The effect of comorbidities for the prognosis of community-acquired pneumonia: an epidemiologic study using a hospital surveillance in Japan

Antibiotic Consumption in a Cohort of Hospitalized Adults with Viral Respiratory Tract Infection

Development of antibiotic resistance, a threat to global health, is driven by inappropriate antibiotic usage. Respiratory tract infections (RTIs) are frequently treated empirically with antibiotics, despite the fact that a majority of the infections are caused by viruses. The purpose of this study was to determine the prevalence of antibiotic treatment in hospitalized adults with viral RTIs, and to investigate factors influencing the antibiotic decision-making. We conducted a retrospective observational study of patients ≥ 18 years, hospitalized in 2015-2018 with viral RTIs. Microbiological data were taken from the laboratory information system and information on antibiotic treatment drawn from the hospital records. To investigate decisions for prescribing antibiotic treatment, we evaluated relevant factors such as laboratory and radiological results, in addition to clinical signs. In 951 cases without secondary bacterial RTIs (median age 73 years, 53% female), 720 (76%) were prescribed antibiotic treatment, most frequently beta-lactamase-sensitive penicillins, but cephalosporins were prescribed as first-line in 16% of the cases. The median length of treatment (LOT) in the patients treated with antibiotics was seven days. Patients treated with antibiotics had an average of two days longer hospital stay compared to patients with no such treatment, but no difference in mortality was found. Our study revealed that there is still a role for antimicrobial stewardship to further improve antibiotic use in patients admitted for viral RTIs in a country with relatively low antibiotic consumption.

Validation of risk prediction for outcomes of severe community-acquired pneumonia among under-five children in Amhara region, Northwest Ethiopia

BACKGROUND

Globally there are over 1,400 cases of pneumonia per 100,000 children every year, where children in South Asia and Sub-Saharan Africa are disproportionately affected. Some of the cases develop poor treatment outcome (treatment failure or antibiotic change or staying longer in the hospital or death), while others develop good outcome during interventions. Although clinical decision-making is a key aspect of the interventions, there are limited tools such as risk scores to assist the clinical judgment in low-income settings. This study aimed to validate a prediction model and develop risk scores for poor outcomes of severe community-acquired pneumonia (SCAP).

METHODS

A cohort study was conducted among 539 under-five children hospitalized with SCAP. Data analysis was done using R version 4.0.5 software. A multivariable analysis was done. We developed a simplified risk score to facilitate clinical utility. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration plot. Bootstrapping was used to validate all accuracy measures. A decision curve analysis was used to evaluate the clinical and public health utility of our model.

RESULTS

The incidence of poor outcomes of pneumonia was 151(28%) (95%CI: 24.2%-31.8%). Vaccination status, fever, pallor, unable to breastfeed, impaired consciousness, CBC abnormal, entered ICU, and vomiting remained in the reduced model. The AUC of the original model was 0.927, 95% (CI (0.90, 0.96), whereas the risk score model produced prediction accuracy of an AUC of 0.89 (95%CI: 0.853-0.922. Our decision curve analysis for the model provides a higher net benefit across ranges of threshold probabilities.

CONCLUSIONS

Our model has excellent discrimination and calibration performance. Similarly, the risk score model has excellent discrimination and calibration ability with an insignificant loss of accuracy from the original. The models can have the potential to improve care and treatment outcomes in the clinical settings.

Pham S, P.M. Vo T, X. Duong C, A. Perwitasari D, H.K. Truong N, T.H. Quach D, N.P. Nguyen T, T.T. Duong V, M. Nguyen P, H. Nguyen T, Taxis K, Nguyen T. Pneumonia: Drug-Related Problems and Hospital Readmissions

Pneumonia is one of the most common infectious diseases and the fourth leading cause of death globally. According to US statistics in 2019, pneumonia is the most common cause of sepsis and septic shock. In the US, inpatient pneumonia hospitalizations account for the top 10 highest medical costs, totaling $9.5 billion for 960,000 hospital stays. The emergence of antibiotic resistance in the treatment of infectious diseases, including the treatment of pneumonia, is a globally alarming problem. Antibiotic resistance increases the risk of death and re-hospitalization, prolongs hospital stays, and increases treatment costs, and is one of the greatest threats in modern medicine. Drug-related problems (DRPs) in pneumonia - such as suboptimal antibiotic indications, prolonged treatment duration, and drug interactions - increase the rate of antibiotic resistance and adverse effects, thereby leading to an increased burden in treatment. In a context in which novel and effective antibiotics are scarce, mitigating DRPs in order to reduce antibiotic resistance is currently a prime concern. A variety of interventions proven useful in reducing DRPs are antibiotic stewardship programs, the use of biomarkers, computerized physician order entries and clinical decision support systems, and community-acquired pneumonia scores.

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient's unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.

Hospitalization of mild cases of community-acquired pneumonia decreased more than severe cases during the COVID-19 pandemic

OBJECTIVE

The coronavirus disease 2019 (COVID-19) pandemic has affected all healthcare systems. This study aimed to assess the impact of the COVID-19 pandemic on the number and severity of cases of community-acquired pneumonia (CAP) in Japan.

METHODS

Using claims data from the Quality Indicator/Improvement Project (QIP) database, urgent cases of inpatients for CAP from 01 August 2018 to 30 July 2020 were included. The monthly ratios of inpatient cases were compared from August 2018 to July 2019 and August 2019 to July 2020 as a year-over-year comparison. These ratios were also compared according to the "A-DROP" severity score, and an interrupted time series (ITS) analysis was performed to evaluate the impact of the COVID-19 pandemic on the monthly number of inpatient cases.

RESULTS

This study included a total of 67,900 inpatient cases for CAP in 262 hospitals. During the COVID-19 pandemic (defined as the period between March and July 2020) the number of inpatient cases for CAP drastically decreased compared with the same period in the previous year (-48.1%), despite a temporary reduction in the number of other urgent admissions. The number of inpatient cases decreased according to the severity of pneumonia. Milder cases showed a greater decrease in the year-over-year ratio than severe ones: mild -55.2%, moderate -45.8%, severe -39.4%, and extremely severe -33.2%. The ITS analysis showed that the COVID-19 pandemic significantly reduced the monthly number of inpatient cases for CAP (estimated decrease: -1233 cases; 95% CI -521 to -1955).

CONCLUSIONS

This study showed a significant reduction in the number of inpatient cases for CAP during the COVID-19 pandemic in Japan. The milder cases showed a greater decrease in the year-over-year ratio of the number of inpatient cases.

Myocardial injury determination improves risk stratification and predicts mortality in COVID-19 patients

BACKGROUND

Despite being associated with worse prognosis in patients with COVID-19, systematic determination of myocardial injury is not recommended. The aim of the study was to study the effect of myocardial injury assessment on risk stratification of COVID-19 patients.

METHODS

Seven hundred seven consecutive adult patients admitted to a large tertiary hospital with confirmed COVID-19 were included. Demographic data, comorbidities, laboratory results and clinical outcomes were recorded. Charlson comorbidity index (CCI) was calculated in order to quantify the degree of comorbidities. Independent association of cardiac troponin I (cTnI) increase with outcomes was evaluated by multivariate regression analyses and area under curve. In addition, propensity-score matching was performed to assemble a cohort of patients with similar baseline characteristics.

RESULTS

In the matched cohort (mean age 66.76 ± 15.7 years, 37.3% females), cTnI increase above the upper limit was present in 20.9% of the population and was associated with worse clinical outcomes, including all-cause mortality within 30 days (45.1% vs. 23.2%; p = 0.005). The addition of cTnI to a multivariate prediction model showed a significant improvement in the area under the time-dependent receiver operating characteristic curve (0.775 vs. 0.756, DC-statistic = 0.019; 95% confidence interval 0.001-0.037). Use of renin-angiotensin-aldosterone system inhibitors was not associated with mortality after adjusting by baseline risk factors.

CONCLUSIONS

Myocardial injury is independently associated with adverse outcomes irrespective of baseline comorbidities and its addition to multivariate regression models significantly improves their performance in predicting mortality. The determination of myocardial injury biomarkers on hospital admission and its combination with CCI can classify patients in three risk groups (high, intermediate and low) with a clearly distinct 30-day mortality.