Are respiratory physicians adherent to guidelines when evaluating pulmonary nodules?

Intervertebral disc degeneration (IVDD) is a predominant underlying cause of low back pain, a condition that imposes a staggering global socioeconomic burden and is a leading contributor to years lived with disability worldwide [, ]. The pathophysiology of IVDD is multifactorial, involving a complex interplay of genetic predisposition, mechanical stress, inflammatory processes, and metabolic disturbances [, ]. Despite its high prevalence, the modifiable risk factors and causal mechanisms driving IVDD progression remain incompletely elucidated, hampering the development of effective preventive and therapeutic strategies. Traditional observational studies have identified numerous associations between various exposures—such as obesity, lifestyle habits, and biochemical traits—and IVDD risk [, ]. However, inferring causality from these associations is notoriously challenging due to residual confounding and reverse causation []. Mendelian randomization (MR) has emerged as a powerful methodological approach to address these limitations. By using genetic variants as instrumental variables for exposures, MR can provide more reliable evidence for causal inferences, as genetic alleles are randomly assigned at conception and are generally independent of confounding environmental factors [, ]. The application of MR has rapidly expanded in the field of IVDD, with recent studies investigating the causal roles of a wide spectrum of factors [, ]. Nevertheless, the evidence from individual MR studies is often fragmented and sometimes inconsistent. These discrepancies may arise from differences in statistical power, genetic instrument selection, population ancestry, or methodological heterogeneity. A meta-analysis of MR studies offers a robust means of synthesizing these findings, enhancing statistical power and providing more precise and generalizable causal estimates [, ].