The Prognostic Significance of Respiratory Rate in Patients With Pneumonia
A retrospective analysis of data from 705 928 hospitalized patients in Germany from 2010–2012
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Background: Measurement of the respiratory rate is an important instrument for assessing the severity of acute disease. The respiratory rate is often not measured in routine practice because its clinical utility is inadequately appreciated. In Germany, documentation of the respiratory rate is obligatory when a patient with pneumonia is hospitalized. This fact has enabled us to study the prognostic significance of the respiratory rate in reference to a large medical database.
Methods: We retrospectively analyzed data from the external quality-assurance program for community-acquired pneumonia for the years 2010–2012. All patients aged 18 years or older who were not mechanically ventilated on admission were included in the analysis. Logistic regression was used to determine the significance of the respiratory rate as a risk factor for in-hospital mortality.
Results: 705 928 patients were admitted to the hospital with community-acquired pneumonia (incidence: 3.5 cases per 1000 adults per year). The in-hospital mortality of these patients was 13.1% (92 227 persons). The plot of mortality as a function of respiratory rate on admission was U-shaped and slanted to the right, with the lowest mortality at a respiratory rate of 20/min on admission. If patients with a respiratory rate of 12–20/min are used as a baseline for comparison, patients with a respiratory rate of 27–33/min had an odds ratio (OR) of 1.72 for in-hospital death, and those with a respiratory rate above 33/min had an OR of 2.55. Further independent risk factors for in-hospital death were age, admission from a nursing home, hospital, or rehabilitation facility, chronic bedridden state, disorientation, systolic blood pressure, and pulse pressure.
Conclusion: Respiratory rate is an independent risk marker for in-hospital mortality in community-acquired pneumonia. It should be measured when patients are admitted to the hospital with pneumonia and other acute conditions.
Measuring the respiratory rate is an important and simple tool for assessing the severity of acute cardiorespiratory and metabolic diseases.
The first British Thoracic Society survey (1982–1983) on prognostic factors for community-acquired pneumonia revealed a close association between respiratory rate and mortality (1). The mortality in this study rose from 0 for a respiratory rate below 20/min to 1.7%, 9% and 16% for respiratory rate values in the ranges 20 to 29, 30 to 39, and 40 to 49, respectively (1). The prognostic significance of the respiratory rate was confirmed in numerous studies about acute respiratory infections in different age groups (2–5). Accordingly, the respiratory rate is included in standard prognostic tools, such as the CRB 65 Index (confusion, respiratory rate, blood pressure, age ≥ 65 years) or the Pneumonia Severity Index (PSI or FINE Score) (6, 7). Although the German and international guidelines recommend the use of these scores (8–10), the respiratory rate is often not recorded in acute care situations, or the need for monitoring the respiratory rate is questioned (11–15). The main reason for that is the lack of awareness of the prognostic significance of this vital sign (13–15).
Since the introduction of mandatory external quality assurance in 2005, the respiratory rate of patients with community-acquired pneumonia is recorded on admission and on discharge. The objective of this analysis is to study the prognostic significance of the respiratory rate based on the external quality assurance data collected from an unselected patient population with community-acquired pneumonia.
Data of the mandatory external quality assurance from 2010 to 2012 in the clinical area Community-acquired pneumonia were analyzed. The data set includes all adults (≥18 years) who received inpatient treatment in a German hospital with the principal diagnosis of community-acquired pneumonia. Patients were identified based on the ICD code of the DRG (Diagnosebezogene Fallgruppen, German Diagnosis-Related Groups) coding with pneumonia as principal diagnosis (eBox 1). Patients with severe immunodeficiency (such as leukemia or HIV infection) and hospital-acquired pneumonias (eBox 2) were excluded. Data were collected on type of admission (from nursing facility, hospital or rehabilitation facility), bedridden state, state of consciousness, respiratory rate and blood pressure on hospital admission (eFigure 1). The method how to measure the respiratory rate or the procedure is not prescribed. The breaths should be counted over a period of at least 30 seconds, ideally of one minute. In the 2010 data year, logistic regressions were first introduced to promote fair risk comparison (for example between hospitals), taking into consideration (nearly) all patients admitted with community-acquired pneumonia. With this method, the impact of the respiratory rate can be analyzed while simultaneously taking into account/adjusting other prognostic factors. Based on this approach, the following risk-adjusted analyses were performed (16).
To evaluate the respiratory rate on admission as a risk factor for hospital mortality, a logistic regression was performed including all patients (≥18 years) who did not receive mechanical ventilation at the time of admission. Adjustments were performed on the following parameters: age, sex, admission from nursing facility, hospital or rehabilitation facility, bedridden state, state of consciousness, and blood pressure on hospital admission. Calculation of the hospital standardized mortality ratio (HSMR) in relation to respiratory rate was based on these risk factors used in the model. These were included in the standardization with the respective regression coefficient. Patients without records of the respiratory rate and/or the blood pressure on admission, patients with implausible blood pressure values (<20 mmHg) and respiratory rates (<6/min or >49/min) were excluded.
Statistical analysis was performed using IBM SPSS 20.0.0.
Between 2010 and 2012, altogether 705 928 adult patients were treated on an in-patient basis for community acquired pneumonia. With 67.1 million adults (≥18 years) living in Germany, this represents an average annual incidence of hospital admissions for pneumonia of 3.5 per 1000 inhabitants above 18 years. Of these patients, 13.1% (92 277) died during their hospital stays. 692 950 patients were not ventilated on admission. For 643 356 of the remaining patients, admission respiratory rate data were available; of these, 641 661 patients had plausible values, i.e. an admission respiratory rate between 6/min and 49/min and a systolic blood pressure of more than 20 mmHg. Of these evaluable 641 661 patients, 80 293 died (12.5%).
About half of these patients had respiratory rates between 12 and 20/min (normal range). Less than 1% had values below 12/min (Table 1). The hospital standardized mortality ratio (HSMR) of the patients in relation to the respiratory rate shows a right-skewed U-shaped distribution, with the lowest probability of dying at about 20/min (Figure 1). In a binomial logistic regression analysis of the 2010–2012 data, the admission respiratory rate was one of several independent risk factors for hospital mortality. The risk of dying significantly increases on both admission respiratory rates above 20/min and below 12/min (Figure 2). The odds ratio for patients with respiratory rates:
- between 21 and 23/min is 1.20
- between 24 and 26/min is 1.33
- between 27 and 33/min is 1.72 and
- above 33/min is 2.55 in comparison with patients with respiratory rates between 12 and 20/min.
Other independent risk factors are age, admission from nursing facility, hospital or rehabilitation facility, chronic bedridden state, disorientation, systolic blood pressure and pulse amplitude (Table 2).
Respiratory rate and prognosis in pneumonia
With over 230 000 hospital admissions per year, community-acquired pneumonia is one of the most common acute conditions in German hospitals. More than 10% of these patients die during their hospital stay (www.sqg.de/ergebnisse/leistungsbereiche/ambulant-erworbene-pneumonie.html). Due to the large numbers and the high mortality among these patients, an early and rather simple prognostic assessment is required. Measuring the respiratory rate on admission is well suited for early risk stratification: Both decreased and increased respiratory rates on admission are associated with significantly increased hospital mortality rates. A comparatively mild tachypnea of 21–23/min already yields an odds ratio of 1.20 (95% CI: 1.17–1.23). The risk of dying rises further with increasing respiratory rate: with respiratory rates above 33/min the odds ratio is 2.55 (Table 2).
This relationship between mortality and respiratory rate on admission was first reported in a survey of the British Thoracic Society with 453 pneumonia patients which was published in 1987 (1). It can also be demonstrated in Germany (Figure).
The respiratory rate is an integral part of established prognostic tools such as the CRB-65 index or the PSI (6,7). Measuring the respiratory rate for calculating the CRB-65 index is also recommended in the S3 guideline for outpatient patients with pneumonia to help with the decision whether a patient should be admitted to hospital (recommendation level B) (8). In the external quality assurance for Community-acquired pneumonia, the documentation of the respiratory rate is required for the calculation of the CRB-65 index, among others, and thus for risk adjustment. Without reliable documentation of the respiratory rate, risk adjustment via the CRB-65 index cannot be performed. Moreover, with missing or incorrect documentation the respiratory rate is lost as a parameter for developing future risk adjustment tools.
Respiratory rate as marker of acute disease
In acute bronchial asthma, pulmonary embolism or heart failure, the respiratory rate is an important prognostic parameter as well (17–19). Because hypercapnia, hypoxia and metabolic acidosis, amongst others, lead to an increase in respiratory rate, it is logical that the respiratory rate can be used to detect and monitor these conditions, regardless of the underlying disease. Therefore, measuring the respiratory rate may support the early identification of high-risk patients. This was demonstrated for patients in emergency departments, in general wards or after surgery (20–24). For example, the respiratory rate was the parameter best suited to identify high-risk patients among 1695 emergency department patients (25). Likewise, in the prediction of cardiac arrest on a general ward, the respiratory rate was superior to other physiological parameters, such as hypoxia and systolic blood pressure (26, 27). Interestingly, a recently published analysis of more than a million sets of vital data of patients in a US hospital found an association between the deviation of the respiratory rate from normal and hospital mortality of a size similar to that demonstrated for the external quality assurance pneumonia data (Figure) (28). In early warning systems, which trigger the deployment of hospital emergency teams, measuring the respiratory rate is regularly included and again one of the best predictive parameters (11, 20, 23, 25). If the respiratory rate is not measured, these tools cannot be used or the alarm threshold is not reached. Thus, abnormal respiratory rates should be further investigated while these patients require close monitoring (e.g. on display devices).
Measuring of respiratory rate
The most commonly used method to determine the respiratory rate is discontinuous manual measurement by counting the respiratory chest movements (via inspection or auscultation). In adult patients, the respiratory rate can also be measured manually with sufficient reliability (good intra- and inter-observer reliability) (29, 30). Taking into consideration the variability of breathing, a period of at least 30 seconds should be allowed for measuring. Even more accurate results can be obtained by counting the respiratory rate over a period of 60 seconds or in two blocks of 30 second intervals (31). Capnography, the measurement of CO2 concentrations in the expired air, is considered the gold standard of continuous monitoring. Alternative technologies include impedance pneumography (recording of chest impedance changes during in- and expiration by means of chest wall electrodes) or the detection of breathing-induced amplitude modulation of R-waves in electocardiography (ECG), among others. Impedance pneumography is commonly used along with continuous ECG monitoring; measurements are reliable as long as interfering factors, such as wrong electrode placement, coughing or excessive patient movements, are excluded (32).
One important limitation of the study is the diagnosis of community-acquired pneumonia using the coded principal diagnosis and the exclusion of hospital-acquired pneumonias and pneumonias associated with severe immunodeficiency using coded secondary diagnoses. Pneumonia patients coded with another principal diagnosis (e.g. sepsis) may have been missed, while patients with hospital-acquired pneumonias or severe immunodeficiency may have been included if the secondary diagnosis was not coded. The impact of comorbidities could not be included in the analysis of independent risk factors for hospital mortality as these were not systematically recorded with this method. This is one of the reasons why the adjustment only has a moderate Nagelkerke’s pseudo-R2.
The validity of the analyzed data depends on the validity of the measuring method and the quality of documentation. While for parameters such as age or survival a high level of validity can be expected, a higher error rate has to be assumed for the measurement and documentation of the respiratory rate, for example. With more than 200 000 data sets per year from over 1200 hospitals, reviewing individual cases is not possible. Thus, implausible values or values under 6/min or above 49/min which, based on clinical experience, are rather difficult to measure accurately were excluded from this study. In the actual quality assurance program, statistical abnormality identification with feedback to the affected hospitals (“structured dialogue“) and random sampling with second acquisition of selected data fields were used for data validation. Moreover, with quality assurance in the clinical area Pneumonia in place since 2005, the participants were familiar with it. A particular strength of this study is that virtually all hospitalized patients in Germany with community-acquired pneumonia were included.
Potential for improvement and conclusion
Measuring the respiratory rate is a simple and reliable tool to assess the prognosis in patients with pneumonia and other acute diseases.
Studies and also the discussion related to the external quality assurance in the clinical area Pneumonia show that measuring and documenting the respiratory rate is still not generally accepted (11–15).
To improve the measurement and documentation of vital signs in general and of the respiratory rate in particular, more awareness of their proven importance for patient care should be raised among nurses and doctors during their education and training. Training to this effect has been proven to result in significant improvements. For example, training and audits as part of the implementation of an “early-warning system” on general wards increased the level of respiratory rate documentation from 30% to 91%, while in an emergency department environment, vital signs documentation climbed from 78% to 88% (33, 34).
Conflict of interest statement
All authors are members of the Federal Experts’ Working Group on Pneumonia of the AQUA Institute.
PD Strauß has received fees for consultancy from Swedish Orphan Biovitrum, Biotest and Pfizer. He has received reimbursements for congress participation fees from Bayer Vital, Pfizer and Infetcopharm. He has received reimbursement for travel and accommodation expenses and fees for the preparation of scientific meetings from Bayer Vital, Pfizer, Infectopharm, and MSD.
The remaining authors declare that no conflict of interest exists.
Manuscript received on: 18 September 2012; revised version accepted on 15 May 2014.
Translated from the original German by Ralf Thoene, MD.
PD Dr. med. Richard Strauß
Medizinische Klinik 1, Universitätsklinikum Erlangen
Ulmenweg 18, 91054 Erlangen, Germany
@eBoxes and eFigure:
Public Health Laboratory Service. Q J Med 1987; 62: 195–220. MEDLINE
Centre for Thoracic Diseases in the Ruhr Area, EVK Herne and Augusta-Kranken-Anstalt Bochum, Departments of Pneumology and Infectious Diseases, Bochum: Prof. Dr. med. Ewig
AQUA – Institute for Applied Quality Improvement and Research in Health Care GmbH Göttingen: Dr. med. Richter, Dr. rer. nat. König, PD Dr. med. Heller
Helios Klinikum Emil von Behring, Berlin: Prof. Dr. med. Bauer
|1.|| Community-acquired pneumonia in adults in British hospitals in 1982–1983: a survey of aetiology, mortality, prognostic factors and outcome. The British Thoracic Society and the |
Public Health Laboratory Service. Q J Med 1987; 62: 195–220. MEDLINE
|2.||Rajesh VT, Singhi S, Kataria S: Tachypnoea is a good predictor of hypoxia in acutely ill infants under 2 months. Arch Dis Child 2000; 82: 46–9. CrossRef PubMed Central|
|3.||Garcia-Ordonez MA, Garcia-Jimenez JM, Paez F, et al.: Clinical aspects and prognostic factors in elderly patients hospitalised for community-acquired pneumonia. Eur J Clin Microbiol Infect Dis 2001; 20: 14–9. CrossRef MEDLINE|
|4.||McFadden JP, Price RC, Eastwood HD, Briggs RS: Raised respiratory rate in elderly patients: a valuable physical sign. Br Med J (Clin Res Ed) 1982; 284: 626–7. CrossRef MEDLINE|
|5.||Ma HM, Tang WH, Woo J: Predictors of in-hospital mortality of older patients admitted for community-acquired pneumonia. Age Ageing; 40: 736–41. CrossRef MEDLINE|
|6.||Lim WS, van der Eerden MM, Laing R, et al.: Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax 2003; 58: 377–82. CrossRef MEDLINE PubMed Central|
|7.||Fine MJ, Auble TE, Yealy DM, et al.: A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med 1997; 336: 243–50. CrossRef MEDLINE|
|8.||Hoffken G, Lorenz J, Kern W, et al.: Epidemiology, diagnosis, antimicrobial therapy and management of community-acquired pneumonia and lower respiratory tract infections in adults. Guidelines of the Paul-Ehrlich-Society for Chemotherapy, the German Respiratory Society, the German Society for Infectiology and the Competence Network CAPNETZ Germany. Pneumologie 2009; 63: e1–68. MEDLINE|
|9.||Woodhead M, Blasi F, Ewig S, et al.: Guidelines for the management of adult lower respiratory tract infections—full version. Clin Microbiol Infect 2011; 17 Suppl 6: E1–59. CrossRef MEDLINE|
|10.||Mandell LA, Wunderink RG, Anzueto A, et al.: Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis 2007; 44 Suppl 2: 27–72. CrossRef MEDLINE|
|11.||Hillman K, Chen J, Cretikos M, et al.: Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. Lancet 2005; 365: 2091–7. CrossRef MEDLINE|
|12.||Hodgetts TJ, Kenward G, Vlachonikolis IG, Payne S, Castle N: The identification of risk factors for cardiac arrest and formulation of activation criteria to alert a medical emergency team. Resuscitation 2002; 54: 125–31. CrossRef MEDLINE|
|13.||Hogan J. Why don’t nurses monitor the respiratory rates of patients? Br J Nurs 2006; 15: 489–92. CrossRef MEDLINE|
|14.||Butler-Williams C, Cantrill N, Maton S: Increasing staff awareness of respiratory rate significance. Nurs Times 2005; 101: 35–7. CrossRef|
|15.||Cretikos MA, Bellomo R, Hillman K, Chen J, Finfer S, Flabouris A: Respiratory rate: the neglected vital sign. Med J Aust 2008; 188: 657–9. MEDLINE|
|16.||Rochon J, Tasche K: Risikoadjustierung. In: AQUA-Institut (ed.): Qualitätsreport 2009. Göttingen: AQUA-Institut GmbH; 2010: 145–9.|
|17.||Fischl MA, Pitchenik A, Gardner LB: An index predicting relapse and need for hospitalization in patients with acute bronchial asthma. N Engl J Med 1981; 305: 783–9. CrossRef MEDLINE|
|18.||Bhatia RS, Tu JV, Lee DS, et al.: Outcome of heart failure with preserved ejection fraction in a population-based study. N Engl J Med 2006; 355: 260–9. CrossRef MEDLINE|
|19.||Aujesky D, Roy PM, Le Manach CP, et al.: Validation of a model to predict adverse outcomes in patients with pulmonary embolism. Eur Heart J 2006; 27: 476–81. CrossRef MEDLINE|
|20.||Kellett J, Deane B: The Simple Clinical Score predicts mortality for 30 days after admission to an acute medical unit. QJM 2006; 99: 771–81. CrossRef MEDLINE|
|21.||Gravelyn TR, Weg JG: Respiratory rate as an indicator of acute respiratory dysfunction. JAMA 1980; 244: 1123–5. CrossRef MEDLINE|
|22.||Goldhill DR, Worthington L, Mulcahy A, Tarling M, Sumner A: The patient-at-risk team: identifying and managing seriously ill ward patients. Anaesthesia 1999; 54: 853–60. CrossRef MEDLINE|
|23.||Goldhill DR, McNarry AF: Physiological abnormalities in early warning scores are related to mortality in adult inpatients. Br J Anaesth 2004; 92: 882–4. CrossRef MEDLINE|
|24.||Goldhill DR, McNarry AF, Mandersloot G, McGinley A: A physiologically-based early warning score for ward patients: the association between score and outcome. Anaesthesia 2005; 60: 547–53. CrossRef MEDLINE|
|25.||Subbe CP, Davies RG, Williams E, Rutherford P, Gemmell L: Effect of introducing the Modified Early Warning score on clinical outcomes, cardio-pulmonary arrests and intensive care utilisation in acute medical admissions. Anaesthesia 2003; 58: 797–802. CrossRef MEDLINE|
|26.||Fieselmann JF, Hendryx MS, Helms CM, Wakefield DS: Respiratory rate predicts cardiopulmonary arrest for internal medicine inpatients. J Gen Intern Med 1993; 8: 354–60. CrossRef MEDLINE|
|27.||Churpek MM, Yuen TC, Huber MT, Park SY, Hall JB, Edelson DP. Predicting cardiac arrest on the wards: a nested case-control study. Chest 2012; 141: 1170–6. CrossRef MEDLINE PubMed Central|
|28.||Bleyer AJ, Vidya S, Russell GB, et al.: Longitudinal analysis of one million vital signs in patients in an academic medical center. Resuscitation 2011; 82: 1387–92. CrossRef MEDLINE|
|29.||Lim WS, Carty SM, Macfarlane JT, et al.: Respiratory rate measurement in adults--how reliable is it? Respir Med 2002; 96: 31–3. CrossRef MEDLINE|
|30.||Brookes CN, Whittaker JD, Moulton C, Dodds D: The PEP respiratory monitor: a validation study. Emerg Med J 2003; 20: 326–8. CrossRef PubMed Central|
|31.||Simoes EA, Roark R, Berman S, Esler LL, Murphy J. Respiratory rate: measurement of variability over time and accuracy at different counting periods. Arch Dis Child 1991; 66: 1199–203. CrossRef MEDLINE PubMed Central|
|32.||Gaucher A, Frasca D, Mimoz O, Debaene B: Accuracy of respiratory rate monitoring by capnometry using the Capnomask(R) in extubated patients receiving supplemental oxygen after surgery. Br J Anaesth; 108: 316–20. CrossRef MEDLINE|
|33.||McBride J, Knight D, Piper J, Smith GB: Long-term effect of introducing an early warning score on respiratory rate charting on general wards. Resuscitation 2005; 65: 41–4. CrossRef MEDLINE|
|34.||di Martino P, Leoli F, Cinotti F, et al.: Improving vital sign documentation at triage: an emergency department quality improvement project. J Patient Saf 2011; 7: 26–9. CrossRef MEDLINE|