How does peak flow affect heart attack

These inverse associations were also found within all combinations of 5-year follow-up period and year baseline age group Figure 1. Baseline age groups used were 40—49, 50—59, and 60—69 years. Hazard ratios HR are adjusted for area. Area of square is inversely proportional to floated variance of log HR.

Numbers above error bars are HRs. However, the association of h-PEF with mortality varied with the follow-up period Figure 1. In further analyses that were also adjusted for baseline age, additional adjustment for smoking and education slightly attenuated all associations Table 2. Further adjustment for BMI resulted in little change in associations of h-PEF with mortality from combined non-respiratory causes Table 2 , but did slightly attenuate the associations of h-PEF with respiratory mortality.

Consequently, all further analyses were adjusted for smoking and years of education as well as baseline age in 5-year categories and area of residence strata , but were done separately according to follow-up period. The HRs in other categories of h-PEF and at later follow-up intervals, beyond 5 years, were reduced to a lesser extent. After similar exclusions for COPD or shortness of breath, the HRs for combined non-respiratory mortality were also slightly reduced in the lowest category of h-PEF and in the first 5-years of follow-up, but there was almost no effect in higher categories of h-PEF.

Hazard ratios HR are adjusted for area, baseline age, smoking, and education. Numbers above error bars are HRs, numbers below error bars are numbers of deaths. HRs are adjusted for 5-year baseline age group, area, smoking, and education.

Peak flow also predicted death from a wide range of specific causes Figure 3 , and Supplementary Table S3 , available as Supplementary data at IJE online. Mortality from all cardiovascular disease was strongly associated with h-PEF Figure 2. Associations of h-PEF with CHD, stroke, and other cardiovascular causes of death were similar, although the trend for CHD mortality over the year follow-up period was not statistically significant.

Lung cancer was responsible for most of the observed inverse association of all cancer with h-PEF. There were also inverse associations of h-PEF with lung cancer, stroke, and CHD within categories of smoking and years of education, and no statistical evidence that the strengths of these associations were significantly modified by smoking Table 3 or years of education Table 4.

The strengths of this study are its large size, nationally representative population sample, and long follow-up period, enabling associations of PEF with cause-specific mortality to be analysed in detail.

In common with prospective studies of FEV 1 in Western populations we found that mortality from respiratory causes and from a wide range of specific non-respiratory causes, including lung cancer, 1 , 6—8 CHD, 1—3 , 9 , 10 and stroke, 1 , 2 , 9 , 11 , 12 was associated with lung function.

Associations in the single study of FEV 1 and cause-specific mortality that was also based on the population of a developing country India 22 can be compared with the associations found in our study on the basis of HR per SD decline in lung function.

In that study, the associations of FEV 1 with respiratory and cardiovascular mortality and all cancer were slightly higher than in our study, but persons with histories of chronic disease were not excluded.

That study did not have enough deaths from lung cancer to make good comparisons. A limited number of other studies of PEF and subsequent cause—specific mortality also found associations with cardiovascular events 15 , 17 , 18 and lung-cancer mortality, 15 but these studies were small, with relatively short follow-up periods, elderly populations at baseline, and varying indices of PEF, preventing comparisons of the strengths of associations of PEF with cause-specific mortality with those found in our study.

Chronic obstructive pulmonary disease is usually characterised by a gradual decline in lung function, yet in our study, deaths attributed to COPD occurred in the first 5-year follow-up period in participants with apparently normal baseline values of h-PEF. These deaths may therefore actually have been caused by acute respiratory infections, 32 or may indicate that PEF poorly indicated airflow obstruction at baseline.

In accord with the findings in other studies, 1 and with respiratory failure being the main cause of death in severe COPD, 32 the association was strongest in participants with a physician diagnosis of COPD or with shortness of breath at baseline.

Even after the exclusion of individuals known to have respiratory disease at baseline, about half of the association remained, suggesting that the measurement of PEF may be a useful means of screening for persons at risk for future respiratory disease.

Several explanations have been proposed for the associations of lung function with non-respiratory—associated mortality. First, lung function, and particularly PEF, is well correlated with indicators of general physical and cognitive health.

Associations were stronger in the 28 participants who were excluded from the main analyses in our study because of a history of chronic disease other than COPD Supplementary Table S4 , available as Supplementary data at IJE online , and undiagnosed disease at baseline could therefore have contributed to the observed associations of PEF with mortality in the study population.

However, with the notable exception of the association of PEF with cancers other than lung cancer, most other associations of PEF with mortality persisted after the first 5-year follow-up period, and are therefore probably not completely explained by reverse causality. Associations of PEF with non-respiratory mortality are also unlikely to be explained by confounding by smoking or low socio-economic status, both of which are important risk factors for COPD in China.

However, baseline COPD was defined as a self-reported, physician-made diagnosis, and was probably also considerably under-diagnosed. A puzzling feature of our findings is the attenuation of associations of PEF with non-respiratory disease in later stages of the follow-up period. Other published studies have found associations of mortality with FEV 1 to be highly consistent over lengthy follow-up periods, 1 , 3 , 11 but we know of no comparable studies using PEF.

It is unlikely that reverse causality would have contributed much to the attenuation of associations of PEF with non-respiratory disease after the first 5-year follow-up period, but minor departure from log-linearity in some of the associations in early stages of the follow-up period would have contributed to this.

Baseline PEF might predict future respiratory decline less well than FEV 1 , but then we would also expect to have seen attenuation in associations of PEF with respiratory mortality. A weakness of the present study was that we had only the highest of the three measurements that were made of PEF, and no data on repeatability and no estimates of the decline in PEF in individuals with which to test this hypothesis. Our study suggests that further such assessments of the utility of PEF should be conducted.

Such a screening tool might be particularly useful in China, where late diagnosis of COPD adds considerably to the burden of this disease. Studies of Western populations have found that PEF also provides a useful assessment of general health status and is predictive of future hospitalizations and mortality.

Because PEF was also not strongly associated with SBP, the possibility of using PEF as part of a health-assessment to screen for individuals likely to develop cardiovascular disease, as well as identifying those at risk of respiratory disease, should be considered.

Because associations of PEF with non-fatal events may differ from its associations with mortality, further studies of PEF and incident disease are needed in China. We thank the study participants and the China DSP staff in the 45 areas in which this study was conducted. We thank Om Kurmi and Gary Whitlock for their comments at various stages of the preparation of this paper. In the Chinese population of this study, PEF was inversely associated with subsequent mortality from a range of causes, including death from non-neoplastic respiratory disease, cardiovascular diseases, and lung cancer, but not other cancers.

Inverse associations of PEF with lung cancer and cardiovascular disease were not explained by confounding with smoking or socio-economic status, or by existing disease at baseline.

In contrast to studies of Western populations that have found consistent associations of PEF with lung cancer and cardiovascular disease mortality over long periods of follow-up, these were attenuated over 15 years of follow-up in the present study.

The association of PEF with subsequent respiratory mortality was present, even after the exclusion of persons known to have COPD or reporting shortness of breath at baseline. Therefore measurement of PEF may be a useful means of screening for persons at risk for future respiratory disease. Google Scholar. Oxford University Press is a department of the University of Oxford.

It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.

Sign In or Create an Account. Sign In. Advanced Search. Search Menu. Article Navigation. Close mobile search navigation Article Navigation. Published online Oct John E. Kori L. Author information Article notes Copyright and License information Disclaimer. Gough: ude. Received Aug 13; Accepted Aug Gough and K.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Materials and Methods This prospective, cohort, pilot study was conducted in the ED over a two-month period.

Results Twenty-one total patients were enrolled in the study. Open in a separate window. Figure 1. Table 1 Patients enrolled in study. Acknowledgment The authors would like to recognize and thank the following medical students for their assistance with patient enrollment: Michael Burris, Akhil Hedge, Stephen Ryan, Nikolas Collins.

References 1. Shortness of breath prehospital treatment of respiratory distress. Journal of Emergency Medical Services. Diagnostic and therapeutic challenges in patients with coexistent chronic obstructive pulmonary disease and chronic heart failure. Journal of the American College of Cardiology.

Dyspnea differentiation index: a new method for the rapid separation of cardiac vs pulmonary dyspnea. Jackson H, Hubbard R. Detecting chronic obstructive pulmonary disease using peak flow rate: cross sectional survey. The British Medical Journal.

Monitoring pulmonary function in asthma and COPD: point-of-care testing. Annals of Pharmacotherapy. Nunn AJ, Gregg I. New regression equations for predicting peak expiratory flow in adults. Paramedic diagnostic accuracy for patients complaining of chest pain or shortness of breath. Upchurch J. COPD vs. Brater DC. Diuretic therapy. The New England Journal of Medicine.

Tell your healthcare provider if you take any medicines. This includes prescriptions, over-the-counter medicines, vitamins, and herbal supplements. Before starting daily peak flow meter measuring, your healthcare provider may have you follow a detailed schedule over 2 to 3 weeks.

This value will be used as a baseline for your daily measurements. Peak flow measurement is done 1 or more times daily at the same time of day, or whenever you are having early signs of an asthma attack.

Or you should use it when directed by your healthcare provider. Use the peak flow meter PFM before taking asthma medicine. Your healthcare provider may advise other times when using a PFM is useful. Before each use, make sure the sliding pointer on the peak flow meter is reset to the 0 mark. Take a deep breath and put the mouthpiece in your mouth. Seal your lips and teeth tightly around the mouthpiece. Blow out as hard and as fast as you can. Repeat this 3 times. The 3 readings should be close together.

If not, adjust your technique. Record only the highest of the 3 readings on a graph or in a notebook. Do not average the numbers together. The highest number is called your peak flow or personal best. Use the peak flow meter once a day, or as directed by your healthcare provider.

Measure peak flows about the same time each day. A good time might be when you first wake up, or at bedtime. If you use a new peak flow meter, you will need to find your new personal best value on the new meter. He or she may tell you to increase or change your medicines. He or she may give you other instructions to help keep your symptoms from getting worse.

Take your rescue medicine and call your healthcare provider or go to an emergency room. Your healthcare provider may give you more instructions about what to do for each peak flow zone. Health Home Treatments, Tests and Therapies. The 3 peak flow zones are noted by color and include: Green. Why might I need peak flow measurement? A peak flow meter can help you determine: When to get emergency medical care How well an asthma treatment plan is working When to stop or add medicine as directed by your healthcare provider What triggers an asthma attack, such as exercise A peak flow meter can help you manage asthma.

PFM can also be used to assess other lung problems, such as: Emphysema. What are the risks of peak flow measurement?