A new tool to assess Clinical Diversity In Meta‐analyses (CDIM) of interventions

OBJECTIVE: To develop and validate Clinical Diversity In Meta-analyses (CDIM), a new tool for assessing clinical diversity between trials in meta-analyses of interventions.STUDY DESIGN AND SETTING: The development of CDIM was based on consensus work informed by empirical literature and expertise. We drafted the CDIM tool, refined it, and validated CDIM for interrater scale reliability and agreement in three groups.RESULTS: CDIM measures clinical diversity on a scale that includes four domains with 11 items overall: setting (time of conduct/country development status/units type); population (age, sex, patient inclusion criteria/baseline disease severity, comorbidities); interventions (intervention intensity/strength/duration of intervention, timing, control intervention, cointerventions); and outcome (definition of outcome, timing of outcome assessment). The CDIM is completed in two steps: first two authors independently assess clinical diversity in the four domains. Second, after agreeing upon scores of individual items a consensus score is achieved. Interrater scale reliability and agreement ranged from moderate to almost perfect depending on the type of raters.CONCLUSION: CDIM is the first tool developed for assessing clinical diversity in meta-analyses of interventions. We found CDIM to be a reliable tool for assessing clinical diversity among trials in meta-analysis.</p

Addressing the CO₂ emissions of the world's largest coal producer and consumer: lessons from the Haishiwan Coalfield, China

China is now the world's largest user of coal, and also has the highest greenhouse gas emissions associated with the mining and use of coal. In the mining sector, the interests of workforce safety coincide with those of GHG (greenhouse gas) management. While the traditional approach to ensuring workforce safety in coal mines was simply to vent the hazardous gases to the atmosphere, thus increasing GHG emissions, recent innovations have seen elements of CCS (carbon capture and storage) being used to simultaneously ensure workforce safety and minimization of GHG emissions. The Haishiwan Coalfield represents a particularly challenging environment for applying this approach, as the coal-bearing strata host both oil shales and a naturally-occurring CO2 reservoir, disturbance of which could both imperil workers and lead to elevated GHG emissions. A low-carbon, CCS-based model of gas management developed in the Haishiwan Coalfield offers attractive lessons for application to other coal mines, within and beyond China. This approach achieves multiple benefits: energy production, enhanced workforce safety and minimization of GHG emissions. Given the extreme nature of the Haishiwan case, it ought to be even easier to implement these approaches elsewhere

A new tool to assess Clinical Diversity In Meta-analyses (CDIM) of interventions

OBJECTIVE: To develop and validate Clinical Diversity In Meta-analyses (CDIM), a new tool for assessing clinical diversity between trials in meta-analyses of interventions. STUDY DESIGN AND SETTING: The development of CDIM was based on consensus work informed by empirical literature and expertise. We drafted the CDIM tool, refined it, and validated CDIM for interrater scale reliability and agreement in three groups. RESULTS: CDIM measures clinical diversity on a scale that includes four domains with 11 items overall: setting (time of conduct/country development status/units type); population (age, sex, patient inclusion criteria/baseline disease severity, comorbidities); interventions (intervention intensity/strength/duration of intervention, timing, control intervention, cointerventions); and outcome (definition of outcome, timing of outcome assessment). The CDIM is completed in two steps: first two authors independently assess clinical diversity in the four domains. Second, after agreeing upon scores of individual items a consensus score is achieved. Interrater scale reliability and agreement ranged from moderate to almost perfect depending on the type of raters. CONCLUSION: CDIM is the first tool developed for assessing clinical diversity in meta-analyses of interventions. We found CDIM to be a reliable tool for assessing clinical diversity among trials in meta-analysis