Predictors of Bacteraemia in Patients with Suspected Community-Acquired Pneumonia

Utility of shaking chills as a diagnostic sign for bacteremia in adults: a systematic review and meta-analysis

BACKGROUND

Accurate prediction of bacteremia is essential for guiding blood culture collection and optimal antibiotic treatment. Shaking chills, defined as a subjective chill sensation with objective body shivering, have been suggested as a potential predictor of bacteremia; however, conflicting findings exist. To address the evidence gap, we conducted a systematic review and meta-analysis of studies to assess the diagnostic accuracy of shaking chills for predicting bacteremia among adult patients.

METHODS

We included studies reporting the diagnostic accuracy of shaking chills or chills for bacteremia. Adult patients with suspected bacteremia who underwent at least one set of blood cultures were included. Our main analysis focused on studies that assessed shaking chills. We searched these studies through CENTRAL, MEDLINE, Embase, the World Health Organization ICTRP Search Portal, and ClinicalTrials.gov. Study selection, data extraction, evaluation for risk of bias, and applicability using the QUADAS-2 tool were conducted by two independent investigators. We estimated a summary receiver operating characteristic curve and a summary point of sensitivity and specificity of the index tests, using a hierarchical model and the bivariate model, respectively.

RESULTS

We identified 19 studies with a total of 14,641 patients in which the accuracy of shaking chills was evaluated. The pooled sensitivity and specificity of shaking chills were 0.37 (95% confidence interval [CI], 0.29 to 0.45) and 0.87 (95% CI, 0.83 to 0.90), respectively. Most studies had a low risk of bias in the index test domain and a high risk of bias and a high applicability concern in the patient-selection domain.

CONCLUSIONS

Shaking chills are a highly specific but less sensitive predictor of bacteremia. Blood cultures and early initiation of antibiotics should be considered for patients with an episode of shaking chills; however, the absence of shaking chills must not lead to exclusion of bacteremia and early antibiotic treatment.

Clinical Features, Diagnostics, Etiology, and Outcomes of Hospitalized Solid Organ Recipients With Community-Acquired Pneumonia: A Retrospective Cohort Analysis

BACKGROUND

Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality worldwide. Limited evidence is available on the most effective diagnostic approaches, management strategies, and long-term outcomes for CAP in patients who have undergone solid organ transplantation.

RESEARCH QUESTION

What is the acute and long-term morbidity and mortality after CAP in organ transplant recipients?

STUDY DESIGN AND METHODS

We retrospectively analyzed hospitalizations for CAP in solid organ recipients at the largest German transplant center. The study included patients admitted between January 1, 2010, and May 31, 2021. The reported outcomes are in-hospital and 1-year mortality, risk of cardiovascular events during hospitalization and at 1 year, admission to the ICU, and risk of pneumonia with Pseudomonas aeruginosa. Multivariable binary logistic regression using stepwise forward selection was performed to determine predictive factors for pneumonia with P aeruginosa.

RESULTS

We analyzed data from 403 hospitalizations of 333 solid organ recipients. In > 60% of cases, patients had multiple comorbidities, with cardiovascular and chronic kidney disease being the most prevalent. More than one-half of the patients required oxygen supplementation after admission. In-hospital mortality (13.2%) and the death rate at 1 year postevent (24.6%) were higher than data reported from immunocompetent patients. We also observed high rates of acute cardiovascular events and events occurring 1 year after admission. Early blood cultures and bronchoscopy in the first 24 h significantly increased the odds of establishing an etiology. In our low-resistance setting, the burden of antimicrobial resistance was driven by bacteria from chronically colonized patients, mostly lung transplant recipients.

INTERPRETATION

This comprehensive analysis highlights the high morbidity associated with CAP after transplantation. It also emphasizes the need for prospective multicenter studies to guide evidence-based practices and improve outcomes for these vulnerable patients.

Predicting Bacteremia among Septic Patients Based on ED Information by Machine Learning Methods: A Comparative Study

Introduction: Bacteremia is a common but life-threatening infectious disease. However, a well-defined rule to assess patient risk of bacteremia and the urgency of blood culture is lacking. The aim of this study is to establish a predictive model for bacteremia in septic patients using available big data in the emergency department (ED) through logistic regression and other machine learning (ML) methods. Material and Methods: We conducted a retrospective cohort study at the ED of National Cheng Kung University Hospital in Taiwan from January 2015 to December 2019. ED adults (≥18 years old) with systemic inflammatory response syndrome and receiving blood cultures during the ED stay were included. Models I and II were established based on logistic regression, both of which were derived from support vector machine (SVM) and random forest (RF). Net reclassification index was used to determine which model was superior. Results: During the study period, 437,969 patients visited the study ED, and 40,395 patients were enrolled. Patients diagnosed with bacteremia accounted for 7.7% of the cohort. The area under the receiver operating curve (AUROC) in models I and II was 0.729 (95% CI, 0.718–0.740) and 0.731 (95% CI, 0.721–0.742), with Akaike information criterion (AIC) of 16,840 and 16,803, respectively. The performance of model II was superior to that of model I. The AUROC values of models III and IV in the validation dataset were 0.730 (95% CI, 0.713–0.747) and 0.705 (0.688–0.722), respectively. There is no statistical evidence to support that the performance of the model created with logistic regression is superior to those created by SVM and RF. Discussion: The advantage of the SVM or RF model is that the prediction model is more elastic and not limited to a linear relationship. The advantage of the LR model is that it is easy to explain the influence of the independent variable on the response variable. These models could help medical staff identify high-risk patients and prevent unnecessary antibiotic use. The performance of SVM and RF was not inferior to that of logistic regression. Conclusions: We established models that provide discrimination in predicting bacteremia among patients with sepsis. The reported results could inspire researchers to adopt ML in their development of prediction algorithms.

Clinical manifestation, laboratory and radiology finding, treatment and outcomes of COVID-19: A systematic review and meta-analysis

BACKGROUND

Since December 2019, coronavirus (COVID-19) spread throughout the world. The high rate of infection and its unknown nature led specialists to report the condition of patients. The aim of this study is to systematically review of symptoms, laboratory and radiologic findings, treatment, and outcomes of patients with COVID-19.

MATERIALS AND METHODS

Databases such as PubMed, Embase, Scopus, Web of Science, Google Scholar, and Cochrane were searched. Finally, 46 articles were appropriate for the aim of the study. After quality evaluation, the necessary data were extracted and meta-analysis was performed.

RESULTS

4858 articles were retrieved until March 30, 2020. After screening, the full-text of 46 articles was assessed. Of the reported cases, 31.7% had no comorbidities, 21.4% had high blood pressure, 70.6% had fever, and lymphopenia was reported in 55.2% of patients. For 16% bilateral patchy shadowing in radiography and for 51% ground-glass opacity was reported. Outcomes were remarkable for recover to death.

CONCLUSION

COVID-19 leads to healthcare problems for countries. Nonspecific symptoms have made it difficult for differential diagnoses without computed tomography-scan or corona Test, but they are not available in many countries. Therefore, this systematic review can help health care staff to make decisions based on symptoms, treatments, and outcomes..

Does This Patient Need Blood Cultures? A Scoping Review of Indications for Blood Cultures in Adult Nonneutropenic Inpatients

Guidance regarding indications for initial or follow-up blood cultures is limited. We conducted a scoping review of articles published between January 2004 and June 2019 that reported the yield of blood cultures and/or their impact in the clinical management of fever and common infectious syndromes in nonneutropenic adult inpatients. A total of 2893 articles were screened; 50 were included. Based on the reported incidence of bacteremia, syndromes were categorized into low, moderate, and high pretest probability of bacteremia. Routine blood cultures are recommended in syndromes with a high likelihood of bacteremia (eg, endovascular infections) and those with moderate likelihood when cultures from the primary source of infection are unavailable or when prompt initiation of antibiotics is needed prior to obtaining primary source cultures. In syndromes where blood cultures are low-yield, blood cultures can be considered for patients at risk of adverse events if a bacteremia is missed (eg, patient with pacemaker and severe purulent cellulitis). If a patient has adequate source control and risk factors or concern for endovascular infection are not present, most streptococci or Enterobacterales bacteremias do not require routine follow-up blood cultures.

Added value of clinical prediction rules for bacteremia in hemodialysis patients: An external validation study

Introduction

Having developed a clinical prediction rule (CPR) for bacteremia among hemodialysis (HD) outpatients (BAC-HD score), we performed external validation.

Materials & methods

Data were collected on maintenance HD patients at two Japanese tertiary-care hospitals from January 2013 to December 2015. We enrolled 429 consecutive patients (aged ≥ 18 y) on maintenance HD who had had two sets of blood cultures drawn on admission to assess for bacteremia. We validated the predictive ability of the CPR using two validation cohorts. Index tests were the BAC-HD score and a CPR developed by Shapiro et al. The outcome was bacteremia, based on the results of the admission blood cultures. For added value, we also measured changes in the area under the receiver operating characteristic curve (AUC) using logistic regression and Net Reclassification Improvement (NRI), in which each CPR was added to the basic model.

Results

In Validation cohort 1 (360 subjects), compared to a Model 1 (Basic Model) AUC of 0.69 (95% confidence interval [95% CI]: 0.59–0.80), the AUC of Model 2 (Basic model + BAC-HD score) and Model 3 (Basic model + Shapiro’s score) increased to 0.8 (95% CI: 0.71–0.88) and 0.73 (95% CI: 0.63–0.83), respectively. In validation cohort 2 (96 subjects), compared to a Model 1 AUC of 0.81 (95% CI: 0.68–0.94), the AUCs of Model 2 and Model 3 increased to 0.83 (95% CI: 0.72–0.95) and 0.85 (95% CI: 0.76–0.94), respectively. NRIs on addition of the BAC-HD score and Shapiro’s score were 0.3 and 0.06 in Validation cohort 1, and 0.27 and 0.13, respectively, in Validation cohort 2.

Conclusion

Either the BAC-HD score or Shapiro’s score may improve the ability to diagnose bacteremia in HD patients. Reclassification was better with the BAC-HD score.

Risk of bacteremia in patients presenting with shaking chills and vomiting - a prospective cohort study

Chills and vomiting have traditionally been associated with severe bacterial infections and bacteremia. However, few modern studies have in a prospective way evaluated the association of these signs with bacteremia, which is the aim of this prospective, multicenter study. Patients presenting to the emergency department with at least one affected vital sign (increased respiratory rate, increased heart rate, altered mental status, decreased blood pressure or decreased oxygen saturation) were included. A total of 479 patients were prospectively enrolled. Blood cultures were obtained from 197 patients. Of the 32 patients with a positive blood culture 11 patients (34%) had experienced shaking chills compared with 23 (14%) of the 165 patients with a negative blood culture, P = 0.009. A logistic regression was fitted to show the estimated odds ratio (OR) for a positive blood culture according to shaking chills. In a univariate model shaking chills had an OR of 3.23 (95% CI 1.35–7.52) and in a multivariate model the OR was 5.9 (95% CI 2.05–17.17) for those without prior antibiotics adjusted for age, sex, and prior antibiotics. The presence of vomiting was also addressed, but neither a univariate nor a multivariate logistic regression showed any association between vomiting and bacteremia. In conclusion, among patients at the emergency department with at least one affected vital sign, shaking chills but not vomiting were associated with bacteremia.

Rate and Predictors of Bacteremia in Afebrile Community-Acquired Pneumonia

BACKGROUND

Although blood cultures (BCs) are the "gold standard" for detecting bacteremia, the utility of BCs in patients with community-acquired pneumonia (CAP) is controversial. This study describes the proportion of patients with CAP and afebrile bacteremia and identifies the clinical characteristics predicting the necessity for BCs in patients who are afebrile.

METHODS

Bacteremia rates were determined in 4,349 patients with CAP enrolled in the multinational cohort study The Competence Network of Community-Acquired Pneumonia (CAPNETZ) and stratified by presence of fever at first patient contact. Independent predictors of bacteremia in patients who were afebrile were determined using logistic regression analysis.

RESULTS

Bacteremic pneumonia was present in 190 of 2,116 patients who were febrile (8.9%), 101 of 2,149 patients who were afebrile (4.7%), and one of 23 patients with hypothermia (4.3%). Bacteremia rates increased with the CURB-65 score from 3.5% in patients with CURB-65 score of 0 to 17.1% in patients with CURB-65 score of 4. Patients with afebrile bacteremia exhibited the highest 28-day mortality rate (9.9%). Positive pneumococcal urinary antigen test (adjusted OR [AOR], 4.6; 95% CI, 2.6-8.2), C-reactive protein level > 200 mg/L (AOR, 3.1; 95% CI, 1.9-5.2), and BUN level ≥ 30 mg/dL (AOR, 3.1; 95% CI, 1.9-5.3) were independent positive predictors, and antibiotic pretreatment (AOR, 0.3; 95% CI, 0.1-0.6) was an independent negative predictor of bacteremia in patients who were afebrile.

CONCLUSIONS

A relevant proportion of patients with bacteremic CAP was afebrile. These patients had an increased mortality rate compared with patients with febrile bacteremia or nonbacteremic pneumonia. Therefore, the relevance of fever as an indicator for BC necessity merits reconsideration.

Utility of Blood Cultures in Pneumonia

INTRODUCTION

Blood cultures are of limited utility in nonsevere community-acquired pneumonia, though routinely recommended for severe community-acquired pneumonia or health care-associated pneumonia due to perceived greater bacteremia risk, particularly with multidrug-resistant organisms. The utility of this practice is unknown.

METHODS

In this observational cohort study, we abstracted data from medical records for consecutive hospitalizations for pneumonia by adults to an academic medical center from 2014-2015. The primary outcomes included bacteremia, multidrug-resistant organism bacteremia, and appropriate management changes attributed to culture results, stratified by pneumonia classification (nonsevere community-acquired pneumonia, severe community-acquired pneumonia, or health care-associated pneumonia) and likelihood the bacteremia was due to pneumonia vs another infection. We assessed the diagnostic test performance of one or more guideline-defined risk factors for bacteremia in nonsevere community-acquired pneumonia, for whom cultures are routinely recommended.

RESULTS

Of 456 pneumonia hospitalizations, 30 (6.6%) had bacteremia, with a greater incidence in severe community-acquired pneumonia (14.7%) than nonsevere community-acquired pneumonia (7.8%) and health care-associated pneumonia (6.6%; P = .12). Seventeen bacteremia cases were likely due to pneumonia (3.7%). Only 2 (0.4%) had multidrug-resistant organisms (both health care-associated pneumonia), one of whom was due to pneumonia. Appropriate management changes occurred in 8 cases (1.8%; 7 de-escalation and 1 escalation of antibiotics); only 1 with bacteremia likely due to pneumonia (de-escalation). The one case of appropriate antibiotic escalation occurred in a patient with vancomycin-resistant Enterococcus unrelated to pneumonia. Having one or more guideline-defined risk factors did not identify bacteremia in nonsevere community-acquired pneumonia (positive likelihood ratio, 1.10; 95% confidence interval, 0.61-1.99).

CONCLUSION

Routine blood cultures in pneumonia have extremely low yield and utility irrespective of severity and risk.

Machine learning for fast identification of bacteraemia in SIRS patients treated on standard care wards: a cohort study

Bacteraemia is a life-threating condition requiring immediate diagnostic and therapeutic actions. Blood culture (BC) analyses often result in a low true positive result rate, indicating its improper usage. A predictive model might assist clinicians in deciding for whom to conduct or to avoid BC analysis in patients having a relevant bacteraemia risk. Predictive models were established by using linear and non-linear machine learning methods. To obtain proper data, a unique data set was collected prior to model estimation in a prospective cohort study, screening 3,370 standard care patients with suspected bacteraemia. Data from 466 patients fulfilling two or more systemic inflammatory response syndrome criteria (bacteraemia rate: 28.8%) were finally used. A 29 parameter panel of clinical data, cytokine expression levels and standard laboratory markers was used for model training. Model tuning was performed in a ten-fold cross validation and tuned models were validated in a test set (80:20 random split). The random forest strategy presented the best result in the test set validation (ROC-AUC: 0.729, 95%CI: 0.679–0.779). However, procalcitonin (PCT), as the best individual variable, yielded a similar ROC-AUC (0.729, 95%CI: 0.679–0.779). Thus, machine learning methods failed to improve the moderate diagnostic accuracy of PCT.

Community-acquired pneumonia requiring hospitalization: rational decision making and interpretation of guidelines

PURPOSE OF REVIEW

This review focuses on the evidence base for guideline recommendations on the diagnosis, the optimal choice, timing and duration of empirical antibiotic therapy, and the use of microbiological tests for patients hospitalized with community-acquired pneumonia (CAP): issues for which guidelines are frequently used as a quick reference. Furthermore, we will discuss possibilities for future research in these topics.

RECENT FINDINGS

Many national and international guideline recommendations, even on critical elements of CAP management, are based on low-to-moderate quality evidence.

SUMMARY

The diagnosis and management of CAP has hardly changed for decades. The recommendation to cover atypical pathogens in all hospitalized CAP patients is based on observational studies only and is challenged by two recent trials. The following years, improved diagnostic testing, radiologically by low-dose Computed Tomography or ultrasound and/or microbiologically by point-of-care multiplex PCR, has the potential to largely influence the choice and start of antibiotic therapy in hospitalized CAP patients. Rapid microbiological testing will hopefully improve antibiotic de-escalation or early pathogen-directed therapy, both potent ways of reducing broad-spectrum antibiotic use. Current guideline recommendations on the timing and duration of antibiotic therapy are based on limited evidence, but will be hard to improve.

Evaluating the appropriateness of antimicrobial treatment in hospitalized patients: a comparison of three methods

BACKGROUND

Approximately 20-50% of antimicrobial therapy in hospitalized patients is considered inappropriate, which may be associated with increased morbidity and mortality. The best method for evaluation of appropriateness is not well defined.

AIM

To evaluate the rate of appropriate antimicrobial therapy in a secondary hospital using three different methods, and determine the rate of agreement between the different methods.

METHODS

A point prevalence study included all adult hospitalized patients receiving systemic antimicrobial therapy during 2016, screened on a single day. Clinical, laboratory and therapeutic data were collected from patient files, and appropriateness was rated with a qualitative evaluation by expert opinion. In addition, a quantitative evaluation was performed according to 11 quality indicators (QIs) rated for each patient. A strict definition of appropriateness was fulfilled if six essential QIs were met, and a lenient definition was fulfilled if at least five QIs were met. Agreement between methods was analysed using kappa statistic.

FINDINGS

Among 106 patients included, rates of appropriateness of antimicrobial therapy ranged from 20% to 75%, depending on the method of evaluation. Very low agreement was found between the strict definition and expert opinion (kappa=0.068), and medium agreement was found between the lenient definition and expert opinion (kappa=0.45).

CONCLUSIONS

Rates of appropriateness of antimicrobial therapy varied between evaluation methods, with low to moderate agreement between the different methods.

Development and Validation of a Clinical Prediction Rule for Bacteremia among Maintenance Hemodialysis Patients in Outpatient Settings

Background

To our knowledge, no reliable clinical prediction rule (CPR) for identifying bacteremia in hemodialysis (HD) patients has been established. The aim of this study was to develop a CPR for bacteremia in maintenance HD patients visiting the outpatient department.

Methods

This multicenter cohort study involved consecutive maintenance HD patients who visited the outpatient clinic or emergency room of seven Japanese institutions between August 2011 and July 2013. The outcome measure was bacteremia diagnosed based on the results of blood cultures. The candidate predictors for bacteremia were extracted through a literature review. A CPR for bacteremia was developed using a coefficient-based multivariable logistic regression scoring method, and calibration was performed. The test performance was then assessed for the CPR.

Results

Of 507 patients eligible for the study, we analyzed the 293 with a complete dataset for candidate predictors. Of these 293 patients, 48 (16.4%) were diagnosed with bacteremia. At the conclusion of the deviation process, body temperature ≥ 38.3°C, heart rate ≥ 125 /min, C-reactive protein ≥ 10 mg/dL, alkaline phosphatase >360 IU/L, and no prior antibiotics use within the past week were retained and scored. The CPR had a good fit for the model on calibration. The AUC of the CPR was 0.76, and for score CPR ≥ 2, the sensitivity and specificity were 89.6% and 51.4%, respectively.

Conclusions

We established a simple CPR for bacteremia in maintenance HD patients using routinely obtained clinical information in an outpatient setting. This model may facilitate more appropriate clinical decision making.