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Adverse Effects of Cannabinoids and Tobacco Consumption on the Cardiovascular System: A Systematic Review
review-article
Author(s):
Anas A Abu Jad
1
,
,
Anvesh Ravanavena
1 ,
Chetna Ravindra
2 ,
Emmanuelar O Igweonu-Nwakile
1 ,
Safina Ali
1 ,
Salomi Paul
1 ,
Shreyas Yakkali
1 ,
Sneha Teresa Selvin
1 ,
Sonu Thomas
1 ,
Viktoriya Bikeyeva
1 ,
Ahmed Abdullah
1 ,
Aleksandra Radivojevic
1 ,
Prachi Balani
1
Publication date (Electronic, pub):
15 September 2022
Publication date (Electronic, collection):
September 2022
Journal:
Cureus
Publisher:
Cureus
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Abstract
With the recent legalization of marijuana in several countries for recreational use, a controversial belief is spreading about it being "safe". In this systematic review, we decided to investigate this belief and present the adverse effects of marijuana and tobacco smoking on the cardiovascular system.
We carried out an electronic search on databases including PubMed, PubMed Central, and Medline. Medical Subject Headings (MeSH) terms and different keywords were used for data collection. We included studies published in the last 10 years that were in English. All types of study subjects were accepted. Grey literature, books, case reports and case series, overlapping and duplicate studies, and studies older than 10 years were excluded.
In this review, we included 18 studies, which we then separated into the "tobacco and cardiovascular disease" arm and the "cannabinoids and cardiovascular disease" arm. We had 11 and seven studies for each of the arms, respectively. The types of articles included in this review were traditional and systematic reviews and meta-analyses.
After reviewing all the data included in this article, we found out that cannabinoid consumption has a more devastating effect on the cardiovascular system when compared to tobacco. The shocking fact was that in several cases, deadly adverse effects were observed in patients within a few hours after consumption or even during their first time using cannabinoids.
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Most cited references20
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The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews. In order to encourage its wide dissemination this article is freely accessible on BMJ, PLOS Medicine, Journal of Clinical Epidemiology and International Journal of Surgery journal websites. Systematic reviews serve many critical roles. They can provide syntheses of the state of knowledge in a field, from which future research priorities can be identified; they can address questions that otherwise could not be answered by individual studies; they can identify problems in primary research that should be rectified in future studies; and they can generate or evaluate theories about how or why phenomena occur. Systematic reviews therefore generate various types of knowledge for different users of reviews (such as patients, healthcare providers, researchers, and policy makers) [1, 2]. To ensure a systematic review is valuable to users, authors should prepare a transparent, complete, and accurate account of why the review was done, what they did (such as how studies were identified and selected) and what they found (such as characteristics of contributing studies and results of meta-analyses). Up-to-date reporting guidance facilitates authors achieving this [3]. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement published in 2009 (hereafter referred to as PRISMA 2009) [4–10] is a reporting guideline designed to address poor reporting of systematic reviews [11]. The PRISMA 2009 statement comprised a checklist of 27 items recommended for reporting in systematic reviews and an “explanation and elaboration” paper [12–16] providing additional reporting guidance for each item, along with exemplars of reporting. The recommendations have been widely endorsed and adopted, as evidenced by its co-publication in multiple journals, citation in over 60,000 reports (Scopus, August 2020), endorsement from almost 200 journals and systematic review organisations, and adoption in various disciplines. Evidence from observational studies suggests that use of the PRISMA 2009 statement is associated with more complete reporting of systematic reviews [17–20], although more could be done to improve adherence to the guideline [21]. Many innovations in the conduct of systematic reviews have occurred since publication of the PRISMA 2009 statement. For example, technological advances have enabled the use of natural language processing and machine learning to identify relevant evidence [22–24], methods have been proposed to synthesise and present findings when meta-analysis is not possible or appropriate [25–27], and new methods have been developed to assess the risk of bias in results of included studies [28, 29]. Evidence on sources of bias in systematic reviews has accrued, culminating in the development of new tools to appraise the conduct of systematic reviews [30, 31]. Terminology used to describe particular review processes has also evolved, as in the shift from assessing “quality” to assessing “certainty” in the body of evidence [32]. In addition, the publishing landscape has transformed, with multiple avenues now available for registering and disseminating systematic review protocols [33, 34], disseminating reports of systematic reviews, and sharing data and materials, such as preprint servers and publicly accessible repositories. To capture these advances in the reporting of systematic reviews necessitated an update to the PRISMA 2009 statement. Summary points • To ensure a systematic review is valuable to users, authors should prepare a transparent, complete, and accurate account of why the review was done, what they did, and what they found • The PRISMA 2020 statement provides updated reporting guidance for systematic reviews that reflects advances in methods to identify, select, appraise, and synthesise studies • The PRISMA 2020 statement consists of a 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and revised flow diagrams for original and updated reviews • We anticipate that the PRISMA 2020 statement will benefit authors, editors, and peer reviewers of systematic reviews, and different users of reviews, including guideline developers, policy makers, healthcare providers, patients, and other stakeholders Development of PRISMA 2020 A complete description of the methods used to develop PRISMA 2020 is available elsewhere [35]. We identified PRISMA 2009 items that were often reported incompletely by examining the results of studies investigating the transparency of reporting of published reviews [17, 21, 36, 37]. We identified possible modifications to the PRISMA 2009 statement by reviewing 60 documents providing reporting guidance for systematic reviews (including reporting guidelines, handbooks, tools, and meta-research studies) [38]. These reviews of the literature were used to inform the content of a survey with suggested possible modifications to the 27 items in PRISMA 2009 and possible additional items. Respondents were asked whether they believed we should keep each PRISMA 2009 item as is, modify it, or remove it, and whether we should add each additional item. Systematic review methodologists and journal editors were invited to complete the online survey (110 of 220 invited responded). We discussed proposed content and wording of the PRISMA 2020 statement, as informed by the review and survey results, at a 21-member, two-day, in-person meeting in September 2018 in Edinburgh, Scotland. Throughout 2019 and 2020, we circulated an initial draft and five revisions of the checklist and explanation and elaboration paper to co-authors for feedback. In April 2020, we invited 22 systematic reviewers who had expressed interest in providing feedback on the PRISMA 2020 checklist to share their views (via an online survey) on the layout and terminology used in a preliminary version of the checklist. Feedback was received from 15 individuals and considered by the first author, and any revisions deemed necessary were incorporated before the final version was approved and endorsed by all co-authors. The PRISMA 2020 statement Scope of the guideline The PRISMA 2020 statement has been designed primarily for systematic reviews of studies that evaluate the effects of health interventions, irrespective of the design of the included studies. However, the checklist items are applicable to reports of systematic reviews evaluating other interventions (such as social or educational interventions), and many items are applicable to systematic reviews with objectives other than evaluating interventions (such as evaluating aetiology, prevalence, or prognosis). PRISMA 2020 is intended for use in systematic reviews that include synthesis (such as pairwise meta-analysis or other statistical synthesis methods) or do not include synthesis (for example, because only one eligible study is identified). The PRISMA 2020 items are relevant for mixed-methods systematic reviews (which include quantitative and qualitative studies), but reporting guidelines addressing the presentation and synthesis of qualitative data should also be consulted [39, 40]. PRISMA 2020 can be used for original systematic reviews, updated systematic reviews, or continually updated (“living”) systematic reviews. However, for updated and living systematic reviews, there may be some additional considerations that need to be addressed. Where there is relevant content from other reporting guidelines, we reference these guidelines within the items in the explanation and elaboration paper [41] (such as PRISMA-Search [42] in items 6 and 7, Synthesis without meta-analysis (SWiM) reporting guideline [27] in item 13d). Box 1 includes a glossary of terms used throughout the PRISMA 2020 statement. PRISMA 2020 is not intended to guide systematic review conduct, for which comprehensive resources are available [43–46]. However, familiarity with PRISMA 2020 is useful when planning and conducting systematic reviews to ensure that all recommended information is captured. PRISMA 2020 should not be used to assess the conduct or methodological quality of systematic reviews; other tools exist for this purpose [30, 31]. Furthermore, PRISMA 2020 is not intended to inform the reporting of systematic review protocols, for which a separate statement is available (PRISMA for Protocols (PRISMA-P) 2015 statement [47, 48]). Finally, extensions to the PRISMA 2009 statement have been developed to guide reporting of network meta-analyses [49], meta-analyses of individual participant data [50], systematic reviews of harms [51], systematic reviews of diagnostic test accuracy studies [52], and scoping reviews [53]; for these types of reviews we recommend authors report their review in accordance with the recommendations in PRISMA 2020 along with the guidance specific to the extension. How to use PRISMA 2020 The PRISMA 2020 statement (including the checklists, explanation and elaboration, and flow diagram) replaces the PRISMA 2009 statement, which should no longer be used. Box 2 summarises noteworthy changes from the PRISMA 2009 statement. The PRISMA 2020 checklist includes seven sections with 27 items, some of which include sub-items (Table 1). A checklist for journal and conference abstracts for systematic reviews is included in PRISMA 2020. This abstract checklist is an update of the 2013 PRISMA for Abstracts statement [54], reflecting new and modified content in PRISMA 2020 (Table 2). A template PRISMA flow diagram is provided, which can be modified depending on whether the systematic review is original or updated (Fig. 1). Table 1 PRISMA 2020 item checklist Section and topic Item # Checklist item Location where item is reported Title Title 1 Identify the report as a systematic review. Abstract Abstract 2 See the PRISMA 2020 for Abstracts checklist (Table 2). Introduction Rationale 3 Describe the rationale for the review in the context of existing knowledge. Objectives 4 Provide an explicit statement of the objective(s) or question(s) the review addresses. Methods Eligibility criteria 5 Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses. Information sources 6 Specify all databases, registers, websites, organisations, reference lists and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted. Search strategy 7 Present the full search strategies for all databases, registers and websites, including any filters and limits used. Selection process 8 Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process. Data collection process 9 Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process. Data items 10a List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g. for all measures, time points, analyses), and if not, the methods used to decide which results to collect. 10b List and define all other variables for which data were sought (e.g. participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information. Study risk of bias assessment 11 Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process. Effect measures 12 Specify for each outcome the effect measure(s) (e.g. risk ratio, mean difference) used in the synthesis or presentation of results. Synthesis methods 13a Describe the processes used to decide which studies were eligible for each synthesis (e.g. tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)). 13b Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions. 13c Describe any methods used to tabulate or visually display results of individual studies and syntheses. 13d Describe any methods used to synthesise results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used. 13e Describe any methods used to explore possible causes of heterogeneity among study results (e.g. subgroup analysis, meta-regression). 13f Describe any sensitivity analyses conducted to assess robustness of the synthesised results. Reporting bias assessment 14 Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases). Certainty assessment 15 Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome. Results Study selection 16a Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram (see Fig. 1). 16b Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded. Study characteristics 17 Cite each included study and present its characteristics. Risk of bias in studies 18 Present assessments of risk of bias for each included study. Results of individual studies 19 For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g. confidence/credible interval), ideally using structured tables or plots. Results of syntheses 20a For each synthesis, briefly summarise the characteristics and risk of bias among contributing studies. 20b Present results of all statistical syntheses conducted. If meta-analysis was done, present for each the summary estimate and its precision (e.g. confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect. 20c Present results of all investigations of possible causes of heterogeneity among study results. 20d Present results of all sensitivity analyses conducted to assess the robustness of the synthesised results. Reporting biases 21 Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed. Certainty of evidence 22 Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed. Discussion Discussion 23a Provide a general interpretation of the results in the context of other evidence. 23b Discuss any limitations of the evidence included in the review. 23c Discuss any limitations of the review processes used. 23d Discuss implications of the results for practice, policy, and future research. Other information Registration and protocol 24a Provide registration information for the review, including register name and registration number, or state that the review was not registered. 24b Indicate where the review protocol can be accessed, or state that a protocol was not prepared. 24c Describe and explain any amendments to information provided at registration or in the protocol. Support 25 Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review. Competing interests 26 Declare any competing interests of review authors. Availability of data, code, and other materials 27 Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review. Table 2 PRISMA 2020 for abstracts checklista Section and topic Item # Checklist item Title Title 1 Identify the report as a systematic review. Background Objectives 2 Provide an explicit statement of the main objective(s) or question(s) the review addresses. Methods Eligibility criteria 3 Specify the inclusion and exclusion criteria for the review. Information sources 4 Specify the information sources (e.g. databases, registers) used to identify studies and the date when each was last searched. Risk of bias 5 Specify the methods used to assess risk of bias in the included studies. Synthesis of results 6 Specify the methods used to present and synthesise results. Results Included studies 7 Give the total number of included studies and participants and summarise relevant characteristics of studies. Synthesis of results 8 Present results for main outcomes, preferably indicating the number of included studies and participants for each. If meta-analysis was done, report the summary estimate and confidence/credible interval. If comparing groups, indicate the direction of the effect (i.e. which group is favoured). Discussion Limitations of evidence 9 Provide a brief summary of the limitations of the evidence included in the review (e.g. study risk of bias, inconsistency and imprecision). Interpretation 10 Provide a general interpretation of the results and important implications. Other Funding 11 Specify the primary source of funding for the review. Registration 12 Provide the register name and registration number. aThis abstract checklist retains the same items as those included in the PRISMA for Abstracts statement published in 2013 [54], but has been revised to make the wording consistent with the PRISMA 2020 statement and includes a new item recommending authors specify the methods used to present and synthesise results (item #6) Fig. 1 PRISMA 2020 flow diagram template for systematic reviews. The new design is adapted from flow diagrams proposed by Boers [55], Mayo-Wilson et al. [56] and Stovold et al. [57] The boxes in grey should only be completed if applicable; otherwise they should be removed from the flow diagram. Note that a “report” could be a journal article, preprint, conference abstract, study register entry, clinical study report, dissertation, unpublished manuscript, government report or any other document providing relevant information We recommend authors refer to PRISMA 2020 early in the writing process, because prospective consideration of the items may help to ensure that all the items are addressed. To help keep track of which items have been reported, the PRISMA statement website (http://www.prisma-statement.org/) includes fillable templates of the checklists to download and complete (also available in Additional file 1). We have also created a web application that allows users to complete the checklist via a user-friendly interface [58] (available at https://prisma.shinyapps.io/checklist/ and adapted from the Transparency Checklist app [59]). The completed checklist can be exported to Word or PDF. Editable templates of the flow diagram can also be downloaded from the PRISMA statement website. We have prepared an updated explanation and elaboration paper, in which we explain why reporting of each item is recommended and present bullet points that detail the reporting recommendations (which we refer to as elements) [41]. The bullet-point structure is new to PRISMA 2020 and has been adopted to facilitate implementation of the guidance [60, 61]. An expanded checklist, which comprises an abridged version of the elements presented in the explanation and elaboration paper, with references and some examples removed, is available in Additional file 2. Consulting the explanation and elaboration paper is recommended if further clarity or information is required. Journals and publishers might impose word and section limits, and limits on the number of tables and figures allowed in the main report. In such cases, if the relevant information for some items already appears in a publicly accessible review protocol, referring to the protocol may suffice. Alternatively, placing detailed descriptions of the methods used or additional results (such as for less critical outcomes) in supplementary files is recommended. Ideally, supplementary files should be deposited to a general-purpose or institutional open-access repository that provides free and permanent access to the material (such as Open Science Framework, Dryad, figshare). A reference or link to the additional information should be included in the main report. Finally, although PRISMA 2020 provides a template for where information might be located, the suggested location should not be seen as prescriptive; the guiding principle is to ensure the information is reported. Discussion Use of PRISMA 2020 has the potential to benefit many stakeholders. Complete reporting allows readers to assess the appropriateness of the methods, and therefore the trustworthiness of the findings. Presenting and summarising characteristics of studies contributing to a synthesis allows healthcare providers and policy makers to evaluate the applicability of the findings to their setting. Describing the certainty in the body of evidence for an outcome and the implications of findings should help policy makers, managers, and other decision makers formulate appropriate recommendations for practice or policy. Complete reporting of all PRISMA 2020 items also facilitates replication and review updates, as well as inclusion of systematic reviews in overviews (of systematic reviews) and guidelines, so teams can leverage work that is already done and decrease research waste [36, 62, 63]. We updated the PRISMA 2009 statement by adapting the EQUATOR Network’s guidance for developing health research reporting guidelines [64]. We evaluated the reporting completeness of published systematic reviews [17, 21, 36, 37], reviewed the items included in other documents providing guidance for systematic reviews [38], surveyed systematic review methodologists and journal editors for their views on how to revise the original PRISMA statement [35], discussed the findings at an in-person meeting, and prepared this document through an iterative process. Our recommendations are informed by the reviews and survey conducted before the in-person meeting, theoretical considerations about which items facilitate replication and help users assess the risk of bias and applicability of systematic reviews, and co-authors’ experience with authoring and using systematic reviews. Various strategies to increase the use of reporting guidelines and improve reporting have been proposed. They include educators introducing reporting guidelines into graduate curricula to promote good reporting habits of early career scientists [65]; journal editors and regulators endorsing use of reporting guidelines [18]; peer reviewers evaluating adherence to reporting guidelines [61, 66]; journals requiring authors to indicate where in their manuscript they have adhered to each reporting item [67]; and authors using online writing tools that prompt complete reporting at the writing stage [60]. Multi-pronged interventions, where more than one of these strategies are combined, may be more effective (such as completion of checklists coupled with editorial checks) [68]. However, of 31 interventions proposed to increase adherence to reporting guidelines, the effects of only 11 have been evaluated, mostly in observational studies at high risk of bias due to confounding [69]. It is therefore unclear which strategies should be used. Future research might explore barriers and facilitators to the use of PRISMA 2020 by authors, editors, and peer reviewers, designing interventions that address the identified barriers, and evaluating those interventions using randomised trials. To inform possible revisions to the guideline, it would also be valuable to conduct think-aloud studies [70] to understand how systematic reviewers interpret the items, and reliability studies to identify items where there is varied interpretation of the items. We encourage readers to submit evidence that informs any of the recommendations in PRISMA 2020 (via the PRISMA statement website: http://www.prisma-statement.org/). To enhance accessibility of PRISMA 2020, several translations of the guideline are under way (see available translations at the PRISMA statement website). We encourage journal editors and publishers to raise awareness of PRISMA 2020 (for example, by referring to it in journal “Instructions to authors”), endorsing its use, advising editors and peer reviewers to evaluate submitted systematic reviews against the PRISMA 2020 checklists, and making changes to journal policies to accommodate the new reporting recommendations. We recommend existing PRISMA extensions [47, 49–53, 71, 72] be updated to reflect PRISMA 2020 and advise developers of new PRISMA extensions to use PRISMA 2020 as the foundation document. Conclusion We anticipate that the PRISMA 2020 statement will benefit authors, editors, and peer reviewers of systematic reviews, and different users of reviews, including guideline developers, policy makers, healthcare providers, patients, and other stakeholders. Ultimately, we hope that uptake of the guideline will lead to more transparent, complete, and accurate reporting of systematic reviews, thus facilitating evidence based decision making. Box 1 Glossary of terms Systematic review—A review that uses explicit, systematic methods to collate and synthesise findings of studies that address a clearly formulated question [43] Statistical synthesis—The combination of quantitative results of two or more studies. This encompasses meta-analysis of effect estimates (described below) and other methods, such as combining P values, calculating the range and distribution of observed effects, and vote counting based on the direction of effect (see McKenzie and Brennan [25] for a description of each method) Meta-analysis of effect estimates—A statistical technique used to synthesise results when study effect estimates and their variances are available, yielding a quantitative summary of results [25] Outcome—An event or measurement collected for participants in a study (such as quality of life, mortality) Result—The combination of a point estimate (such as a mean difference, risk ratio, or proportion) and a measure of its precision (such as a confidence/credible interval) for a particular outcome Report—A document (paper or electronic) supplying information about a particular study. It could be a journal article, preprint, conference abstract, study register entry, clinical study report, dissertation, unpublished manuscript, government report, or any other document providing relevant information Record—The title or abstract (or both) of a report indexed in a database or website (such as a title or abstract for an article indexed in Medline). Records that refer to the same report (such as the same journal article) are “duplicates”; however, records that refer to reports that are merely similar (such as a similar abstract submitted to two different conferences) should be considered unique. Study—An investigation, such as a clinical trial, that includes a defined group of participants and one or more interventions and outcomes. A “study” might have multiple reports. For example, reports could include the protocol, statistical analysis plan, baseline characteristics, results for the primary outcome, results for harms, results for secondary outcomes, and results for additional mediator and moderator analyses Box 2 Noteworthy changes to the PRISMA 2009 statement • Inclusion of the abstract reporting checklist within PRISMA 2020 (see item #2 and Box 2). • Movement of the ‘Protocol and registration’ item from the start of the Methods section of the checklist to a new Other section, with addition of a sub-item recommending authors describe amendments to information provided at registration or in the protocol (see item #24a-24c). • Modification of the ‘Search’ item to recommend authors present full search strategies for all databases, registers and websites searched, not just at least one database (see item #7). • Modification of the ‘Study selection’ item in the Methods section to emphasise the reporting of how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process (see item #8). • Addition of a sub-item to the ‘Data items’ item recommending authors report how outcomes were defined, which results were sought, and methods for selecting a subset of results from included studies (see item #10a). • Splitting of the ‘Synthesis of results’ item in the Methods section into six sub-items recommending authors describe: the processes used to decide which studies were eligible for each synthesis; any methods required to prepare the data for synthesis; any methods used to tabulate or visually display results of individual studies and syntheses; any methods used to synthesise results; any methods used to explore possible causes of heterogeneity among study results (such as subgroup analysis, meta-regression); and any sensitivity analyses used to assess robustness of the synthesised results (see item #13a-13f). • Addition of a sub-item to the ‘Study selection’ item in the Results section recommending authors cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded (see item #16b). • Splitting of the ‘Synthesis of results’ item in the Results section into four sub-items recommending authors: briefly summarise the characteristics and risk of bias among studies contributing to the synthesis; present results of all statistical syntheses conducted; present results of any investigations of possible causes of heterogeneity among study results; and present results of any sensitivity analyses (see item #20a-20d). • Addition of new items recommending authors report methods for and results of an assessment of certainty (or confidence) in the body of evidence for an outcome (see items #15 and #22). • Addition of a new item recommending authors declare any competing interests (see item #26). • Addition of a new item recommending authors indicate whether data, analytic code and other materials used in the review are publicly available and if so, where they can be found (see item #27). Supplementary Information Additional file 1. PRISMA 2020 checklist. Additional file 2. PRISMA 2020 expanded checklist.
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Role of cannabis in cardiovascular disorders.
Hemant Goyal, Hamza H Awad, Jalal K. Ghali (2017)
The growing popularity of medical and recreational consumption of cannabis, especially among the youth, raises immediate concerns regarding its safety and long-terms effects. The cardiovascular effects of cannabis are not well known. Cannabis consumption has been shown to cause arrhythmia including ventricular tachycardia, and potentially sudden death, and to increase the risk of myocardial infarction (MI). These effects appear to be compounded by cigarette smoking and precipitated by excessive physical activity, especially during the first few hours of consumption. Cannabinoids, or the active compounds of cannabis, have been shown to have heterogeneous effects on central and peripheral circulation. Acute cannabis consumption has been shown to cause an increase in blood pressure, specifically systolic blood pressure (SBP), and orthostatic hypotension. Cannabis use has been reported to increase risk of ischemic stroke, particularly in the healthy young patients. The endocannabinoid system (ECS) is currently considered as a promising therapeutic target in the management of several disease conditions. Synthetic cannabinoids (SCs) are being increasingly investigated for their therapeutic effects; however, the value of their benefits over possible complications remains controversial. Despite the considerable research in this field, the benefits of cannabis and its synthetic derivatives remains questionable even in the face of an increasingly tolerating attitude towards recreational consumption and promotion of the therapeutic complications. More efforts are needed to increase awareness among the public, especially youth, about the cardiovascular risks associated with cannabis use and to disseminate the accumulated knowledge regarding its ill effects.
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Current and Former Smoking and Risk for Venous Thromboembolism: A Systematic Review and Meta-Analysis
Yun-Jiu Cheng, Zhi-Hao Liu, Feng-Juan Yao … (2013)
Introduction Although cigarette smoking has been responsible for approximately 5 million deaths every year, there are still an estimated 1.1 billion smokers worldwide [1],[2]. The magnitude of this public health challenge is growing, and estimates suggest that as many as 8 million people may die from smoking-related diseases by 2030 [2]. Venous thromboembolism (VTE) is a serious medical event and associated with a substantial risk of mortality [3]. In ambulatory population-based cohorts, the estimated 28-d mortality for the first episode of VTE is 11% [4]. Autopsy studies have found that VTE exists in about one-third of deaths in hospitals and 13% of all autopsies showed signs of fatal pulmonary embolism (PE) [5],[6]. Smoking is a well-established risk factor for atherosclerotic disease, but its role as an independent risk factor or effect modifier for VTE remains controversial. Several prospective studies reported smoking to be an independent risk factor [7],[8], whereas others failed to detect a significant relationship between smoking and VTE [9],[10]. A recent meta-analysis showed a statistically nonsignificant odds ratio (OR) for VTE of 1.18 (95% CI 0.95–1.46) for smokers compared with non-smokers [11]. However, the meta-analysis (involving a total of ten studies) included only about one-third of the data currently available. In addition, six of the ten studies included were clinical trials of oral contraceptives, in which the samples may not be representative of the general population. Furthermore, the VTE risk may be underestimated due to lack of distinction between former and current smokers and no adjustment for cardiovascular risk factors. Smoking can be potentially reduced by individual and population-related measures; therefore, demonstrating the link between smoking and the risk of VTE may help reduce the burden of this disease. Therefore, we conducted a meta-analysis with the following aims: (1) to estimate the link between smoking and risk of VTE in the general population; (2) to measure the smoking-VTE relationship according to different degrees of adjustment for confounding factors, study designs, study populations, sex category, and type of VTE; and (3) to study dose-response patterns of tobacco exposure on the risk of VTE. Methods Search Strategy This meta-analysis follows PRISMA guidelines (Text S1). We searched the publications listed in the electronic databases MEDLINE (source PubMed, January 1, 1966 to June 15, 2013) and EMBASE (January 1, 1980 to June 15, 2013) using the following text and key words in combination both as MeSH terms and text word “thromboembolism”, “venous thrombosis”, “pulmonary embolism”, deep-vein thrombosis”, “risk factors”, “smoke”, “cigarette”, “tobacco” or “smoking”. We searched articles published in any language and scrutinized references from these studies to identify other relevant studies. Study Selection To minimize differences between studies, we imposed the following methodological restrictions for the inclusion criteria: (1) Studies that contained the minimum information necessary to estimate the relative risk (RR) associated with smoking, including case-control and cohort studies published as original articles; (2) Studies in which populations were representative of the general population and not those with selected participants on the basis of risk factor for VTE, such as tumor, surgery, or use of oral contraceptives. In instances of multiple publications, the most up-to-date or comprehensive information was used. Data Abstraction Articles were reviewed and cross-checked independently by two authors (YJC and ZHL). Because there is no standardized quality scoring system for observational studies, we selected a priori several important design characteristics that may affect study quality, including method of case confirmation, percentage of patients completing planned follow-up, smoking as the primary analysis of interest, selection criteria for control participants, matching criteria, and control for confounding. Percentage agreement between the two authors on the quality review ranged from 88% to 100%. Any disagreements were resolved by consensus. Data on the following characteristics were independently extracted: study size, number of patients who developed VTE, total person-years of follow-up, study population, publication year, study design, sampling framework, study location (defined as Europe, North America, or Asia); gender category, site of VTE studied (deep vein thrombosis [DVT] or PE), type of VTE studied (unprovoked or provoked), ascertainment of VTE (validated or not validated), smoking category (ever, current, or former), and reported adjustment for potential confounders. When available, we used the most comprehensively adjusted risk estimates. Data Analysis RR was used as a measure of the relationship between smoking and the risk of VTE. For case-control studies, the OR was used as a surrogate measure of the corresponding RR. Because the absolute risk of VTE is low, the OR approximates the RR [12]. Summary RRs (95% CI) were calculated by pooling the study-specific estimates using a random-effects model that included between-study heterogeneity (parallel analyses used fixed-effects models), because significant heterogeneity was anticipated among studies. Pooled RRs were expressed with 95% CIs. We calculated the I2 (95% CI) statistic to assess heterogeneity across studies, applying the following interpretation for I2: 75% = high heterogeneity [13]. We calculated the population attributable fraction (PAF) as {prevalence of smoking×(RR−1)/[prevalence of smoking×(RR−1)+1]}, where RR indicates pooled RRs [14]. On the basis of population-based cohort studies, the average prevalence of three categories of smoking was estimated by weighting by the sample size of each study. Subgroup analyses and meta-regression models were carried out to investigate potential sources of between-study heterogeneity. When several risk estimates were present in a single study (i.e., separate estimates for current and former smokers), we adjusted the pooled estimates for intra-study or within-study correlation [15]. In the dose-response analysis, we considered cigarettes per day and pack-years as explanatory variables. Because for many studies continuous exposures were reported as categorical data with a range, we assigned the mid-point in each category to the corresponding RR for each study. When the highest category was open ended, we considered 60 cigarettes per day and 60 pack-years as the maximum (for example, one study reported >20 cigarettes per day as an open range; we considered 40 cigarettes per day as the mid-point in this category). We used generalized least squares (GLST) regression models to assess the pooled dose-response relation between smoking and risk of VTE across studies that had heterogeneous categorizations of smoking [16]. Linear models were fitted and evaluated on the logarithm of the RRs. To enable the total person-years of observation to be calculated, we included data from reports that specified one or more of the following: total person-time of follow-up; sample size and mean (or median) follow-up per patient; or sample size and cumulative incidence rate. The principal summary measure was event rate expressed per 100,000 patient-years of follow-up. Weighted meta-analytic prevalence estimates for outcomes were calculated with the variance-stabilizing Freeman-Tukey double-arcsine transformation with an inverse-variance random-effects model [17]. Small study bias, consistent with publication bias, was assessed with funnel plot, by Begg's adjusted rank correlation test and by Egger's regression asymmetry test [18]. We used STATA, version 11.0 (Stata Corp) for all analyses. Statistical tests were two sided and used a significance level of p 99%. The sizes of the cohorts ranged from 855 to 2,314,701 (in total 3,926,048), with the two largest studies recruiting participants over 1 million (Table 1) [26],[29]. Nineteen case-control studies were designed to evaluate risk factors for VTE, and eight of them used either hospital discharge data or data from registries. In 12 of the 19 incident case-control studies, controls were matched for age and/or sex only (Table 2). 10.1371/journal.pmed.1001515.t001 Table 1 Cohort studies reporting incidence risk estimates. Study Year Country Source Mean Follow-up (y) Case Confirmation Sexa Female (%) n Cases Persons at Risk Type of VTE Site of VTE Variables adjusted forb Smoking Category Goldhaber SZ [19] 1997 USA Population-based 14.3 Questionnaire W 100 280 112,822 Unprovoked or provoked PE Age, BMI, cholesterol, diabetes, hypertension, and other Current, former Hansson PO [20] 1999 Sweden Population-based 13 Medical record and radiology M 0 56 855 Unprovoked or provoked DVT or PE Waist circumference Current, former Klatsky AL [21] 2000 USA Population-based 14.1 Radiology and autopsy Both 51.3 337 128,934 Unprovoked or provoked DVT or PE Age, sex, BMI, alcohol, and other Ever Glynn RJ [22] 2005 USA Clinical trial 20.1c Questionnaire M 0 358 18,662 Unprovoked, provoked DVT or PE Age, BMI, cholesterol, diabetes, hypertension, alcohol, physical activity, and other Current, former Lindqvist PG [23] 2008 Sweden Population-based 11 Questionnaire W 100 312 2,498 Unprovoked or provoked DVT or PE Age Ever Rosengren A [24] 2008 Sweden Population-based 14.4 Medical record and radiology M 0 358 6,958 Unprovoked or provoked DVT or PE Age Current, former Severinsen MT [8] 2009 Denmark Population-based 10.2c Medical record and radiology M, W 52.3 641 57,053 Unprovoked, provoked DVT or PE BMI, alcohol, physical activity, and other Current, former Holst AG [7] 2010 Denmark Population-based 19.5c Death and patient registry M, W 53.5 969 18,954 unprovoked DVT or PE, Sex, BMI, blood pressure, and other Current, former Lutsey PL [25] 2010 USA Population-based 13c Questionnaire W 100 2,137 40,377 Unprovoked or provoked DVT or PE Age, BMI, physical activity, and other Current, former Hippisley-Cox J [26] 2011 UK General practitioner register 5 Death and patient registry M, W 48.6 14,756 2,314,701 Unprovoked or provoked DVT or PE Age, BMI, and other Current, former Enga KF [27] 2012 Norway Population-based 12.5c Medical record and radiology or autopsy Both 53.3 389 24,576 Unprovoked, provoked DVT or PE Age, sex, BMI, and other Current, former Wattanakit K [28] 2012 USA Population-based 15.5 Medical record and radiology or autopsy Both 55.4 468 15,340 Unprovoked, provoked DVT or PE Age, sex, BMI, and other Current, former Sweetland S [29] 2013 UK Population-based 6 Questionnaire W 100 4,630 1,162,718 Unprovoked or provoked DVT, PE Age, BMI, diabetes, hypertension, alcohol, physical activity, and other Current, former BMI calculated as weight in kilograms divided by height in meters squared. a Adjusted estimates were reported for men and women separately and together. If all three types of estimates were reported (M, W, B), they were analyzed separately by sex only in the heterogeneity analysis for sex. b The term “other” in the “Variables adjusted for” column stands for all the adjusting variables other than age, sex, and cardiovascular risk factors (BCDHAP: B, BMI, body weight, waist circumference; C, cholesterol; D, diabetes; H, hypertension; A, alcohol consumption; P, physical activity). c Median. 10.1371/journal.pmed.1001515.t002 Table 2 Case-control studies reporting incidence risk estimates. Study Year Country Source Control Group Case Confirmation Sexa Female (%) n Cases n Controls Type of VTE Site of VTE Variables Adjusted forb Smoking Category Dreyer NA [30] 1980 USA Hospital-based Age and race matched Radiology W 100 15 29 Unprovoked DVT or PE None Ever Lu Y [31] 2001 China Hospital-based Sex and age matched Radiology Both 38.9 72 72 Unprovoked or provoked PE None Ever Ray JG [32] 2001 Canada Hospital-based Age matched Radiology W 100 129 129 Unprovoked or provoked DVT or PE None Current Tosetto A [33] 2003 Italy Population-based Asymptomatic individuals Questionnaire Both 53.2 116 14,939 Unprovoked, provoked DVT, PE, Age, sex, BMI, and other Ever Worralurt C [34] 2005 Thailand Hospital-based Age and education matched Radiology W 100 70 140 Unprovoked or provoked DVT or PE None Ever Hirohashi T [35] 2006 Japan Hospital-based Non-VTE patients Radiology Both 46.9 75 151 Unprovoked or provoked PE None Ever Sugimura K [36] 2006 Japan Hospital-based Sex and age matched Questionnaire Both 67 209 209 Unprovoked or provoked DVT None Ever Pomp ER [37] 2007 The Netherlands Population-based Partner matched Radiology M,W 100 3,989 4,900 Unprovoked or provoked DVT, PE Age, sex, BMI and other Current, former Prandoni P [38] 2008 Italy Hospital-based Sex and age matched Radiology Both 54.6 299 150 Unprovoked, provoked DVT or PE None Ever Jang MJ [39] 2009 Korea Hospital-based Healthy individuals Objectively diagnosed Both 57.1 208 300 Unprovoked, provoked DVT or PE Age, sex, BMI, hypertension, cholesterol, glucose Ever Yamada N [40] 2009 Japan Hospital-based Non-VTE patients Radiology Both 47.8 100 199 Unprovoked or provoked PE Age, sex Ever Bhoopat L [41] 2010 Tailand Hospital-based Sex and age matched Radiology Both 69.7 97 195 Unprovoked or provoked DVT or PE None Ever Quist-Paulsen P [42] 2010 Norway Population-based Sex and age matched Medical record and radiology Both 54.6 483 1,362 Unprovoked or provoked DVT or PE Age, sex Ever Zhu J [43] 2010 China Hospital-based Sex and age matched Patients hospitalized Both 48.8 425 527 Unprovoked or provoked DVT or PE Age, sex, body weight, and other Current, former Cay N [44] 2011 Turkey Hospital-based Non-VTE patients Radiology Both 43.3 203 210 Unprovoked or provoked DVT None Ever Di Minno MN [45] 2010 Italy Hospital-based Sex and age matched Radiology M, W, Both 63.6 323 868 Unprovoked DVT or PE None Ever Abudureheman K [46] 2012 China Hospital-based Healthy individuals Radiology Both 49.8 222 220 Unprovoked or provoked DVT or PE Age, sex, BMI, cholesterol, hypertension, glucose, and other Ever Cil H [47] 2012 Turkey Hospital-based Healthy individuals Medical record and radiology Both 50.1 147 149 Unprovoked or provoked DVT or PE Age, BMI, hypertension, and other Ever Blondon M [48] 2013 USA Population-based Age matched Medical record and radiology W 54.6 2,278 5,927 Unprovoked, provoked DVT or PE, Age, BMI, hypertension, diabetes, and other Current, former BMI, calculated as weight in kilograms divided by height in meters squared. a Adjusted estimates were reported for men and women separately and together. If all three types of estimates were reported (M, W, B), they were analyzed separately by sex only in the heterogeneity analysis for sex. b The term “other” in the “Variables adjusted for” column stands for all the adjusting variables other than age, sex and cardiovascular risk factors (BCDHAP: B, BMI, body weight, waist circumference; C, cholesterol; D, diabetes; H, hypertension; A, alcohol consumption; P, physical activity). Of all the studies, two included only patients with DVT [36],[44] and four investigated only patients with PE [19],[31],[35],[40]. Four cohort studies [8],[22],[27],[28] and four case-control studies [33],[38],[39],[48] compared the prevalence of smoking between patients with unprovoked VTE and provoked VTE. Eight studies investigated only women [19],[23],[25],[29],[30],[32],[34],[48] and three studies included only men [20],[22],[24]. The association between smoking and VTE was the primary outcome of interest for 20 studies, whereas it was a secondary question in 12 studies. The ascertainment of VTE varied across studies; 24 studies based on medical record, radiology or autopsy (validated), and eight confirmed by questionnaire or patient registry (not validated) (Tables 1 and 2). Adjusted RRs could be determined for all cohort studies and nine of the case-control studies. Most risk estimates were adjusted for age (19 studies) and sex (11 studies). Eighteen studies (56.3%) reported an adjusted estimate for at least one of the cardiovascular risk factors: BMI (11 cohort and seven case-control studies), cholesterol (three cohort and one case-control studies), diabetes (three cohort and three case-control studies), hypertension (four cohort and four case-control studies), alcohol consumption (four cohort studies), or physical activity (four cohort studies). Detailed information on adjustments is reported in Tables 1 and 2. Smoking and Risk of VTE Figures 2, S1, and S2 showed the results from the random-effects model (parallel analysis with fixed-effects model) combining the RRs for VTE. Overall, the ever smokers compared with the reference group experienced a significantly increased risk for developing VTE (RR: 1.17 [95% CI 1.09–1.25, p 2,000 34,463 3,723,529 1.16 (1.09–1.24) 22,745 2,648,946 1.22 (1.13–1.33) 23,689 2,676,222 1.10 (1.04–1.17) a p-Values test homogeneity between strata. b Levels of adjustment in multivariate models: −, not adjusted for any confounding factors; +, adjusted for conventional confounding factors (i.e., age, sex); ++, further adjusted by potential cardiovascular risk factors (BCDHAP: B, BMI, body weight, circumference; C, cholesterol; D, diabetes; H, hypertension; A, alcohol consumption; P, physical activity. BMI, body weight or circumference was adjusted in every study). c Studies could contribute to one or both estimates depending on design of the primary studies. We undertook meta-regression to further identify the relationship between BMI and smoking-VTE risk. Although baseline BMI did not seem to be significantly correlated with the smoking-VTE risk for ever smokers, BMI-adjusted risk estimates were significantly higher than unadjusted ones (p = 0.02) (Figure S6). We also evaluated whether a difference existed between men and women, DVT and PE, and unprovoked and provoked VTE in the smoking-VTE relationship. The stratified analyses shown in Table 4 suggest no modification of the relationship by these characteristics. To allow an unbiased comparison, we also calculated the RRs from studies reporting both estimates for men and women, DVT and PE, and unprovoked and provoked VTE. Similar pooled risks were again observed in both sexes (p = 0.95) [7],[8],[26],[37], sites of VTE (p = 0.31) [29],[33],[37], and types of VTE (p = 0.38) [8],[22],[27],[28],[33],[38],[39],[48]. Dose-Response Relationship and Incidence of VTE After evaluating dose-response patterns for cigarettes per day and pack-years for ever versus never smokers, we observed a linear increase in VTE risk with increasing smoking consumption. The risk increased by 10.2% (95% CI 8.6%–11.8%) for every additional ten cigarettes per day or by 6.1% (95% CI 3.8%–8.5%) for every additional ten pack-years (for example, an individual who smoked one pack of cigarettes per day for 40 y or two packs per day for 20 y has a relative increased risk of 26.7% [95% CI 16.0%–38.4%] for developing VTE compared with someone who never smoked) (Figure 5). 10.1371/journal.pmed.1001515.g005 Figure 5 Linear dose-response relationship between relative risk of VTE incidence and tobacco consumption with cigarettes per day (A) and pack-years (B) as the explanatory variables. The solid line represents point estimates of association between tobacco consumption and VTE risk; dashed lines are 95% CIs. Circles present the dose-specific RR estimates reported in each study. The area of each circle is proportional to the inverse variance of the RR. The dotted line represents the null hypothesis of no association. The vertical axis is on a log scale. From eight population-based studies that reported information on person-years in smokers and nonsmokers, we could calculate absolute annual rates of VTE cases from the general population: 176.3 cases per 100,000 person-years in smokers and 152.0 cases in nonsmokers, corresponding to an absolute risk increase of 24.3 (95% CI 15.4–26.7) cases per 100,000 person-years. PAF Calculations Using the average prevalence of smoking from included cohort studies and the summary estimates obtained from all studies combined, the PAF of VTE due to smoking were 8.7% (95% CI 4.8%–12.3%) for ever smoking, 5.8% (95% CI 3.6%–8.2%) for current smoking, and 2.7% (95% CI 0.8%–4.5%) for former smoking. If cardiovascular risk factor-adjusted risk estimates were used, then the proportions of VTE explained by three categories of smoking increased to 10.6% (95% CI 7.8%–12.8%), 7.7% (95% CI 6.1%–9.1%), and 2.8% (95% CI 1.1%–4.5%), respectively. Discussion The present meta-analysis, involving approximately 4 million participants and more than 35,000 patients with VTE from 32 observational studies, found a slightly increased risk of VTE for smokers compared with non-smokers. The risk was higher in studies adjusted for conventional cardiovascular risk factors, especially for BMI. The risk of developing VTE was greater for current smokers than for former smokers, and a dose-response relationship was found for daily smoking and pack-years smoked. Recent studies have suggested that patients with obesity, hypertension, diabetes, or dyslipidemia were at risk of developing VTE, whereas conflicting results were reported for smoking [10],[11],[49]–[53]. This meta-analysis is the first to our knowledge to confirm smoking to be an independent risk factor for VTE. The risk magnitude appears to be less robust than those reported for well-established major risk factors such as cancer, surgery, pregnancy, use of estrogens, or mutation of factor V Leiden and prothrombin [54]–[57]. However, smoking is more common and its coexistence is associated with an additive causative effect. For example, there was a synergistic effect on VTE risk for smoking and oral contraceptive use. Pomp et al. reported the OR of developing VTE for oral contraceptive users was 3.90, but increased to 8.79 when current smoking was added [37]. One prospective cohort study also identified a hazard ratio of 3.75 for the association of the combination of current smoking and the prothrombin mutation with the risk of VTE, significantly higher than that of the prothrombin mutation only [58]. Thus, given the multi-factorial nature of VTE, it is highly likely that the concomitant action of smoking may be responsible for a proportion of VTE in the general population. A causal relationship between VTE and smoking may be mediated by different mechanisms. Our results suggest that the association of smoking with VTE risk may be largely mediated by an acute mechanism, supported by a dose-response relationship for the amount of current smoking and the higher risk in current compared to former smokers. In addition, the association was not solely due to smoking-related secondary diseases, because we found a positive association between current smoking and both unprovoked and provoked VTE. Furthermore, there is biological plausibility for the relationship. A procoagulant state, reduced fibrinolysis, inflammation, and increased blood viscosity may underlie the association between smoking and VTE risk [59]–[61]. Smoking is associated with a higher level of plasma fibrinogen, hence the increase of factor VIII, which has been reported to be associated with VTE [62]. It has been shown that the fibrinogen concentration decreased quickly after cessation of smoking and the fibrinogen concentration was nearly equal in former smokers and never smokers [63],[64]. Yarnell et al. detected a positive relationship between the amount of current tobacco consumption and plasminogen activator inhibitor-1 concentration, which may also be related to VTE [65]–[67]. These findings might suggest an acute causal association and the dose-response relationship between VTE and smoking. However, a relatively weak association between former smoking and the risk of VTE was also observed. We suppose this association may be mediated by secondary smoking-related diseases. Former smoking is related to cardiovascular diseases, diabetes, and certain types of cancer [68]–[70], which may be associated with risk of VTE [54],[71]. It is also possible that chronic inhalation of tobacco smoke, causing progressive lung destruction, chronic obstructive pulmonary disease, and emphysema [72], may also result in a hypercoagulable state and thus contribute to an increased risk of VTE [73]. It is of note that lack of adjustment for BMI tends to deflate the pooled risk estimate, indicating that BMI is an important confounding factor when assessing the smoking-VTE association. Limiting studies to those adjusted for BMI identified no significant heterogeneity for ever and current smokers, suggesting that BMI may be a source of heterogeneity. Current smokers tend to be thinner than nonsmokers or former smokers [74]–[76], and several studies have shown that smokers' BMI is lower [77]. However, previous studies also identified obesity or weight gain to be an independent risk factor for developing VTE [11],[20],[78]. Thus, given that body leanness of some smokers might partly reduce the risk, the true magnitude of association between smoking and VTE may be greater. This may be an explanation for the non-significant association observed in previous observational studies and meta-analysis that did not control for BMI. Strengths of this meta-analysis include the strict inclusion criteria, the large number of patients analyzed, the robustness of the findings in sensitivity analyses, the dose-response relationship, and the fact that all subgroup analyses were prespecified a priori. The absence of important publication bias supports the robustness of the study findings. A possible limitation of our study is the heterogeneity of the studies with regard to adjustment of the estimates for potential confounders. Although differences in levels of adjustment seems, at least in part, to explain this finding, heterogeneity still exists in former smokers, even after we confined the analysis to studies that adjusted for BMI. This suggests that apart from BMI, there are other factors that potentially may confound the risk estimates. Furthermore, baseline BMI was not significantly associated with the smoking-VTE risk, indicating that the relation between BMI and risk of VTE in smokers needs to be further elucidated. Inclusion of different types of studies into one meta-analysis may also introduce heterogeneity into the results. Despite this, the consistency of the finding of an increased risk of VTE among smokers in both case-control and cohort studies suggests that the association is valid. In addition, the results from a given study for the three comparisons (ever versus never, former versus never, current versus never) are not independent and there is a possibility of a type I error. However, the results continued to be statistically significant after adjusting for multiple comparisons by setting α = 0.05/3. Like all meta-analyses, our study has the limitation of being a retrospective analysis. Another limitation was the lack of individual participant data, which precluded determining the independent associations of individual variables with study outcomes. Instead, we used between-study meta-regressions, when possible. In conclusion, the results from this meta-analysis suggest that smoking slightly increases the risk of VTE, independent of conventional cardiovascular risk factors. BMI may be a potential confounding factor in the risk estimates. The association between smoking and VTE has clinical relevance with respect to individual screening, risk factor modification, and the primary and secondary prevention of VTE. Future prospective studies are needed to elucidate the specific pathogenic mechanisms. Supporting Information Figure S1 Forest plot for VTE incidence: risk estimates for current versus never smokers. The size of each square is proportional to the study's weight (inverse of variance). (TIF) Click here for additional data file. Figure S2 Forest plot for VTE incidence: risk estimates for former versus never smokers. The size of each square is proportional to the study's weight (inverse of variance). (TIF) Click here for additional data file. Figure S3 Pooled relative risks of VTE for ever smokers stratified by VTE validation. VTE case confirmation was based on medical record, radiology, or autopsy (validated) and questionnaire or patient registry (not validated). (TIF) Click here for additional data file. Figure S4 Pooled relative risks of VTE for current smokers stratified by VTE validation. VTE case confirmation was based on medical record, radiology, or autopsy (validated) and questionnaire or patient registry (not validated). (TIF) Click here for additional data file. Figure S5 Pooled relative risks of VTE for former smokers stratified by VTE validation. VTE case confirmation was based on medical record, radiology, or autopsy (validated) and questionnaire or patient registry (not validated). (TIF) Click here for additional data file. Figure S6 Relationship between baseline BMI and smoking-VTE risk for ever smokers. Regression analyses were stratified, where appropriate, by level of adjustment for BMI. Meta-regression p = 0.64 for BMI-unadjusted risk estimates, p = 0.92 for BMI-adjusted risk estimates. (TIF) Click here for additional data file. Text S1 PRISMA 2009 checklist. (DOC) Click here for additional data file.
Author and article information
Journal
Journal ID (nlm-ta): Cureus
Journal ID (iso-abbrev): Cureus
Journal ID (issn): 2168-8184
Title:
Cureus
Publisher:
Cureus
(Palo Alto (CA)
)
ISSN
(Electronic):
2168-8184
Publication date
(Electronic, pub):
15
September
2022
Publication date
(Electronic, collection):
September
2022
Volume: 14
Issue: 9
Electronic Location Identifier: e29208
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Author notes
Anas A. Abu Jad
a.abujad@
123456live.com
Article
DOI: 10.7759/cureus.29208
PMC ID: 9484787
SO-VID: 1931a750-7313-4135-b18e-c1a9ebe59a2a
Copyright © Copyright © 2022, Abu Jad et al.
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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
History
Date
received
: 3
June
2022
Date
accepted
: 15
September
2022
Categories
Subject:
Cardiology
Subject:
Public Health
Subject:
Substance Use and Addiction
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