OBJECTIVES: We sought to establish the effects of 1 mo of intermittent fasting on the gut microbiome.
METHODS: We took advantage of intermittent fasting being voluntarily observed during the Islamic faith-associated Ramadan and sampled feces and blood, as well as collected longitudinal physiologic data in 2 cohorts, sampled in 2 different years. The fecal microbiome was determined by 16S sequencing. Results were contrasted to age- and body weight-matched controls and correlated to physiologic parameters (e.g., body mass and calorie intake).
RESULTS: We observed that Ramadan-associated intermittent fasting increased microbiome diversity and was specifically associated with upregulation of the Clostridiales order-derived Lachnospiraceae [no fasting 24.6 ± 13.67 compared with fasting 39.7 ± 15.9 in relative abundance (%); linear discriminant analysis = 4.9, P
METHODS: We developed a prediction model using the classical cross-validation method from the Pan-Asia Trauma Outcomes Study (PATOS) database from 1 January 2015 to 31 December 2020. Eligible patients aged ≥18 years were transported to the hospital by the EMS. The primary outcome (EMS-witnessed TCA) was defined based on changes in vital signs measured on the scene or en route. We included variables that were immediately measurable as potential predictors when EMTs arrived. An integer point value system was built using multivariable logistic regression. The area under the receiver operating characteristic (AUROC) curve and Hosmer-Lemeshow (HL) test were used to examine discrimination and calibration in the derivation and validation cohorts.
RESULTS: In total, 74,844 patients were eligible for database review. The model comprised five prehospital predictors: age <40 years, systolic blood pressure <100 mmHg, respiration rate >20/minute, pulse oximetry <94%, and levels of consciousness to pain or unresponsiveness. The AUROC in the derivation and validation cohorts was 0.767 and 0.782, respectively. The HL test revealed good calibration of the model (p = 0.906).
CONCLUSION: We established a prediction model using variables from the PATOS database and measured them immediately after EMS personnel arrived to predict EMS-witnessed TCA. The model allows prehospital medical personnel to focus on high-risk patients and promptly administer optimal treatment.
METHODS: We conducted a population-based study using data from the Global Cancer Observatory (GLOBOCAN) 2022 and predicted global radiotherapy demands and workforce requirements in 2050. We obtained incidence figures for 29 types of cancer across 183 countries and derived the cancer-specific radiotherapy use rate using the 2013 Collaboration for Cancer Outcomes Research and Evaluation model. We delineated the proportion of people with cancer who require radiotherapy and can be accommodated within the existing installed capacity, assuming an optimal use rate of 50% or 64%, in both 2022 and 2050. A use rate of 50% corresponds to the global average and a use rate of 64% considers potential re-treatment scenarios, as indicated by the 2013 Collaboration for Cancer Outcomes Research and Evaluation (CCORE) radiotherapy use rate model. We established specified requirements for teletherapy units at a ratio of 1:450 patients, for radiation oncologists at a ratio of 1:250 patients, for medical physicists at a ratio of 1:450 patients, and for radiation therapists at a ratio of 1:150 patients in all countries and consistently using these ratios. We collected current country-level data on the radiotherapy-professional workforce from national health reports, oncology societies, or other authorities from 32 countries.
FINDINGS: In 2022, there were an estimated 20·0 million new cancer diagnoses, with approximately 10·0 million new patients needing radiotherapy at an estimated use rate of 50% and 12·8 million at an estimated use rate of 64%. In 2050, GLOBOCAN 2022 data indicated 33·1 million new cancer diagnoses, with 16·5 million new patients needing radiotherapy at an estimated use rate of 50% and 21·2 million at an estimated use rate of 64%. These findings indicate an absolute increase of 8·4 million individuals requiring radiotherapy from 2022 to 2050 at an estimated use rate of 64%; at an estimated use rate of 50%, the absolute increase would be 6·5 million individuals. Asia was estimated to have the highest radiotherapy demand in 2050 (11 119 478 [52·6%] of 21 161 603 people with cancer), followed by Europe (3 564 316 [16·8%]), North America (2 546 826 [12·0%]), Latin America and the Caribbean (1 837 608 [8·7%]), Africa (1 799 348 [8·5%]), and Oceania (294 026 [1·4%]). We estimated that the global radiotherapy workforce in 2022 needed 51 111 radiation oncologists, 28 395 medical physicists, and 85 184 radiation therapists and 84 646 radiation oncologists, 47 026 medical physicists, and 141 077 radiation therapists in 2050. We estimated that the largest proportion of the radiotherapy workforce in 2050 would be in upper-middle-income countries (101 912 [38·8%] of 262 624 global radiotherapy professionals).
INTERPRETATION: Urgent strategies are required to empower the global health-care workforce and facilitate the fundamental human right of access to suitable health care. A collective effort with innovative and cost-contained health-care strategies from all stakeholders is warranted to enhance global accessibility to radiotherapy and address challenges in cancer care.
FUNDING: China Medical Board Global Health Leadership Development Program, Shanghai Science and Technology Committee Fund, China Ministry of Science and Technology Department of International Cooperation High Level Cooperation and Exchange Projects, and Fudan University Office of Global Partnerships Key Projects Development Fund.
TRANSLATIONS: For the Arabic, Chinese, French, Russian and Spanish translations of the summary see Supplementary Materials section.
METHODS: Specific transplant centers from countries in the Asian Society of Transplantation were invited to participate in a study to examine the epidemiology, clinical features, natural history, and outcomes of COVID-19 infections in KTXs. Data were analyzed and compared with those of large cohort studies from other countries.
RESULTS: The study population was 87 KTXs from nine hospitals in seven Asian countries. Within the study population, 9% were aged 60 years and older, and 79% had at least one comorbidity. The majority of patients (69%) presented with mild-to-moderate COVID-19 severity. Disease progression was more frequently encountered among those with moderate or severe infection (23%) and non-survivors (55%). The mortality rate was 23% (n=20) and differed according to the level of care 12% (n=1/8), 15% (n=10/67), and 100% (n=9/9) of patients managed as outpatients, in the general ward, and in the intensive care unit, respectively. Disease severity at the time of presentation was an independent predictor of mortality. Compared with the mortality rates in other studies worldwide, mortality rates in the current study were comparable.
CONCLUSIONS: Mortality in Asian KTXs who were infected with COVID-19 remains high and could be related to comorbidity burden and the constraints of the general healthcare system when the COVID-19 caseload is high.