Background/Aim: A cutoff value for lymph node diameter in colorectal cancer lymph node metastases has not been established. This prospective study aimed to investigate the direct association between swollen lymph nodes identified on preoperative computed tomography (CT) and pathological findings and proposed a cutoff value. Patients and Methods: We enrolled patients scheduled to undergo curative surgery with lymph node dissection for colorectal adenocarcinoma who underwent preoperative contrast-enhanced CT and had swollen lymph nodes ≥7 mm in diameter. Two gastrointestinal surgeons intraoperatively identified the target lymph nodes to assess the association between lymph node diameter and pathological findings. The diagnostic performance for lymph node metastasis was determined using multi-level logistic modelling. Results: A total of 109 patients were enrolled, and 225 swollen lymph nodes were pathologically evaluated. Using a cutoff value of ≥9 mm for the short diameter, the positive and negative predictive values, sensitivity, and specificity were 100.0% (99.6%-100.0%), 99.9% (99.1%-100.0%), 62.0% (45.6%-76.0%), and 84.9% (67.0%-94.0%), respectively. Conclusion: The cutoff value for improving the positive predictive value for the preoperative lymph node metastasis diagnosis in colorectal cancer patients should be at least 9 mm in diameter.
Introduction: Culinary interventions (cooking classes) are a potential educational tool for salt reduction in the home diet, but their content has never been reported in detail. This study aimed to develop a cooking class for salt reduction, describe its rationale and structure so that other parties could replicate it, and preliminarily assess its impact on salt intake. Methods: A multidisciplinary research team developed a cooking class package to reduce salt content in the Japanese home diet. The package comprised its developmental policy, teaching methodology, a menu and recipes, and an implementation manual and aimed to allow third parties to replicate and modify the content. The team took the following step-by-step developmental approach. First, traditional home meals were modeled to create strategies contributing to a target of 2 g salt/meal. Then, educational topics were developed through these strategies, and finally, a dietitian produced menus and prepared documents for the class. The impact of the cooking class was assessed in a nonrandomized study of community residents. The outcome was differences in urinary salt excretion before and after the intervention. General linear models were used to account for the possible confounders. Results: The authors assumed 4-7 g salt/meal from analyzing typical Japanese home diets and developed 3 strategies: (1) restricting salt content in the main dish, (2) maintaining good tastes without salty dishes, and (3) balancing nutrition with low-salt dishes. On the basis of these strategies, the authors selected a total of 5 educational topics that participants could learn and apply at home: 1a, a simple and reliable technique to limit salt in a serving; 2a, excluding salty dishes; 2b, staple foods with notable flavor and aroma; 3a, flavoring without salt in side dishes; and 3b, ingredients that should be used intentionally. The team dietitian translated these educational topics into a menu and recipes for hands-on training and prepared a manual for conducting the class. The class developed using this approach was successfully overseen by a dietitian outside the research team. In the validation study, the intervention group (n=52) showed a greater decrease in urinary salt excretion than the control group (n=46), with an adjusted difference of -1.38 g (p=0.001). Conclusions: The authors developed a cooking class package for salt reduction so that third parties could replicate and modify the class. The significant salt reduction noted in this study warrants further studies to apply this cooking class to other populations.
BACKGROUND: Meningitis, especially of bacterial origin, is a medical emergency that must be diagnosed promptly. However, due to the associated risks of complications of lumbar puncture, it is crucial to identify individuals who truly need it. The aim of this study was to assess the diagnostic role of inflammatory markers in distinguishing among patients without meningitis, those with aseptic meningitis, and those with bacterial meningitis. METHODS: This was a retrospective, diagnostic study at an acute care hospital, involving adult patients who presented to either ambulatory care or the emergency department with fever and headache, but without altered mental status or neurological deficits. Inflammatory markers (C-reactive protein [CRP], mean platelet volume, neutrophil-lymphocyte ratio, and red cell distribution width) were assessed as index tests. An expert panel classified patients into three groups: no meningitis, aseptic meningitis, and bacterial meningitis using predefined criteria. RESULTS: Of the 80 patients, 52 had no meningitis, 27 had aseptic meningitis, and 1 had bacterial meningitis. Of the inflammatory markers investigated, only CRP showed potential usefulness in differentiating these three diagnostic groups, with median values of 5.6 (interquartile range [IQR] 2.1, 11.3) mg/dL in those without meningitis, 0.2 (IQR 0.1, 1.2) mg/dL in those with aseptic meningitis, and notably elevated at 21.7 mg/dL in the patient with bacterial meningitis. CONCLUSION: In adult patients presenting with fever and headache in an emergency setting, CRP was the only marker that demonstrated potential diagnostic utility in distinguishing among those with no meningitis, aseptic meningitis, and bacterial meningitis.
Background: Mentorship is a dynamic, reciprocal relationship in which an advanced careerist (mentor) encourages the growth of a novice (mentee). Mentorship may protect the mental health of residents at risk for depression and burnout, yet despite its frequent use and known benefits, limited reports exist regarding the prevalence and mental effects of mentorship on residents in Japan. Methods: We conducted a cross-sectional study involving postgraduate year 1 and 2 (PGY-1 and PGY-2) residents in Japan who took the General Medicine In-Training Examination (GM-ITE) at the end of the 2021 academic year. Data on mentorship were collected using surveys administered immediately following GM-ITE completion. The primary outcome was the Patient Health Questionaire-2 (PHQ-2), which consisted depressed mood and loss of interest. A positive response for either item indicated PHQ-2 positive. We examined associations between self-reported mentorship and PHQ-2 by multi-level analysis. Results: Of 4929 residents, 3266 (66.3%) residents reported having at least one mentor. Compared to residents without any mentor, those with a mentor were associated with a lower likelihood of a positive PHQ-2 response (adjusted odds ratio [aOR] 0.75; 95% confidence interval [95% CI] 0.65-0.86). Mentor characteristic significantly associated with negative PHQ-2 response was a formal mentor (aOR; 0.68; 95% CI 0.55-0.84). Conclusions: A mentor-based support system was positively associated with residents' mental health. Further research is needed to determine the quality of mentorship during clinical residency in Japan.
OBJECTIVES: In older patients, the diagnosis of acute pyelonephritis (APN) is challenging. The aim was to evaluate the added value of CT to history, physical examination and urinalysis for the diagnosis of APN in older patients with suspected infection with an unknown focus. DESIGN: Retrospective diagnostic study. SETTING: Department of General Medicine in an acute care hospital in Japan. PARTICIPANTS: Patients aged ≥65 years who underwent blood cultures, a urine culture, and chest and abdominal CT to detect the focus of infection were included. PRIMARY OUTCOME MEASURES: Two radiologists independently reviewed four non-contrast CT signs: perirenal fat stranding, pelvicalyceal wall thickening, enlargement of the kidney and thickening of Gerota's fascia. Findings on contrast-enhanced CT could not be evaluated due to an insufficient number of patients in whom contrast-enhanced CT was performed. An expert panel was used as the reference standard for APN. The added value of CT findings was quantified by comparing the diagnostic performance between a model based on 10 predictors available before CT and an extended model including the CT findings. RESULTS: Of 473 patients, 61 (14.8%) were diagnosed with APN. When the laterality of the CT findings was taken into account, the model fit was not improved by adding them. In the laterality-insensitive analysis, the model performance was significantly improved by adding the CT signs (likelihood-ratio test p=0.03; c-index 0.89 vs 0.91, p=0.03). However, their clinical utility was only to improve the classification of 11.5% of patients with APN. CONCLUSIONS: The added value of non-contrast CT findings to history, physical examination and urinalysis was limited for the diagnosis of APN in older patients with a suspected infection with an unknown focus.
Pyelonephritis , Tomography, X-Ray Computed , Humans , Aged , Retrospective Studies , Acute Disease , Pyelonephritis/diagnostic imaging , Kidney
INTRODUCTION: Intravenous antibiotics are the primary treatment of choice for pyogenic vertebral osteomyelitis (PVO). Surgical intervention is required when the initial antibiotic treatment fails but is often difficult to perform, especially in older adults with multiple comorbidities, because of the reduced physical activity. The size of the infection signal in the spinal bone on magnetic resonance imaging (MRI) at the time of diagnosis was reported to have a high predictive accuracy for antibiotic treatment failure. However, the sample size was too small for this result to be adopted in clinical practice. Thus, we conducted a validation study of the previous research using a larger sample size. METHODS: We conducted a retrospective review of electronic medical records of patients admitted to the orthopedic department of a university hospital with a diagnosis of PVO between 2006 and 2021, and consecutively included patients without planned PVO surgery on admission and with a sagittal view of T1-weighted spinal MRI at the time of diagnosis. The index test was the percentage involvement of the affected areas in one motion segment on sagittal MRI. We also evaluated other MRI findings, such as bone destruction, segmental instability, epidural abscesses, and multiple sites for their predictive accuracy for antibiotic treatment failure. RESULTS: A total of 82 participants were eligible for the analysis. The presence of ≥90% affected area of one motion segment had a sensitivity of 16.7% and a specificity of 70.3% for future antibiotic treatment failure, resulting in poor predictive performance, with positive (LR+) and negative likelihood ratios of 0.56 and 1.19, respectively. The area under the receiver operating characteristic curve for a 10% increase in the affected area was 0.48. Among the other MRI findings, the presence of bone destruction had a significantly higher predictive accuracy (LR+ 3.11, 95% confidence interval 1.30-7.42). CONCLUSION: An infection signal ≥90% on a T1-weighted MRI of one spinal motion segment did not show sufficient predictive performance for antibiotic treatment failure. Spinal bone destruction had a mild-to-moderate predictive accuracy.
IMPORTANCE: The viability of probiotics in the human gastrointestinal tract is important, as some reports indicate that the health benefits of live bacteria are greater than those of dead ones. Therefore, the higher the viability of the probiotic strain, the better it may be. However, probiotic strains lose their viability due to gastrointestinal stress such as gastric acid and bile. This study provides an example of the use of co-culture or pH-controlled monoculture, which uses more stringent conditions (lower pH) than normal monoculture to produce probiotic strains that are more resistant to gastrointestinal stress. In addition, co-cultured beverages showed higher viability of the probiotic strain in the human gastrointestinal tract than monocultured beverages in our human study.
Gastrointestinal Tract , Probiotics , Humans , Coculture Techniques , Gastrointestinal Tract/microbiology , Bacteria , Bile Acids and Salts/pharmacology , Microbial Viability
BACKGROUND: A previous individual participant data meta-analysis (IPD-MA) of antibiotics for adults with clinically diagnosed acute rhinosinusitis (ARS) showed a marginal overall effect of antibiotics, but was unable to identify patients that are most likely to benefit from antibiotics when applying conventional (i.e. univariable or one-variable-at-a-time) subgroup analysis. We updated the systematic review and investigated whether multivariable prediction of patient-level prognosis and antibiotic treatment effect may lead to more tailored treatment assignment in adults presenting to primary care with ARS. METHODS: An IPD-MA of nine double-blind placebo-controlled trials of antibiotic treatment (n=2539) was conducted, with the probability of being cured at 8-15 days as the primary outcome. A logistic mixed effects model was developed to predict the probability of being cured based on demographic characteristics, signs and symptoms, and antibiotic treatment assignment. Predictive performance was quantified based on internal-external cross-validation in terms of calibration and discrimination performance, overall model fit, and the accuracy of individual predictions. RESULTS: Results indicate that the prognosis with respect to risk of cure could not be reliably predicted (c-statistic 0.58 and Brier score 0.24). Similarly, patient-level treatment effect predictions did not reliably distinguish between those that did and did not benefit from antibiotics (c-for-benefit 0.50). CONCLUSIONS: In conclusion, multivariable prediction based on patient demographics and common signs and symptoms did not reliably predict the patient-level probability of cure and antibiotic effect in this IPD-MA. Therefore, these characteristics cannot be expected to reliably distinguish those that do and do not benefit from antibiotics in adults presenting to primary care with ARS.
AIMS: Risk stratification is used for decisions regarding need for imaging in patients with clinically suspected acute pulmonary embolism (PE). The aim was to develop a clinical prediction model that provides an individualized, accurate probability estimate for the presence of acute PE in patients with suspected disease based on readily available clinical items and D-dimer concentrations. METHODS AND RESULTS: An individual patient data meta-analysis was performed based on sixteen cross-sectional or prospective studies with data from 28 305 adult patients with clinically suspected PE from various clinical settings, including primary care, emergency care, hospitalized and nursing home patients. A multilevel logistic regression model was built and validated including ten a priori defined objective candidate predictors to predict objectively confirmed PE at baseline or venous thromboembolism (VTE) during follow-up of 30 to 90 days. Multiple imputation was used for missing data. Backward elimination was performed with a P-value <0.10. Discrimination (c-statistic with 95% confidence intervals [CI] and prediction intervals [PI]) and calibration (outcome:expected [O:E] ratio and calibration plot) were evaluated based on internal-external cross-validation. The accuracy of the model was subsequently compared with algorithms based on the Wells score and D-dimer testing. The final model included age (in years), sex, previous VTE, recent surgery or immobilization, haemoptysis, cancer, clinical signs of deep vein thrombosis, inpatient status, D-dimer (in µg/L), and an interaction term between age and D-dimer. The pooled c-statistic was 0.87 (95% CI, 0.85-0.89; 95% PI, 0.77-0.93) and overall calibration was very good (pooled O:E ratio, 0.99; 95% CI, 0.87-1.14; 95% PI, 0.55-1.79). The model slightly overestimated VTE probability in the lower range of estimated probabilities. Discrimination of the current model in the validation data sets was better than that of the Wells score combined with a D-dimer threshold based on age (c-statistic 0.73; 95% CI, 0.70-0.75) or structured clinical pretest probability (c-statistic 0.79; 95% CI, 0.76-0.81). CONCLUSION: The present model provides an absolute, individualized probability of PE presence in a broad population of patients with suspected PE, with very good discrimination and calibration. Its clinical utility needs to be evaluated in a prospective management or impact study. REGISTRATION: PROSPERO ID 89366.
Pulmonary Embolism , Venous Thromboembolism , Adult , Humans , Venous Thromboembolism/diagnosis , Venous Thromboembolism/epidemiology , Prospective Studies , Cross-Sectional Studies , Models, Statistical , Prognosis , Pulmonary Embolism/diagnosis , Pulmonary Embolism/epidemiology , Fibrin Fibrinogen Degradation Products/analysis
BACKGROUND: Low-value care is healthcare leading to no or little clinical benefit for the patient. The best (combinations of) interventions to reduce low-value care are unclear. PURPOSE: To provide an overview of randomized controlled trials (RCTs) evaluating deimplementation strategies, to quantify the effectiveness and describe different combinations of strategies. METHODS: Analysis of 121 RCTs (1990-2019) evaluating a strategy to reduce low-value care, identified by a systematic review. Deimplementation strategies were described and associations between strategy characteristics and effectiveness explored. RESULTS: Of 109 trials comparing deimplementation to usual care, 75 (69%) reported a significant reduction of low-value healthcare practices. Seventy-three trials included in a quantitative analysis showed a median relative reduction of 17% (IQR 7%-42%). The effectiveness of deimplementation strategies was not associated with the number and types of interventions applied. CONCLUSIONS AND IMPLICATIONS: Most deimplementation strategies achieved a considerable reduction of low-value care. We found no signs that a particular type or number of interventions works best for deimplementation. Future deimplementation studies should map relevant contextual factors, such as the workplace culture or economic factors. Interventions should be tailored to these factors and provide details regarding sustainability of the effect.
Low-Value Care , Workplace , Humans , Working Conditions , Systematic Reviews as Topic , Randomized Controlled Trials as Topic
OBJECTIVES: We present an illustrative application of methods that account for covariates in receiver operating characteristic (ROC) curve analysis, using individual patient data on D-dimer testing for excluding pulmonary embolism. STUDY DESIGN AND SETTING: Bayesian nonparametric covariate-specific ROC curves were constructed to examine the performance/positivity thresholds in covariate subgroups. Standard ROC curves were constructed. Three scenarios were outlined based on comparison between subgroups and standard ROC curve conclusion: (1) identical distribution/identical performance, (2) different distribution/identical performance, and (3) different distribution/different performance. Scenarios were illustrated using clinical covariates. Covariate-adjusted ROC curves were also constructed. RESULTS: Age groups had prominent differences in D-dimer concentration, paired with differences in performance (Scenario 3). Different positivity thresholds were required to achieve the same level of sensitivity. D-dimer had identical performance, but different distributions for YEARS algorithm items (Scenario 2), and similar distributions for sex (Scenario 1). For the later covariates, comparable positivity thresholds achieved the same sensitivity. All covariate-adjusted models had AUCs comparable to the standard approach. CONCLUSION: Subgroup differences in performance and distribution of results can indicate that the conventional ROC curve is not a fair representation of test performance. Estimating conditional ROC curves can improve the ability to select thresholds with greater applicability.
Algorithms , Pulmonary Embolism , Humans , ROC Curve , Bayes Theorem , Area Under Curve , Pulmonary Embolism/diagnosis
BACKGROUND: In patients clinically suspected of having pulmonary embolism (PE), physicians often rely on intuitive estimation ("gestalt") of PE presence. Although shown to be predictive, gestalt is criticized for its assumed variation across physicians and lack of standardization. OBJECTIVES: To assess the diagnostic accuracy of gestalt in the diagnosis of PE and gain insight into its possible variation. METHODS: We performed an individual patient data meta-analysis including patients suspected of having PE. The primary outcome was diagnostic accuracy of gestalt for the diagnosis of PE, quantified as risk ratio (RR) between gestalt and PE based on 2-stage random-effect log-binomial meta-analysis regression as well as gestalts' sensitivity and specificity. The variability of these measures was explored across different health care settings, publication period, PE prevalence, patient subgroups (sex, heart failure, chronic lung disease, and items of the Wells score other than gestalt), and age. RESULTS: We analyzed 20 770 patients suspected of having PE from 16 original studies. The prevalence of PE in patients with and without a positive gestalt was 28.8% vs 9.1%, respectively. The overall RR was 3.02 (95% CI, 2.35-3.87), and the overall sensitivity and specificity were 74% (95% CI, 68%-79%) and 61% (95% CI, 53%-68%), respectively. Although variation was observed across individual studies (I2, 90.63%), the diagnostic accuracy was consistent across all subgroups and health care settings. CONCLUSION: A positive gestalt was associated with a 3-fold increased risk of PE in suspected patients. Although variation was observed across studies, the RR of gestalt was similar across prespecified subgroups and health care settings, exemplifying its diagnostic value for all patients suspected of having PE.
Physicians , Pulmonary Embolism , Humans , Pulmonary Embolism/diagnosis , Pulmonary Embolism/epidemiology , Sensitivity and Specificity , Male , Female
Bile acid resistance is crucial to allow probiotic strains to survive in the gastrointestinal tract and exert health-promoting effects on their hosts. Our aim here was to determine the mechanism of this resistance via a genetic approach by identifying the genes essential for bile acid resistance in Lacticaseibacillus paracasei strain Shirota (LcS). We generated 4649 transposon-inserted lines of L. paracasei YIT 0291, which has the same genome sequence as LcS but lacks the pLY101 plasmid, and we screened them for bile-acid-sensitive mutants. The growth of 14 mutated strains was strongly inhibited by bile acid, and we identified 10 genes that could be involved in bile acid resistance. Expression of these genes was not markedly induced by bile acid, suggesting that their homeostatic expression is important for exerting bile acid resistance. Two mutants in which the transposon was independently inserted into cardiolipin synthase (cls) genes, showed strong growth inhibition. Disruption of the cls genes in LcS caused decreased cardiolipin (CL) production and the accumulation of the precursor phosphatidylglycerol in bacterial cells. These data suggest that LcS possesses several mechanisms for exerting bile acid resistance, and that homeostatic CL production is among the factors most essential for this resistance.
Lacticaseibacillus casei , Lacticaseibacillus paracasei , Probiotics , Lacticaseibacillus , Bile Acids and Salts/pharmacology
OBJECTIVES: We evaluated the presence and frequency of spin practices and poor reporting standards in studies that developed and/or validated clinical prediction models using supervised machine learning techniques. STUDY DESIGN AND SETTING: We systematically searched PubMed from 01/2018 to 12/2019 to identify diagnostic and prognostic prediction model studies using supervised machine learning. No restrictions were placed on data source, outcome, or clinical specialty. RESULTS: We included 152 studies: 38% reported diagnostic models and 62% prognostic models. When reported, discrimination was described without precision estimates in 53/71 abstracts (74.6% [95% CI 63.4-83.3]) and 53/81 main texts (65.4% [95% CI 54.6-74.9]). Of the 21 abstracts that recommended the model to be used in daily practice, 20 (95.2% [95% CI 77.3-99.8]) lacked any external validation of the developed models. Likewise, 74/133 (55.6% [95% CI 47.2-63.8]) studies made recommendations for clinical use in their main text without any external validation. Reporting guidelines were cited in 13/152 (8.6% [95% CI 5.1-14.1]) studies. CONCLUSION: Spin practices and poor reporting standards are also present in studies on prediction models using machine learning techniques. A tailored framework for the identification of spin will enhance the sound reporting of prediction model studies.
Machine Learning , Humans , Prognosis
CONTEXT: Approximately 10% to 20% of patients with Kawasaki disease (KD) are refractory to initial intravenous immunoglobulin (IVIG) therapy. KD is mainly associated with coronary artery abnormalities. OBJECTIVES: To identify and evaluate all developed prediction models for IVIG resistance in patients with KD and synthesize evidence from external validation studies that evaluated their predictive performances. DATA SOURCES: PubMed Medline, Dialog Embase, the Cochrane Central Register of Controlled Trials, the World Health Organization International Clinical Trials Registry Platform, and ClinicalTrials.gov were searched from inception until October 5, 2021. STUDY SELECTION: All cohort studies that reported patients diagnosed with KD who underwent an initial IVIG of 2 g/kg were selected. DATA EXTRACTION: Study and patient characteristics and model performance measures. Two authors independently extracted data from the studies. RESULTS: The Kobayashi, Egami, Sano, Formosa, and Harada scores were the only prediction models with 3 or more external validation of the161 model analyses in 48 studies. The summary C-statistics were 0.65 (95% confidence interval [CI]: 0.57-0.73), 0.63 (95% CI: 0.55-0.71), 0.58 (95% CI: 0.55-0.60), 0.50 (95% CI: 0.36-0.63), and 0.63 (95% CI: 0.44-0.78) for the Kobayashi, Egami, Sano, Formosa, and Harada models, respectively. All 5 models showed low positive predictive values (0.14-0.39) and high negative predictive values (0.85-0.92). LIMITATIONS: Potential differences in the characteristics of the target population among studies and lack of assessment of calibrations. CONCLUSIONS: None of the 5 prediction models with external validation accurately distinguished between patients with and without IVIG resistance.
Immunoglobulins, Intravenous , Mucocutaneous Lymph Node Syndrome , Humans , Infant , Immunoglobulins, Intravenous/therapeutic use , Mucocutaneous Lymph Node Syndrome/diagnosis , Drug Resistance , Predictive Value of Tests , Retrospective Studies
BACKGROUND AND OBJECTIVES: We sought to summarize the study design, modelling strategies, and performance measures reported in studies on clinical prediction models developed using machine learning techniques. METHODS: We search PubMed for articles published between 01/01/2018 and 31/12/2019, describing the development or the development with external validation of a multivariable prediction model using any supervised machine learning technique. No restrictions were made based on study design, data source, or predicted patient-related health outcomes. RESULTS: We included 152 studies, 58 (38.2% [95% CI 30.8-46.1]) were diagnostic and 94 (61.8% [95% CI 53.9-69.2]) prognostic studies. Most studies reported only the development of prediction models (n = 133, 87.5% [95% CI 81.3-91.8]), focused on binary outcomes (n = 131, 86.2% [95% CI 79.8-90.8), and did not report a sample size calculation (n = 125, 82.2% [95% CI 75.4-87.5]). The most common algorithms used were support vector machine (n = 86/522, 16.5% [95% CI 13.5-19.9]) and random forest (n = 73/522, 14% [95% CI 11.3-17.2]). Values for area under the Receiver Operating Characteristic curve ranged from 0.45 to 1.00. Calibration metrics were often missed (n = 494/522, 94.6% [95% CI 92.4-96.3]). CONCLUSION: Our review revealed that focus is required on handling of missing values, methods for internal validation, and reporting of calibration to improve the methodological conduct of studies on machine learning-based prediction models. SYSTEMATIC REVIEW REGISTRATION: PROSPERO, CRD42019161764.
Machine Learning , Supervised Machine Learning , Humans , Algorithms , Prognosis , ROC Curve
BACKGROUND: Due to potentially fatal consequences of missed bacteremia, blood cultures are often overused. While there are several prediction models that can be used to identify patients who truly need blood cultures, physicians often rely on their gestalt. We evaluated the diagnostic performance of physician gestalt for bacteremia in comparison with 2 existing prediction models: Takeshima and Shapiro. METHODS: The study enrolled consecutive adult patients with suspected infection who were in the process of being admitted to the general medicine department at 2 hospitals between April 2017 and January 2019. Attending physicians provided gestalt regarding risk of bacteremia (0%-100%). Patients with a <10% risk estimated via each strategy (ie, physician gestalt or 2 existing models) were categorized as bacteremia excluded (ie, blood cultures were considered unnecessary). Strategies were compared in terms of safety (proportion of patients with bacteremia among those classified as bacteremia excluded) and efficiency (proportion of patients classified as bacteremia excluded among the total cohort). RESULTS: Among 2014 patients, 292 (14.5%) were diagnosed with bacteremia. The safety of physician gestalt and the Takeshima and Shapiro models was 3.7% (95% confidence interval [CI], 2.2% to 5.7%), 6.5% (95% CI, 5.0% to 7.9%), and 10.8% (95% CI, 9.4% to 12.3%), whereas the efficiency of each strategy was 22.4% (95% CI, 22.5% to 26.3%), 52.7% (95% CI, 50.5% to 54.9%), and 87.8% (95% CI, 86.3% to 89.2%), respectively. CONCLUSIONS: Physician gestalt was safer but less efficient than existing models. Clinical prediction models could help reduce the overuse of blood cultures.
Bacteremia , Physicians , Adult , Humans , Bacteremia/diagnosis , Hospitalization , Blood Culture , Hospitals
CASE PRESENTATION: A 75-year-old man with a history of asbestosis presented to the emergency department with sudden-onset dyspnea and hemoptysis, triggered by coughing. The patient was hemodynamically unstable and in respiratory distress. Computed tomography revealed a massive hemothorax on the left side and compression of the descending thoracic aorta. He underwent emergency surgical exploration after decompression by chest tube insertion. The hemothorax was caused by tears in the pleural adhesions due to asbestosis and induced by coughing. DISCUSSION: Spontaneous hemothorax is a rare subtype of hemothorax. There have been only a few case reports of spontaneous tension hemothorax. In addition to its typical findings, compression of the thoracic descending aorta was observed in our patient. We hypothesize that severely diminished pulmonary compliance contributed to the extremely high intrathoracic pressure, which led to this unusual finding.
BACKGROUND & AIMS: Aspiration pneumonia (AP) is a public health concern among older adults. Previous studies have reported the association between oral intake initiation within 48 h after hospital admission and better in-hospital outcomes among patients with AP. We investigated the association between initiation of oral intake within 24 h and in-hospital outcomes of older patients with AP undergoing dysphagia rehabilitation. METHODS: This retrospective cohort study was conducted from April 2015 to September 2020. Door-to-oral time (D2O) was defined as the time from hospital arrival to the first oral intake and was divided into early (within 24 h), middle (between 24 and 48 h), and late (over 48 h). We examined the associations between D2O and in-hospital outcomes: discharge with oral intake (by logistic regression analysis), length of stay, and days from the first oral intake to discharge (by fitting the general linear models with robust variance estimation). RESULTS: Among the 398 patients with AP, 142 (35.7%) were classified into early, 111 (27.9%) into middle, and 145 (36.4%) into late groups. Compared with the late group, we found insufficient evidence that early D2O was associated with a greater likelihood of discharge with oral intake (adjusted odds ratio = 1.09; 95% confidence interval [95% CI]: 0.50 to 2.38). The early group was associated with a shorter length of stay (adjusted length difference [aLD] = -7.14 days; 95% CI: -10.80 to -3.42) but not with shorter days from first oral intake to discharge (aLD = -3.34 days; 95% CI: -6.91 to 0.24). CONCLUSIONS: While D2O within 24 h among patients with AP was not associated with a decreased likelihood of discharge with oral intake, it was associated with a shorter length of stay. To improve outcomes without compromising the quality of AP care, early oral intake should be decided based on careful swallowing function assessment.
Deglutition Disorders , Pneumonia, Aspiration , Aged , Deglutition , Hospitals , Humans , Pneumonia, Aspiration/complications , Retrospective Studies
BACKGROUND: Antibiotics are overused in patients with acute rhinosinusitis (ARS) as it is difficult to identify those who benefit from antibiotic treatment. AIM: To develop prediction models for computed tomography (CT)-confirmed ARS and culture-confirmed acute bacterial rhinosinusitis (ABRS) in adults presenting to primary care with symptoms suggestive of ARS. DESIGN AND SETTING: This was a systematic review and individual participant data meta-analysis. METHOD: CT-confirmed ARS was defined as the presence of fluid level or total opacification in any maxillary sinuses, whereas culture-confirmed ABRS was defined by culture of fluid from antral puncture. Prediction models were derived using logistic regression modelling. RESULTS: Among 426 patients from three studies, 140 patients (32.9%) had CT-confirmed ARS. A model consisting of seven variables: previous diagnosis of ARS, preceding upper respiratory tract infection, anosmia, double sickening, purulent nasal discharge on examination, need for antibiotics as judged by a physician, and C-reactive protein (CRP) showed an optimism-corrected c-statistic of 0.73 (95% confidence interval [CI] = 0.69 to 0.78) and a calibration slope of 0.99 (95% CI = 0.72 to 1.19). Among 225 patients from two studies, 68 patients (30.2%) had culture-confirmed ABRS. A model consisting of three variables: pain in teeth, purulent nasal discharge, and CRP showed an optimism-corrected c-statistic of 0.70 (95% CI = 0.63 to 0.77) and a calibration slope of 1.00 (95% CI = 0.66 to 1.52). Clinical utility analysis showed that both models could be useful to rule out the target condition. CONCLUSION: Simple prediction models for CT-confirmed ARS and culture-confirmed ABRS can be useful to safely reduce antibiotic use in adults with ARS in high-prescribing countries.
Rhinitis , Sinusitis , Acute Disease , Adult , Anti-Bacterial Agents/therapeutic use , C-Reactive Protein , Humans , Primary Health Care , Rhinitis/diagnostic imaging , Rhinitis/drug therapy , Sinusitis/diagnostic imaging , Sinusitis/drug therapy , Tomography, X-Ray Computed
