Predicting acute respiratory infection in Chinese healthy individuals: A effective way of patient care

1 Introduction

Acute respiratory infection is one of the foremost causes of emergency department (ED) visits. There has been a significantly steady increase in the number of emergency department (ED) visits among patients with acute respiratory infection in China over the past decades and this continues to increase each year (Calder et al., 2015; Sauvin et al., 2013). This may be attributed to many reasons such as lack of consistent access to general physicians which often forces caretakers to seek medical attention at emergency departments. The most common reasons for unscheduled ED return visits are inadequate symptom relief, misdiagnosis, deterioration of condition, and inappropriate management, including and not limited to, inadequate patient education and patient related factors (Keith et al., 1989; Nunez et al., 2006; Chiu-Lung et al., 2008; Wu et al., 2010). Hence, focusing on factors associated with ED visits and appropriate resolution could reduce revisit rates and help improve patient satisfaction, clinical outcomes and reduce healthcare costs. Among the possible reasons of unscheduled re-visit, Gordon et al. have suggested that the diagnosis at the time of first visit could be one of key predictors of early ED return; inappropriate diagnosis may be one of chief correctable reasons of unscheduled returns to ED (Gordon et al., 1998).

For patients who re-visit ED within a short period of time after discharge, the most common reason assumed is that their initial diagnosis and/or treatment were inadequate (Tresch, 1987; Fox, 1988; O'dell, 1988). The diseases with vague or non-specific signs and symptoms are more likely to be misdiagnosed at the initial visit in a high volume healthcare setting like the ED. Patients suffering from infectious diseases often present with vague symptoms (Gambert and Escher, 1988; Gupta et al., 1988) and may only begin to show text-book signs through further evolution of the disease process. Patients with such non-specific presentations are at a high risk of being misdiagnosed resulting in early release from the ED; this can eventually lead to an unscheduled return to ED within a short duration after discharge (Gambert and Escher, 1988; Gupta et al., 1988).

Prediction of acute respiratory infection based on early symptoms is one of the important achievements in current medical practice. For the optimal care and success of medical treatment, prediction of outcome of diseases condition with some accuracy plays a vital role in achieving success of medical intervention, and it is helpful for patients and consulting physician. Early prediction in outcome helps to improve healing potentials, and give chance to take decision about the future treatments and care intensity and to avoid ineffective diagnostic procedure. Moreover, the understanding of forthcoming consequences of patients’ illness is the mainstay of the regaining process [8–13]. Early prediction of outcomes is very important in diseases with high disability rate, and plays a vital role in avoiding emergency conditions associated with diseases. In the emergency setting, clinical decision based on the patient’s condition or illness has high impact on mortality and death among patients of critical illness (Gambert and Escher, 1988; Gupta et al., 1988)

Several anti-infective agents are available in the treatment of acute respiratory infection. Use of anti-infective agents has hardly been directed by laboratory finding. We hypothesis the clinical forecasters of acute respiratory can assist in making right treatment decision and avoid needless use of antibiotic. We therefore designed this nurse led care research designed to observe predictive factors this can assist in making right treatment decision and avoid needless use of antibiotic. Our study may serve the basis for conducting large multi-centric, multi-country, clinical study which assesses predictive factors this can assist in making right treatment decision and avoid needless use of antibiotic.

2 Materials and methods

3 Results

Medical records of total of 1500 adults who were suffering from influenza like symptoms were screened phase during Jan 2012 to Dec 2016 (4 year data). Of these, a total of 1220 adults who were suffering from influenza like symptoms who attended our hospital at the time of their consultation were selected for data analysis. All the selected subjects agreed to use their data in our study. The mean (SD) age of identified subjects with respiratory tract infection (influenza) was 32.23 (1.4) years, whereas mean (SD) age of identified subjects without respiratory tract infection (influenza) was 33.13 (2.2) years, who were visited during Jan 2012 to Dec 2016 were studied. The proportion of male patients was higher in both the groups. Majority of patients had symptoms onset time within 36 h. Also the patients who had respiratory tract infection (influenza), majority of them were diagnosed with type B followed by type A and both. There were few patients in respiratory tract infection (influenza) group who had unidentified type of influenza. Also Demographic and clinical characteristic of identified subjects are presented in Table 1.

Medical records of 1220 adults who were suffering from influenza like symptoms at baseline were reviewed by nurse. Of total subjects, a total of 824 (67.5%) were identified to have acute respiratory infection (influenza). As indicated in Table 2, significantly higher incidence of cough, high body tem (fever) and both was noted among the patients who had acute respiratory infection (influenza) compared to those patients with no acute respiratory infection (influenza). Among the reported baseline symptoms, fever and cough were found most common among patients who were diagnosed with acute respiratory infection (influenza). The most common reported symptoms among patients who diagnosed with respiratory tract infection (influenza) are weakness, muscle pain, cold and cough. In subjects who were not diagnosed with respiratory tract infection (influenza) reported to have weakness and muscle pain as most commonly reported signs and symptoms. The subjects with respiratory tract infection (influenza) were more likely to have cough, high body temperature fever than subject who were not diagnosed with respiratory tract infection (influenza) (Table 3).

A logistic regression was performed for all the baseline signs and symptoms, and model was run which showed, fever and cough were found to be finest explanatory variables. Parameters such as headache and muscle pain which is having been poor explanatory variables were excluded from the model. The symptom “Feverishness” has not been included as the term “fever” has already been included in this analysis. Mixed model analysis revealed high correlation of two symptoms (cough and fever) with acute respiratory infection (influenza). Our study results suggested that Chinese patients who experienced cough and fever within first 48 h of onset of acute respiratory infection are more likely to have influenza, and thus appropriate antiviral therapy is recommended in patients with acute respiratory infection (influenza). Univariate analysis revealed that the patients who had high body temperature (Fever) and cough were more likely to have acute respiratory infection (influenza).

The similar trend was observed in analysis conducted by multivariate analysis (Table 4). Multivariate analysis also revealed that the patients who had high body temperature (Fever) and cough were more likely to have acute respiratory infection (influenza). This indicates that the that Chinese patients who experienced cough and fever within first 48 h of onset of acute respiratory infection are more likely to have influenza, and thus appropriate antiviral therapy is recommended in patients with acute respiratory infection (influenza).We observed significantly higher incidence of cough, high body tem (fever) and both was noted among the patients who had acute respiratory infection (influenza) compared to those patients with no acute respiratory infection (influenza). Mixed model analysis revealed high correlation of two symptoms (cough and fever) with acute respiratory infection (influenza).

4 Discussion

Prediction of acute respiratory infection based on early symptoms is one of the effective ways of patient care. For the optimal care and success of medical treatment, prediction of outcome of diseases condition with some accuracy plays a vital role in achieving success of medical intervention, and it is helpful for patients and consulting physician. Early prediction in outcome helps to improve healing potentials, and give chance to take decision about the future treatments and care intensity and to avoid ineffective diagnostic procedure. Moreover, the understanding of forthcoming consequences of patients’ illness is the mainstay of the regaining process (Tresch, 1987; Fox, 1988; O'dell, 1988). In the emergency setting, clinical decision based on the patient’s condition or illness has high impact on mortality and death among patients of critical illness (O'dell, 1988). Several anti-infective agents are available in the treatment of acute respiratory infection. Use of anti-infective agents has hardly been directed by laboratory finding. We hypothesis the clinical forecasters of acute respiratory can assist in making right treatment decision and avoid needless use of antibiotic. We therefore designed this nurse led care research designed to observe predictive factors this can assist in making right treatment decision and avoid needless use of antibiotic. Our study may serve the basis for conducting large multi-centric, multi-country, clinical study which assesses predictive factors this can assist in making right treatment decision and avoid needless use of antibiotic. This nurse led care research designed to observe predictive factors this can assist in making right treatment decision and avoid needless use of antibiotic. In this retrospective study, medical records of adults who visited at our hospital and who were suffering from acute respiratory infection and had influenza like symptoms which includes high body temperature, body ache, muscle pain, cough, and sore throat. Based on the signs and symptoms, patients were subjected in laboratory examination and culture test. Medical records of Chinese patients with confirm diagnosis of influenza was selected. We also assessed the medical records of patients with no influenza based on laboratory investigation. Correlation of signs and symptoms with laboratory examination was performed to identify the best predictive factors of acute respiratory infection which can assist in making right treatment decision and avoid needless use of antibiotic.

In this study, medical records of adults who were suffering from influenza like symptoms at baseline were reviewed by nurse. Of total subjects, 67% of enrolled patient were identified to have acute respiratory infection (influenza). We observed significantly higher incidence of cough, high body tem (fever) and both was noted among the patients who had acute respiratory infection (influenza) compared to those patients with no acute respiratory infection (influenza). Mixed model analysis revealed high correlation of two symptoms (cough and fever) with acute respiratory infection (influenza). Majority of patients had symptoms onset time within 36 h. Also the patients who had respiratory tract infection (influenza), majority of them were diagnosed with type B followed by type A and both. There were few patients in respiratory tract infection (influenza) group who had unidentified type of influenza. Significantly higher incidence of cough, high body tem (fever) and both was noted among the patients who had acute respiratory infection (influenza) compared to those patients with no acute respiratory infection (influenza). Among the reported baseline symptoms, fever and cough were found most common among patients who were diagnosed with acute respiratory infection (influenza). The most common reported symptoms among patients who diagnosed with respiratory tract infection (influenza) are weakness, muscle pain, cold and cough. In subjects who were not diagnosed with respiratory tract infection (influenza) reported to have weakness and muscle pain as most commonly reported signs and symptoms. The subjects with respiratory tract infection (influenza) were more likely to have cough, high body temperature fever than subject who were not diagnosed with respiratory tract infection (influenza). A logistic regression was performed for all the baseline signs and symptoms, and model was run which showed, fever and cough were found to be finest explanatory variables. Parameters such as headache and muscle pain which is having been poor explanatory variables were excluded from the model. The symptom “Feverishness” has not been included as the term “fever” has already been included in this analysis. Mixed model analysis revealed high correlation of two symptoms (cough and fever) with acute respiratory infection (influenza). Our study results suggested that Chinese patients who experienced cough and fever within first 48 h of onset of acute respiratory infection are more likely to have influenza, and thus appropriate antiviral therapy is recommended in patients with acute respiratory infection (influenza). Univariate analysis revealed that the patients who had high body temperature (Fever) and cough were more likely to have acute respiratory infection (influenza). The similar trend was observed in analysis conducted by multivariate analysis (Table 4). Multivariate analysis also revealed that the patients who had high body temperature (Fever) and cough were more likely to have acute respiratory infection (influenza). This indicates that the that Chinese patients who experienced cough and fever within first 48 h of onset of acute respiratory infection are more likely to have influenza, and thus appropriate antiviral therapy is recommended in patients with acute respiratory infection (influenza). We observed significantly higher incidence of cough, high body tem (fever) and both was noted among the patients who had acute respiratory infection (influenza) compared to those patients with no acute respiratory infection (influenza). Mixed model analysis revealed high correlation of two symptoms (cough and fever) with acute respiratory infection (influenza).

5 Conclusion

The results of this nurse led care research suggested that Chinese patients who experienced cough and fever within first 48 h of onset of acute respiratory infection are more likely to have influenza, and thus appropriate antiviral therapy is recommended in patients with acute respiratory infection (influenza). Prediction of acute respiratory infection based on early symptoms is one of the effective ways of patient care. Our study results will assist in making right treatment decision and avoid needless use of antibiotic.