow-up imaging accordingly.
Aneurysm ; Calibration ; Cohort Studies ; Discrimination (Psychology) ; Follow-Up Studies ; Humans ; Intracranial Aneurysm ; Risk Factors ; Subarachnoid Hemorrhage