Causal effects of lung function and COPD on functional outcome following ischemic stroke: a univariable and multivariable Mendelian randomization study

Causal effects of lung function and COPD on functional outcome following ischemic stroke: a univariable and multivariable Mendelian randomization study | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Causal effects of lung function and COPD on functional outcome following ischemic stroke: a univariable and multivariable Mendelian randomization study Wan-ting Sun , Juan Wang , Zhuo-ya Yao , Fang Pan , Zhao-dan Gan , Yun Yang , Jun Lu , Long-yun Zhou , Guang-xu Xu doi: https://doi.org/10.1101/2025.09.03.25335062 Wan-ting Sun 1 School of Rehabilitation Medicine, Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Juan Wang 1 School of Rehabilitation Medicine, Nanjing Medical University , Nanjing, China 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zhuo-ya Yao 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Fang Pan 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zhao-dan Gan 1 School of Rehabilitation Medicine, Nanjing Medical University , Nanjing, China 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yun Yang 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jun Lu 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Long-yun Zhou 1 School of Rehabilitation Medicine, Nanjing Medical University , Nanjing, China 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: xuguangxu{at}njmu.edu.cn lonyunzhou{at}163.com Guang-xu Xu 1 School of Rehabilitation Medicine, Nanjing Medical University , Nanjing, China 2 Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University , Nanjing, China 3 Suzhou Rehabilitation Hospital, Suzhou Hospital Affiliated with Nanjing Medical University , Suzhou, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: xuguangxu{at}njmu.edu.cn lonyunzhou{at}163.com Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Background and Objectives Studies have shown that lung function and chronic obstructive pulmonary disease (COPD) are associated with functional outcome for several diseases, as well as the onset of stroke. However, the causal relationship between lung function, COPD and the functional outcome of ischemic stroke (IS) is unclear. The aim of this study was to investigate the causal relationship between lung function, COPD and IS functional outcomes using Mendelian randomization (MR). Methods Lung function data were derived from the Genome-wide Association Study (GWAS) summary database. Data of COPD were derived from the national genetic factors data repository of the FinnGen project in Finland. The outcome data of IS function were obtained from the Genetics of Ischemic Stroke Functional Outcome (GISCOME) Network. Univariate MR analysis mainly used the inverse variance weighting (IVW) method, MR-Egger, weighted median method and two-sample Maximum Likelihood to evaluate the causal effects of lung function and COPD on the prognosis of IS. Sensitivity analyses were conducted by evaluating heterogeneity and potential pleiotropy. Additionally, multivariable MR analyses were employed to ascertain whether these effects were independent. Results In univariate MR analyses, the estimates of IVW, MR-Egger, weighted median method and two-sample Maximum Likelihood analysis all showed that there was no genetic causal relationship between COPD, FVC, FEV1, FEV1/FVC, PEF and functional outcome after IS (P>0.05). Sensitivity analyses yielded no evidence of directional pleiotropy or substantial heterogeneity. Multivariable MR analyses demonstrated that, after adjustment for insomnia, smoking initiation, waist-to-hip ratio(WHR) or depression, both COPD and PEF exhibited a causal association with adverse functional outcome following IS. Conclusion Our research indicated that at the level of genetic causality, no significant associations were observed between lung function indices (FEV1, FVC, FEV1/FVC, PEF) or COPD and functional outcome following IS. Our discovery may challenge the conventional notion that “improving lung function itself can efficiently promote the prognosis of IS function”. Future research needs to further explore other possible causal pathways and consider various factors comprehensively to develop more effective rehabilitation strategies after IS. Introduction Stroke are major causes of morbidity and mortality worldwide. 1 Approximately 12 million new stroke cases occur globally each year, with 6.55 million deaths attributed to stroke. The comprehensive economic loss caused by ischemic stroke (IS) is estimated at approximately $891 billion per year. 2 , 3 In this context, the incidence rate, disability rate, mortality rate and recurrence rate of stroke in our country are all at high levels, which imposes a heavy economic and social burden on society and families. Furthermore, the prevalence and mortality rates are showing an increasing trend year by year. 4 The proportions of stroke survivors left with varying degrees of motor dysfunction, cognitive impairment and aphasia are 80%, 78.7% and 30%, respectively. Approximately 50% of patients are unable to independently perform daily functional activities three months after the onset of a stroke and up to 40% of patients will face the harsh reality of moderate to severe disability. 5 – 8 IS significantly affects the quality of life of patients, hinders their reintegration into society and imposes unbearable emotional and financial burdens on their families. 9 , 10 It is therefore crucial to investigate the factors associated with the improvement of functional outcome after IS. Lung function tests are primarily used to assess the patency of the airways and the size of lung capacity. 11 , 12 They hold significant clinical value for the early detection of lung and airway lesions, as well as for evaluating the severity of diseases and their functional outcome. 13 – 15 Among others, the main indicators of lung function include: forced vital capacity (FVC), forced expiratory volume in one second (FEV1), the ratio of FEV1 to FVC (FEV1/FVC), the ratio of FEV1 to maximum vital capacity (FEV1/VC MAX) and peak expiratory flow (PEF). The functional outcome of stroke are influenced by various factors, including the type of stroke, age at onset, severity of the condition, rehabilitation training, the psychological state of the patient, lifestyle habits and social support. 16 , 17 Research had found a close connection between lung function and stroke, with common genetic overlap between IS and lung function. 18 Furthermore, individuals with impaired lung function had an increased incidence of IS. 19 The study of Choi suggested that a 4-week program of comprehensive diaphragm training for patients with acute stroke results in significantly greater improvements in lung function and respiratory muscle strength compared to the control group, indicating that diaphragm training may reduce respiratory complications following a stroke. 20 The elevated levels of inflammatory factors in the bodies of chronic obstructive pulmonary disease(COPD) patients not only affect lung function but also impair the recovery of brain tissue through damage to the blood-brain barrier, thereby delaying functional outcome. 21 Given those rational, it is well accepted that improvement of lung function can exert beneficial effects on the functional outcome after IS. However, a few investigations reported a different finding. For instance, Britto observed that following inspiratory muscle training (IMT) in stroke survivors, no statistically significant changes emerged in measures of functional performance or health-related quality of life. 22 Likewise, Vaz demonstrated that although six weeks of IMT improved respiratory muscle strength in IS patients, no corresponding gains were identified in maximal inspiratory pressure, 6-minute-walk-test distance, activities of daily living or quality of life scores. 23 Therefore, can the enhancement of lung function truly be beneficial to the functional outcome after ischemic stroke? Further rigorous investigation may still be required. The Mendelian randomization (MR) method utilizes genetic variations and other non-experimental data as instrumental variables (IVs). 24 MR avoids confounding and reverse causation issues present in traditional observational studies, enhancing the availability of genetic association resources. 25 – 27 The method of MR has been employed to investigate aspects related to functional outcome after stroke, as well as the effects of lung function and COPD on other diseases. 28 – 31 However, there is a gap in MR studies regarding the associations between lung function, COPD and functional outcome after IS. Therefore, this study aims to utilize univariate MR methods to explore the genetic associations between lung function, COPD and functional outcome after IS, providing evidence at the genetic level. Materials and Methods Study Design In this study, we used lung function indicators and COPD as IVs, where the lung function indicators include FEV1, FEV1/FVC, FVC and PEF. The functional outcome of IS would be considered as the outcome variable. A two-sample Mendelian randomization approach was employed to examine the causal association. The research design is shown in Figure. 1 . Download figure Open in new tab Figure 1. The study design, data sources, and flowchart in the present MR study. Outcome data sources We obtained Genome-wide Association Study (GWAS) result files (mRS 0-2 vs 3-6) related to functional outcome after IS from the Genetic of Ischemic Stroke Functional Outcomes (GISCOME) network ( https://kp4cd.org/node/391 ). This network encompasses 12 studies from Europe, Australia and the United States, involving a total of 6021 patients of European ancestry. 32 In these studies, the modified Rankin Scale (mRS) score was assessed both as an ordinal variable and as a binary variable, specifically including two comparison forms: mRS 0-2 vs 3-6 and mRS 0-1 vs 2-6. In the GISCOME study, 33 a total of 3741 patients achieved good functional outcome (mRS 0-2) after IS, whereas 2280 patients experienced poor functional outcome (mRS 3-6). For this analysis, we employed both forms of the 3-month mRS: ordinal mRS and dichotomous mRS (mRS 0-2 vs 3-6). Exposure Data To investigate the genetic associations of lung function, COPD and IS, we obtained relevant data of lung function and COPD from two data resources. Firstly, we accessed the lung function-related GWAS results files (FVC, ieu-b-105; FEV1, ukb-b-11141; FEV1/FVC, ebi-a-GCST007431; PEF, ukb-b-12019) from the IEU OpenGWAS project in the openGWAS summary database ( https://gwas.mrcieu.ac.uk/ ). The GWAS analyses were adjusted for factors such as age, age squared (age 2 ), height and smoking status. Additionally, we retrieved the genetic association summary data (finngen_R12_J10_COPD) for COPD from the latest data release of the national genetic factors data repository of the FinnGen project in Finland ( https://www.finngen.fi/en ). This dataset comprises 433208 samples, with 24138 cases and 409070 controls. Selection of IVs The selection of IVs was completed through a series of quality control procedures: First, among the exposure factors, single-nucleotide polymorphisms(SNPs) with a significance level of P 0.001 criterion within a window size of 10,000 kb. Third, SNPs with an F statistic greater than 10 were retained to mitigate potential bias caused by weak IVs. The calculation formula for the F statistic is: F = (R 2 × (n – k – 1)) / [k × (1 – R 2 )], where R 2 represents the proportion of variance explained by the phenotype, n denotes the effective sample size and k indicates the number of genetic variations. Final, SNPs that exhibited significant associations with the outcomes of interest ( P < 0.05) were excluded to prevent pleiotropic effects. Statistical analysis All statistical analyses were performed using R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). Before the analyses of the causal effects, we firstly performed harmonization of the IVs and outcome variables using the ‘TwoSampleMR’ package. This process involved correcting effect directions and standardizing data formats, thereby ensuring the consistency of genetic association data and laying the foundation for subsequent analyses. The inverse variance weighted (IVW) method served as the primary statistical approach, calculating the overall estimate of genetic effects through a meta-analysis of the Wald estimates from each SNP. 34 Specifically, we weighted the effect sizes of all SNPs by the inverse of the standard error of each SNP (1/SE²) to obtain an overall effect estimate. Furthermore, to assess the robustness of the study results, the weighted median, Two-Sample Maximum Likelihood and MR-Egger methods 35 – 37 were used as auxiliary references for the evaluation of the association between the lung function and the functional outcome following IS. Causal effects were expressed as odds ratios with 95% confidence intervals (CIs). The statistically significant association is defined to be P < 0.05. The MR-Egger regression method was used in the multi-IV pooled-level MR test to evaluate whether there was pleiotropy in the IVs. To further determine whether the intercept of the MR-Egger regression is indeed significant or a false positive, the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) was introduced because MR-PRESSO is shown to be more accurate than the MR-Egger regression. Meanwhile, heterogeneity across instruments was evaluated with the I ² metric and Cochran’ s Q test, and a leave-one-out sensitivity check was carried out to determine whether any single SNP disproportionately influenced the pooled estimate. Moreover, we also conducted multivariable MR analyses to further explore the associations between lung function, COPD and functional outcome following IS by adjusting for the effects of potential confounders. The potential confounders include smoking initiation, depression, insomnia, and waist-to-hip ratio (WHR), which have been shown to be highly associated with both the lung function and the functional outcome after IS. Results Genetic IVs According to the selection criteria for IVs, a total of 856 SNPs were identified as IVs for four lung function indicators and COPD in the analysis using the ordered mRS score and binary mRS score. Detailed information regarding the selected IVs can be found in Tab. 1 . View this table: View inline View popup Download powerpoint Table 2. The univariable MR for assessing the causal effect of COPD and lung function on functional outcome of IS. Univariable MR analyses In univariate MR analyses, the estimates of IVW, MR-Egger, weighted median method and two-sample Maximum Likelihood analysis all showed that there was no significant genetic causal relationship between COPD, FVC, FEV1, FEV1/FVC, PEF and functional outcome after IS ( Tab. 1 , Fig. 2 . P > 0.05). Download figure Open in new tab Figure 2. The forestplot of univariable MR for assessing the causal effect of COPD and lung function on functional outcome of IS. Sensitivity Analyses In our sensitivity analyses, heterogeneity was examined using the I² statistic ( P > 0.05) and Cochran’ s Q test (Q 0.05), indicating no significant heterogeneity among the instrumental variables (IVs) for lung-function measures (FEV1, FVC, FEV1/FVC, PEF) or for COPD. The MR-Egger regression intercept test for directional pleiotropy showed no evidence of potential pleiotropic bias in the MR estimates linking lung function traits and COPD to IS functional outcome (all P > 0.05). Correction with MR-PRESSO likewise revealed no significant horizontal pleiotropy (all P > 0.05). Both MR-Egger and MR-PRESSO detected no material pleiotropic distortion in any of the other causal estimates. Leave-one-out sensitivity analyses demonstrated that no single SNP materially altered the overall causal estimates in any of the univariable MR analyses for the lung-function indices ( Fig. 2 ). Funnel plots from the IVW-based MR analyses exhibited generally symmetrical distributions, indicating the absence of marked small-study bias. Multivariable MR analyses Compared with univariable MR findings, multivariable MR analyses in which COPD was adjusted for insomnia, smoking initiation and depression revealed a potential causal effect on functional outcome after IS ( Tab. 2 ; adjusting for insomnia, β: 0.29, SE: 0.11, OR: 1.34, 95%CI: 1.09-1.65, P = 0.006; adjusting for smoking initiation, β: 0.28, SE: 0.09, OR: 1.32, 95%CI: 1.12-1.57, P = 0.001; adjusting for depression: β: 0.31, SE: 0.12, OR:1.37, 95%CI: 1.08-1.72, P = 0.009). Similarly, PEF adjusted for WHR and insomnia showed an analogous causal association with functional outcome following IS (adjusting for WHR, β: –1.33, SE: 0.42, OR: 0.27, 95%CI: 0.12-0.61, P = 0.002; adjusting for insomnia, β: –0.68, SE: 0.33, OR: 0.51, 95%CI: 0.27-0.98, P = 0.042). These findings indicated a causal relationship between COPD and functional outcome following IS after controlling the effect of insomnia, smoking initiation and depression. PEF also had a causal relationship with functional outcome following IS after controlling the effect of WHR and insomnia. View this table: View inline View popup Download powerpoint Table 2. The multivariable MR for assessing the causal effect of COPD and lung function on functional outcome of IS (ordinal mRS) after adjusting WHR, smoking initiation, depression Discussion It is well accepted that enhancing lung function exerts beneficial effects on the recovery of a wide range of diseases. In this study, we used the MR approach to explore the causal association between lung function, COPD, and functional outcome after IS. By employing genetic variation as IVs, the results of this study revealed no significant genetic causal relationship between lung function (FEV1, FVC, FEV1/FVC and PEF), COPD, and the functional outcome after IS. This study provided evidence at the genetic level that may challenge the commonly held view that enhancing lung function exert beneficial effects on the functional outcome of IS. This finding is significant for re-evaluating the key points in rehabilitation training and the clinical management strategy for patients following IS. It may provide a reference for developing a forward-looking prevention and management strategy that aims to improve the functional outcome following IS. The association among lung function, COPD and functional outcome following IS A substantial amount of observational evidence has consistently indicated that favorable lung function and a low burden of COPD were not only associated with a reduced risk of incident stroke 18 , 19 , 38 – 41 but may also exert a beneficial effect on functional outcome following IS. 19 – 21 , 42 – 45 Proposed mechanisms include improved oxygenation, attenuated systemic inflammation, decreased oxidative stress, preserved endothelial function and maintained coagulation-fibrinolysis homeostasis. 21 , 43 , 46 – 48 Collectively, these studies had reinforced the view that optimizing lung function and controlling COPD represent potentially modifiable therapeutic targets for enhancing functional outcome in patients with IS. However, using MR with genetic variants as IVs to infer causality, our study obtained results that diverge markedly from the above conventional understanding. Univariable MR analyses, including IVW, MR-Egger, weighted median and two-sample maximum-likelihood estimators, uniformly demonstrated no significant causal associations at the genetic level between lung function indices (FEV1, FVC, FEV1/FVC, PEF) or COPD liability and functional outcome following IS assessed by the mRS (all P > 0.05). Consequently, genetically predicted baseline lung function or COPD does not appear to materially influence the extent of neurological recovery following IS. Several potential explanations may account for the negative findings of our univariable MR analyses. First, residual confounding inherent in prior observational studies was likely to have generated spurious associations. Patients with diminished lung function or COPD frequently exhibit a cluster of co-occurring risk factors, such as advanced age, smoking initiation, hypertension, diabetes, obesity, depression, insomnia and others factions. 17 These factors are themselves strong predictive indicators of poor functional outcome following IS. Consequently, the apparent relationship between lung impairment and adverse prognosis may reflect the aggregate influence of these pervasive confounders rather than an independent causal effect of lung function. Our multivariable MR results lend partial support to this interpretation: after adjustment for WHR, smoking initiation, depression and insomnia, COPD and PEF demonstrated associations with functional outcome following IS. This result suggested that the adjusted variables may constitute more proximal determinants or critical mediators of prognosis, while lung indicators (particularly COPD and PEF) largely serve as proxies for the presence of these confounding factors or their downstream effects. Second, clinical respiratory rehabilitation, such as IMT, may improve respiratory muscle strength. 49 , 50 But primarily enhances are dyspnea and exercise tolerance, 51 without necessarily synchronously augmenting cerebral hemodynamics or neural plasticity. 52 , 53 The recovery of neurological function is more dependent on the salvage of the ischemic penumbra, 54 reperfusion time and neuronal plasticity, rather than the lung function itself. Therefore, improvements in lung function and COPD do not have a significant impact on the mRS. Third, MR analysis relies on genetic variations that are closely associated with exposure factors. 55 Although this study selected genetic variations that are strongly linked to lung function indicators and COPD as IVs, these genetic variations may not fully represent the complexity of lung function and COPD. Furthermore, COPD has an intrinsic relationship with lung function measures such as FVC, which may impact the estimation of causal effects. Fourth, The impact of lung function and COPD on functional outcome following IS may involve various biological mechanisms, including inflammatory responses, 56 oxidative stress 40 , 57 and endothelial function. 58 MR analysis primarily focuses on the influence of genetic variations on exposure factors and these genetic variations may not directly participate in the aforementioned biological mechanisms, leading to insignificant causal effects. Strengths and Limitations Through the comprehensive analysis process described above, we have not only validated the causal relationship between lung function, COPD and functional outcome after IS from multiple perspectives, but also enhanced the credibility and robustness of our research findings through cross-validation using various statistical methods. MR provides evidence at the genetic level to make adjustments to the perception of authority. However, this study also had some limitations. First, MR analysis relies on genetic variation as tools for gene prediction, which may not fully represent the complexity of lung function and COPD. Second, the data used in this study was regionally biased, primarily based on data from European ancestry populations. The applicability to other racial groups may be limited. More extensive database support is needed to address the requirements of different regions and ethnicities. Third, this study analyzed the association between the core indicators of lung function (FEV1, FVC, FEV1/FVC, PEF) and the functional outcome following IS. Moreover, there are many other indicators of lung function that were not included in this analysis due to the limitations of current GWAS data. Therefore, in clinical practice, while monitoring and managing the lung function and COPD status of IS patients is crucial for their overall health and rehabilitation participation, the effectiveness of interventions targeting lung function and COPD as a core causal strategy for directly improving stroke functional prognosis may be limited. It is important to consider the concurrent management of confounding factors such as smoking, WHR, depression and insomnia. Our study was merely based on genetic level predictions and future multicenter, high-quality RCTs are needed for validation. Conclusion The results of this study indicated that at the level of genetic causality, no significant associations were observed between lung function indices (FEV1, FVC, FEV1/FVC, PEF) or COPD and functional outcome following IS. Our discovery may challenge the conventional notion that “improving lung function itself can efficiently promote the prognosis of IS function”. This finding offered genetic-level evidence for reevaluating the role of lung function in the functional outcome following IS. It may serve as a reference value for optimizing stroke rehabilitation strategies in clinical practice. However, considering the limitations in the design of our study, the results of this MR study should be interpreted with caution. Data Availability All data in this study were obtained from open access platforms. The IS outcome data is sourced from the GISCOME file (mRS 0-2 vs 3-6) available at https://kp4cd.org/node/391 ; the GWAS results related to lung function (FVC, ieu-b-105; FEV1, ukb-b-11141; FEV1/FVC, ebi-a-GCST007431; PEF, ukb-b-12019) are sourced from the IEU OpenGWAS project ( https://gwas.mrcieu.ac.uk/ ). The COPD data (finngen_R12_J10_COPD) is sourced from https://www.finngen.fi/en . The full set of SNP-exposure and SNP-outcome associations used in the Mendelian randomization analysis is provided in Supplementary materials. Authors’ contributions All authors contributed to analysis, interpretation and final manuscript preparation. WTS and JW contributed to study concept, rationale and initial manuscript drafts. ZYY, FP, ZDG, YY, JL and LYZ contributed to data acquisition and data analysis. LYZ and GXX contributed to project management and personnel arrangement. All authors read and approved the final manuscript. Availability of data and materials All data in this study were obtained from open access platforms. The IS outcome data is sourced from the GISCOME file (mRS 0-2 vs 3-6) available at https://kp4cd.org/node/391 ; the GWAS results related to lung function (FVC, ieu-b-105; FEV1, ukb-b-11141; FEV1/FVC, ebi-a-GCST007431; PEF, ukb-b-12019) are sourced from the IEU OpenGWAS project ( https://gwas.mrcieu.ac.uk/ ). The COPD data (finngen_R12_J10_COPD) is sourced from https://www.finngen.fi/en . Ethics approval and consent to participate Ethical approval and consent was not specifically for this study as we used summary data that is publicly available. Conflicts of interest The authors have no financial conflicts of interest. Acknowledgements We thank the FinnGen, OpenGWAS and GISCOME network for providing summary data for the analyses. Abbreviation COPD chronic obstructive pulmonary disease IS ischemic stroke FVC forced vital capacity FEV1 forced expiratory volume in one second FEV1/FVC the ratio of FEV1 to FVC FEV1/VC MAX the ratio of FEV1 to maximum vital capacity PEF peak expiratory flow MR Mendelian randomization IVs instrumental variables mRS modified Rankin Scale GISCOME Genetic of Ischemic Stroke Functional Outcomes GWAS Genome-wide Association Study SNPs single nucleotide polymorphisms IVW inverse variance weighted MR – PRESSO Mendelian randomization pleiotropy residual sum and outlier WHR waist-to-hip ratio IMT inspiratory muscle training CIs confidence intervals Reference [1]. ↵ GBD 2021 Causes of Death Collaborators . Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 . Lancet . 2024 ; 403 ( 10440 ): 2100 – 2132 . doi: 10.1016/S0140-6736(24)00367-2 OpenUrl CrossRef PubMed [2]. ↵ Thayabaranathan T , Kim J , Cadilhac DA , et al. Global stroke statistics 2022 . Int J Stroke . 2022 ; 17 ( 9 ): 946 – 956 . doi: 10.1177/17474930221123175 OpenUrl CrossRef [3]. ↵ GBD 2019 Stroke Collaborators . Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019 . Lancet Neurol . 2021 ; 20 ( 10 ): 795 – 820 . doi: 10.1016/S1474-4422(21)00252-0 OpenUrl CrossRef PubMed [4]. ↵ The Writing Committee Of The Report On Cardiovascular Health And Diseases In China . Report on Cardiovascular Health and Diseases in China 2022: an Updated Summary . Biomed Environ Sci . 2023 ; 36 ( 8 ): 669 – 701 . doi: 10.3967/bes2023.106 OpenUrl CrossRef PubMed [5]. ↵ Grönberg A , Henriksson I , Stenman M , et al. Incidence of Aphasia in Ischemic Stroke . Neuroepidemiology . 2022 ; 56 ( 3 ): 174 – 182 . doi: 10.1159/000524206 OpenUrl CrossRef PubMed [6]. He A , Wang Z , Wu X , et al. Incidence of post-stroke cognitive impairment in patients with first-ever ischemic stroke: a multicenter cross-sectional study in China . Lancet Reg Health West Pac . 2023 ; 33 : 100687 . doi: 10.1016/j.lanwpc.2023.100687 OpenUrl CrossRef PubMed [7]. Hu SS , The Writing Committee of the Report on Cardiovascular Health and Diseases in China. Epidemiology and current management of cardiovascular disease in China . J Geriatr Cardiol . 2024 ; 21 ( 4 ): 387 – 406 . doi: 10.26599/1671-5411.2024.04.001 OpenUrl CrossRef PubMed [8]. ↵ Everard G , Luc A , Doumas I , et al. Self-Rehabilitation for Post-Stroke Motor Function and Activity-A Systematic Review and Meta-Analysis . Neurorehabil Neural Repair . 2021 ; 35 ( 12 ): 1043 – 1058 . doi: 10.1177/15459683211048773 OpenUrl CrossRef PubMed [9]. ↵ Feigin VL , Owolabi MO , World Stroke Organization – Lancet Neurology Commission Stroke Collaboration Group. Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization-Lancet Neurology Commission . Lancet Neurol . 2023 ; 22 ( 12 ): 1160 – 1206 . doi: 10.1016/S1474-4422(23)00277-6 OpenUrl CrossRef PubMed [10]. ↵ Westendorp WF , Dames C , Nederkoorn PJ , et al. Immunodepression, Infections, and Functional Outcome in Ischemic Stroke . Stroke . 2022 ; 53 ( 5 ): 1438 – 1448 . doi: 10.1161/STROKEAHA.122.038867 OpenUrl CrossRef PubMed [11]. ↵ Pellegrino R , Viegi G , Brusasco V , et al. Interpretative strategies for lung function tests . Eur Respir J . 2005 ; 26 ( 5 ): 948 – 968 . doi: 10.1183/09031936.05.00035205 OpenUrl FREE Full Text [12]. ↵ Liang BM , Lam DCL , Feng YL . Clinical applications of lung function tests: a revisit . Respirology . 2012 ; 17 ( 4 ): 611 – 619 . doi: 10.1111/j.1440-1843.2012.02149.x OpenUrl CrossRef PubMed [13]. ↵ Mahler DA , Wells CK . Evaluation of clinical methods for rating dyspnea . Chest . 1988 ; 93 ( 3 ): 580 – 586 . doi: 10.1378/chest.93.3.580 OpenUrl CrossRef PubMed Web of Science [14]. Lee TY , Sadatsafavi M . Lung function as independent predictor of cardiovascular disease risk: implications for practice and policy . Thorax . 2024 ; 79 ( 3 ): 196 – 197 . doi: 10.1136/thorax-2023-221166 OpenUrl FREE Full Text [15]. ↵ Jiang M , Hao X , Jiang Y , et al. Genetic and observational associations of lung function with gastrointestinal tract diseases: pleiotropic and mendelian randomization analysis . Respir Res . 2023 ; 24 ( 1 ): 315 . doi: 10.1186/s12931-023-02621-0 OpenUrl CrossRef PubMed [16]. ↵ Chen WC , Hsiao MY , Wang TG . Prognostic factors of functional outcome in post-acute stroke in the rehabilitation unit . J Formos Med Assoc . 2022 ; 121 ( 3 ): 670 – 678 . doi: 10.1016/j.jfma.2021.07.009 OpenUrl CrossRef PubMed [17]. ↵ Li Z , Wu WX , Ji ZX , et al. The factors influencing the occurrence of post-ischemic stroke depression and its relationship with the burden score of cerebral small vessel disease . Eur Rev Med Pharmacol Sci . 2024 ; 28 ( 7 ): 2677 – 2685 . doi: 10.26355/eurrev_202404_35896 OpenUrl CrossRef PubMed [18]. ↵ Cai H , Cai B , Liu Z , et al. Genetic correlations and causal inferences in ischemic stroke . J Neurol . 2020 ; 267 ( 7 ): 1980 – 1990 . doi: 10.1007/s00415-020-09786-4 OpenUrl CrossRef PubMed [19]. ↵ Hozawa A , Billings JL , Shahar E , et al. Lung function and ischemic stroke incidence: the Atherosclerosis Risk in Communities study . Chest . 2006 ; 130 ( 6 ): 1642 – 1649 . doi: 10.1378/chest.130.6.1642 OpenUrl CrossRef PubMed Web of Science [20]. ↵ Choi HE , Jo GY , Do HK , et al. Comprehensive Respiratory Muscle Training Improves Pulmonary Function and Respiratory Muscle Strength in Acute Stroke Patients . J Cardiopulm Rehabil Prev . 2021 ; 41 ( 3 ): 166 – 171 . doi: 10.1097/HCR.0000000000000526 OpenUrl CrossRef PubMed [21]. ↵ Holmes MV , Ala-Korpela M . What is ‘LDL cholesterol’? . Nat Rev Cardiol . 2019 ; 16 ( 4 ): 197 – 198 . doi: 10.1038/s41569-019-0157-6 OpenUrl CrossRef PubMed [22]. ↵ Britto RR , Rezende NR , Marinho KC , et al. Inspiratory muscular training in chronic stroke survivors: a randomized controlled trial . Arch Phys Med Rehabil . 2011 ; 92 ( 2 ): 184 – 190 . doi: 10.1016/j.apmr.2010.09.029 OpenUrl CrossRef PubMed [23]. ↵ Vaz LO , Almeida JC , Froes KSDSO , et al. Effects of inspiratory muscle training on walking capacity of individuals after stroke: A double-blind randomized trial . Clin Rehabil . 2021 ; 35 ( 9 ): 1247 – 1256 . doi: 10.1177/0269215521999591 OpenUrl CrossRef PubMed [24]. ↵ Larsson SC , Butterworth AS , Burgess S . Mendelian randomization for cardiovascular diseases: principles and applications . Eur Heart J . 2023 ; 44 ( 47 ): 4913 – 4924 . doi: 10.1093/eurheartj/ehad736 OpenUrl CrossRef PubMed [25]. ↵ Burgess S , Scott RA , Timpson NJ , et al. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors . Eur J Epidemiol . 2015 ; 30 ( 7 ): 543 – 552 . doi: 10.1007/s10654-015-0011-z OpenUrl CrossRef PubMed [26]. Kintu C , Soremekun O , Kamiza AB , et al. The causal effects of lipid traits on kidney function in Africans: bidirectional and multivariable Mendelian-randomization study . EBioMedicine . 2023 ; 90 : 104537 . doi: 10.1016/j.ebiom.2023.104537 OpenUrl CrossRef PubMed [27]. ↵ Smith GD , Ebrahim S . “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol . 2003 ; 32 ( 1 ): 1 – 22 . doi: 10.1093/ije/dyg070 OpenUrl CrossRef PubMed Web of Science [28]. ↵ Prokić I , Lahousse L , de Vries M , et al. A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease . BMC Pulm Med . 2020 ; 20 ( 1 ): 193 . doi: 10.1186/s12890-020-01222-7 OpenUrl CrossRef PubMed [29]. Qu D , Jiang D , Xin Y , et al. Gut microbiota and functional outcome after ischemic stroke: a Mendelian randomization study . Front Immunol . 2024 ; 15 : 1414653 . doi: 10.3389/fimmu.2024.1414653 OpenUrl CrossRef PubMed [30]. Elmore AR , Adhikari N , Hartley AE , et al. Protein Identification for Stroke Progression via Mendelian Randomization in Million Veteran Program and UK Biobank . Stroke . 2024 ; 55 ( 8 ): 2045 – 2054 . doi: 10.1161/STROKEAHA.124.047103 OpenUrl CrossRef PubMed [31]. ↵ Higbee DH , Granell R , Hemani G , et al. Lung function, COPD and cognitive function: a multivariable and two sample Mendelian randomization study . BMC Pulm Med . 2021 ; 21 ( 1 ): 246 . doi: 10.1186/s12890-021-01611-6 OpenUrl CrossRef PubMed [32]. ↵ Söderholm M , Pedersen A , Lorentzen E , et al. Genome-wide association meta-analysis of functional outcome after ischemic stroke . Neurology . 2019 ; 92 ( 12 ): e1271 – e1283 . doi: 10.1212/WNL.0000000000007138 OpenUrl CrossRef PubMed [33]. ↵ Maguire J M , Bevan S , Stanne T M , et al. GISCOME – Genetics of Ischaemic Stroke Functional Outcome network: A protocol for an international multicentre genetic association study . Eur Stroke J . 2017 ; 2 ( 3 ): 229 – 237 . doi: 10.1177/2396987317704547 OpenUrl CrossRef PubMed [34]. ↵ Burgess S , Dudbridge F , Thompson SG . Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods . Stat Med . 2016 ; 35 ( 11 ): 1880 – 1906 . doi: 10.1002/sim.6835 OpenUrl CrossRef PubMed [35]. ↵ Zhao JV , Schooling CM . Using Mendelian randomization study to assess the renal effects of antihypertensive drugs . BMC Med . 2021 ; 19 ( 1 ): 79 . doi: 10.1186/s12916-021-01951-4 OpenUrl CrossRef PubMed [36]. Xu J , Zhang S , Tian Y , et al. Genetic Causal Association between Iron Status and Osteoarthritis: A Two-Sample Mendelian Randomization . Nutrients . 2022 ; 14 ( 18 ): 3683 . doi: 10.3390/nu14183683 OpenUrl CrossRef [37]. ↵ Burgess S , Thompson SG . Interpreting findings from Mendelian randomization using the MR-Egger method . Eur J Epidemiol . 2017 ; 32 ( 5 ): 377 – 389 . doi: 10.1007/s10654-017-0255-x OpenUrl CrossRef [38]. ↵ Teng F , Sun X , Ran Y , et al. Role of Radiation-related Lung Function Genes in Prognosis and Immune Infiltration of Lung Adenocarcinoma . Comb Chem High Throughput Screen . 2025 ; 28 ( 3 ): 487 – 499 . doi: 10.2174/0113862073275640231228124547 OpenUrl CrossRef PubMed [39]. Zhang Y , Wang G , Zhang Q , et al. The value of lung function assessment and Testin expression detection in clinicopathological features and prognosis of NSCLC patients . J Cardiothorac Surg . 2024 ; 19 ( 1 ): 223 . doi: 10.1186/s13019-024-02720-z OpenUrl CrossRef PubMed [40]. ↵ Geltser BI , Kurpatov IG , Dei AA , et al. [Assessment of the respiratory muscles strength at various stages of ischemic stroke] . Zh Nevrol Psikhiatr Im S S Korsakova . 2019 ; 119 ( 3.Vyp.2 ): 83 – 88 . doi: 10.17116/jnevro201911903283 OpenUrl CrossRef [41]. ↵ Ezeugwu VE , Olaogun M , Mbada CE , et al. Comparative lung function performance of stroke survivors and age-matched and sex-matched controls . Physiother Res Int . 2013 ; 18 ( 4 ): 212 – 219 . doi: 10.1002/pri.1547 OpenUrl CrossRef PubMed [42]. ↵ Hayes JD , Flanagan JU , Jowsey IR . Glutathione transferases . Annu Rev Pharmacol Toxicol . 2005 ; 45 : 51 – 88 . doi: 10.1146/annurev.pharmtox.45.120403.095857 OpenUrl CrossRef PubMed Web of Science [43]. ↵ Higbee DH , Granell R , Sanderson E , et al. Lung function and cardiovascular disease: a two-sample Mendelian randomisation study . Eur Respir J . 2021 ; 58 ( 3 ): 2003196 . doi: 10.1183/13993003.03196-2020 OpenUrl Abstract / FREE Full Text [44]. Ortapamuk H , Naldoken S . Brain perfusion abnormalities in chronic obstructive pulmonary disease: comparison with cognitive impairment . Ann Nucl Med . 2006 ; 20 ( 2 ): 99 – 106 . doi: 10.1007/BF02985621 OpenUrl CrossRef PubMed [45]. ↵ Antonelli Incalzi R , Marra C , Giordano A , et al. Cognitive impairment in chronic obstructive pulmonary disease--a neuropsychological and spect study . J Neurol . 2003 ; 250 ( 3 ): 325 – 332 . doi: 10.1007/s00415-003-1005-4 OpenUrl CrossRef PubMed Web of Science [46]. ↵ Hozawa A , Billings JL , Shahar E , et al. Lung function and ischemic stroke incidence: the Atherosclerosis Risk in Communities study . Chest . 2006 ; 130 ( 6 ): 1642 – 1649 . doi: 10.1378/chest.130.6.1642 OpenUrl CrossRef PubMed Web of Science [47]. Truelsen T , Prescott E , Lange P , et al. Lung function and risk of fatal and non-fatal stroke. The Copenhagen City Heart Study . Int J Epidemiol . 2001 ; 30 ( 1 ): 145 – 151 . doi: 10.1093/ije/30.1.145 OpenUrl CrossRef PubMed Web of Science [48]. ↵ Lahousse L , Tiemeier H , Ikram MA , et al. Chronic obstructive pulmonary disease and cerebrovascular disease: A comprehensive review . Respir Med . 2015 ; 109 ( 11 ): 1371 – 1380 . doi: 10.1016/j.rmed.2015.07.014 OpenUrl CrossRef PubMed [49]. ↵ Liu S , Fan Z , Fu M , et al. Impact of inspiratory muscle training on aspiration symptoms in patients with dysphagia following ischemic stroke . Brain Res . 2025 ; 1850 : 149396 . doi: 10.1016/j.brainres.2024.149396 OpenUrl CrossRef PubMed [50]. ↵ Jung JH , Shim JM , Kwon HY , et al. Effects of Abdominal Stimulation during Inspiratory Muscle Training on Respiratory Function of Chronic Stroke Patients . J Phys Ther Sci . 2014 ; 26 ( 1 ): 73 – 76 . doi: 10.1589/jpts.26.73 OpenUrl CrossRef PubMed [51]. ↵ Tovar-Alcaraz A , de Oliveira-Sousa SL , León-Garzón MC , et al. [Effects of inspiratory muscle training on respiratory function and balance in stroke survivors: a randomized controlled trial] . Rev Neurol . 2021 ; 72 ( 4 ): 112 – 120 . doi: 10.33588/rn.7204.2020532 OpenUrl CrossRef PubMed [52]. ↵ Stokowska A , Aswendt M , Zucha D , et al. Complement C3a treatment accelerates recovery after stroke via modulation of astrocyte reactivity and cortical connectivity . J Clin Invest . 2023 ; 133 ( 10 ): e162253 . doi: 10.1172/JCI162253 OpenUrl CrossRef PubMed [53]. ↵ Tsang CK , Mi Q , Su G , et al. Maf1 is an intrinsic suppressor against spontaneous neural repair and functional recovery after ischemic stroke . J Adv Res . 2023 ; 51 : 73 – 90 . doi: 10.1016/j.jare.2022.11.007 OpenUrl CrossRef PubMed [54]. ↵ Denecke KM , McBain CA , Hermes BG , et al. Microfluidic Model to Evaluate Astrocyte Activation in Penumbral Region following Ischemic Stroke . Cells . 2022 ; 11 ( 15 ): 2356 . doi: 10.3390/cells11152356 OpenUrl CrossRef [55]. ↵ Sanderson E . Multivariable Mendelian Randomization and Mediation . Cold Spring Harb Perspect Med . 2021 ; 11 ( 2 ): a038984 . doi: 10.1101/cshperspect.a038984 OpenUrl Abstract / FREE Full Text [56]. ↵ Zhu H , Jian Z , Zhong Y , et al. Janus Kinase Inhibition Ameliorates Ischemic Stroke Injury and Neuroinflammation Through Reducing NLRP3 Inflammasome Activation via JAK2/STAT3 Pathway Inhibition . Front Immunol . 2021 ; 12 : 714943 . doi: 10.3389/fimmu.2021.714943 OpenUrl CrossRef PubMed [57]. ↵ Austin V , Crack PJ , Bozinovski S , et al. COPD and stroke: are systemic inflammation and oxidative stress the missing links? Clin Sci (Lond ). 2016 ; 130 ( 13 ): 1039 – 1050 . doi: 10.1042/CS20160043 OpenUrl Abstract / FREE Full Text [58]. ↵ Voulgaris A , Archontogeorgis K , Steiropoulos P , et al. Cardiovascular Disease in Patients with Chronic Obstructive Pulmonary Disease, Obstructive Sleep Apnoea Syndrome and Overlap Syndrome . Curr Vasc Pharmacol . 2021 ; 19 ( 3 ): 285 – 300 . doi: 10.2174/1570161118666200318103553 OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted September 05, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Causal effects of lung function and COPD on functional outcome following ischemic stroke: a univariable and multivariable Mendelian randomization study Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Causal effects of lung function and COPD on functional outcome following ischemic stroke: a univariable and multivariable Mendelian randomization study Wan-ting Sun , Juan Wang , Zhuo-ya Yao , Fang Pan , Zhao-dan Gan , Yun Yang , Jun Lu , Long-yun Zhou , Guang-xu Xu medRxiv 2025.09.03.25335062; doi: https://doi.org/10.1101/2025.09.03.25335062 Share This Article: Copy Citation Tools Causal effects of lung function and COPD on functional outcome following ischemic stroke: a univariable and multivariable Mendelian randomization study Wan-ting Sun , Juan Wang , Zhuo-ya Yao , Fang Pan , Zhao-dan Gan , Yun Yang , Jun Lu , Long-yun Zhou , Guang-xu Xu medRxiv 2025.09.03.25335062; doi: https://doi.org/10.1101/2025.09.03.25335062 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Rehabilitation Medicine and Physical Therapy Subject Areas All Articles Addiction Medicine (567) Allergy and Immunology (863) Anesthesia (297) Cardiovascular Medicine (4411) Dentistry and Oral Medicine (443) Dermatology (380) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1505) Epidemiology (15205) Forensic Medicine (30) Gastroenterology (1119) Genetic and Genomic Medicine (6574) Geriatric Medicine (666) Health Economics (994) Health Informatics (4511) Health Policy (1365) Health Systems and Quality Improvement (1608) Hematology (537) HIV/AIDS (1263) Infectious Diseases (except HIV/AIDS) (15903) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (665) Neurology (6573) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1139) Occupational and Environmental Health (954) Oncology (3319) Ophthalmology (967) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (662) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5421) Public and Global Health (9205) Radiology and Imaging (2191) Rehabilitation Medicine and Physical Therapy (1367) Respiratory Medicine (1191) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fe875ba5e248e2e',t:'MTc3OTI0OTg5Mw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();