Diagnostic utility of appetite loss in addition to existing prediction models for community-acquired pneumonia in the elderly: a prospective diagnostic study in acute care hospitals in Japan

Abstract

ObjectiveDiagnosis of community-acquired pneumonia (CAP) in the elderly is often delayed because of atypical presentation and non-specific symptoms, such as appetite loss, falls and disturbance in consciousness. The aim of this study was to investigate the external validity of existing prediction models and the added value of the non-specific symptoms for the diagnosis of CAP in elderly patients.DesignProspective cohort study.SettingGeneral medicine departments of three teaching hospitals in Japan.ParticipantsA total of 109 elderly patients who consulted for upper respiratory symptoms between 1 October 2014 and 30 September 2016.Main outcome measuresThe reference standard for CAP was chest radiograph evaluated by two certified radiologists. The existing models were externally validated for diagnostic performance by calibration plot and discrimination. To evaluate the additional value of the non-specific symptoms to the existing prediction models, we developed an extended logistic regression model. Calibration, discrimination, category-free net reclassification improvement (NRI) and decision curve analysis (DCA) were investigated in the extended model.ResultsAmong the existing models, the model by van Vugt demonstrated the best performance, with an area under the curve of 0.75(95% CI 0.63 to 0.88); calibration plot showed good fit despite a significant Hosmer-Lemeshow test (p=0.017). Among the non-specific symptoms, appetite loss had positive likelihood ratio of 3.2 (2.0–5.3), negative likelihood ratio of 0.4 (0.2–0.7) and OR of 7.7 (3.0–19.7). Addition of appetite loss to the model by van Vugt led to improved calibration at p=0.48, NRI of 0.53 (p=0.019) and higher net benefit by DCA.ConclusionsInformation on appetite loss improved the performance of an existing model for the diagnosis of CAP in the elderly.

Diagnostic performance of food consumption for bacteraemia in patients admitted with suspected infection: a prospective cohort study

“…Furthermore, our findings were not in line with our previous study which suggested the usefulness of self-rated food consumption (using the same definition as the present study) for the diagnosis of community-acquired pneumonia in older patients who presented with upper respiratory symptoms. 11 In this previous study, food consumption with the cut-off of 50% showed Sn of 66.7%, Sp of 79.3%, LR+ of 3.2, LR– of 0.4 and DOR of 7.7 for the diagnosis of community-acquired pneumonia. 11 The previous study aimed to differentiate pneumonia from other viral infection (ie, upper respiratory infection), while we aimed to differentiate bacteraemia from other bacterial infection in the present study.…”

“… 11 In this previous study, food consumption with the cut-off of 50% showed Sn of 66.7%, Sp of 79.3%, LR+ of 3.2, LR– of 0.4 and DOR of 7.7 for the diagnosis of community-acquired pneumonia. 11 The previous study aimed to differentiate pneumonia from other viral infection (ie, upper respiratory infection), while we aimed to differentiate bacteraemia from other bacterial infection in the present study. Thus, the severity between the two conditions was less prominent in the present study than in the previous one, which might have led to the poorer performance of food consumption.…”

“…From a previous study that evaluated the diagnostic performance of food consumption for the diagnosis of community-acquired pneumonia, we used a definition of food consumption based on self-assessment of 24-hour food intake in proportion to the usual intake. 11 On admission, the physician in charge of the management of a patient during hospitalisation asked the patient ‘What percentage of usual food intake were you able to eat during the past 24 hours?’ and recorded the responses. In cases where patients could not assess food consumption by themselves (eg, those with dementia), we asked their caregivers to rate it.…”

Statistical inference for decision curve analysis, with applications to cataract diagnosis

“…They also discussed some subtle but important issues that arise when individuals in a population have different costs or benefits from a medical intervention recommended on the basis of predicted risk. Takada et al 10 investigated the external validity of existing prediction models and the added value of the nonspecific symptoms for the diagnosis of community‐acquired pneumonia in elderly patients by using net benefit analysis. Moran and Santamaria 11 investigated the importance of lactate as a risk biomarker in sepsis and septic shock by using decision curve.…”