Impact of Shift Work on Blood Pressure and Hypertension: a systematic review and meta-analysis
Bibliographic record
Abstract
Hypertension (HTN) remains a major preventable cause of cardiovascular diseases and all-cause mortality, justifying considerable efforts for its prevention. Moreover the continuous relationship between Blood Pressure (BP) values and CVD events has been shown, , making the distinction between normotension and hypertension based on cut-off BP values somewhat arbitrary nevertheless useful for clinical and public health decisions. Recent guidelines on CVD prevention stress the importance of non-traditional risk factors, including socioeconomic status, social isolation and some occupational factors. Shift work, considering the circadian rhythm disruption due to atypical working hours , may be of relevance. The link between shift work and HTN has been previously studied and reviewed, albeit with somewhat conflicting results. Being shift work a growing societal trend and hypertension a leading risk factor for cardiovascular disease, it is crucial to clarify the impact of shift work organization in the Blood Pressure (BP) values and the HTN risk, in order to support the eventual need for specific policies regarding shift workers. The purpose of the present review is to assess the effect of shift work exposure on the Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) values of adult shift workers, compared to non shift workers, as well as Hypertension (HTN) risk. The following electronic databases will be searched: MEDLINE, EMBASE and The Cochrane Library. Data from published clinical trials and observational studies that present data of blood pressure and/or incident/prevalent hypertension in shift workers and in a comparator group of non-shift workers will be included. Outcomes variables will include SBP and DBP values, measured either by Ambulatory Blood Pressure Monitor (AMBP) or in the clinical office, and HTN prevalence. The diagnosis of HTN assumed is the one being defined accordingly to the most recent European guidelines. The diagnosis of HTN will also be considered when the subject is under anti-hypertensive medication, however, studies in which the diagnosis relies on subjects self-report will not be considered. Two reviewers will independently screen the title and abstract and determine if each paper meets the inclusion criteria for the review using to Rayyan QCRI Software. Selected studies relevant data will be extracted independently by two authors into a standardised form built in Microsoft Excel® including information on: study characteristics, participants ( shift workers vs non-shift-workers), exposure to shift work type and outcomes. When studies present different estimates using the same control/reference we will include the most representative according to our criteria (see Protocol). We will rate the methodological quality of the included studies using the Newcastle–Ottawa quality assessment scale (NOS) for observational studies. If studies are sufficiently homogeneous in terms of exposure, comparator, and design, we will conduct meta-analyses using a random-effects model. The consistency of results across studies may influence the decision whether to combine individual study data in a meta-analysis. A systematic narrative synthesis will be provided with information presented in the text and tables to summarise and explain the characteristics and main findings of the included studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.023 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".