New categorization of chest pain: noncardiac is in, atypical is out!

Chest pain poses a diagnostic challenge in the emergency department and requires a thorough clinical assessment. The traditional distinction between "atypical" and "typical" chest pain carries the risk of not addressing nonischemic clinical pictures. The newly conceived subdivision into cardiac, possibly cardiac, and (probably) noncardiac causes of the presenting symptom complex addresses a much more interdisciplinary approach to a symptom-oriented diagnostic algorithm. The diagnostic structures of the chest pain units in Germany do not currently reflect this. An adaptation should therefore be considered.

Características clínicas de las pericarditis y miopericarditis diagnosticadas en urgencias y factores asociados con la necesidad de hospitalización / Clinical features of pericarditis with and without myocardial involvement diagnosed in the emergency department and factors associated with need for hospitalization

Objetivo: Analizar los episodios de pericarditis aguda (PA) diagnosticados en urgencias en función de la edad y de la afectación miocárdica (miopericarditis, MioP), y determinar los factores asociados a hospitalización. Método: Estudio observacional, descriptivo, unicéntrico de casos consecutivos, con análisis retrospectivo de todos los casos diagnosticados de PA en urgencias durante 10 años (2008-2017), y revisión de las características clínicas, ECG, analíticas y ecográficas (en MioP). Se compararon características clínicas según la edad (< 50 y $ 50 años) y existencia de MioP. Los factores asociados a hospitalización (PA y MioP) se identificaron de forma cruda y ajustada por las diferencias clínicas entre grupos. Resultados: Se diagnosticaron 983 PA (34% mujeres, mediana de edad: 42 años). Los pacientes más jóvenes referían con mayor frecuencia dolor torácico (DT) punzante y modificable con la respiración o cambios posturales, y los más mayores tenían más comorbilidades cardiovasculares, refirieron más frecuentemente DT opresivo y generaron mayor sospecha de síndrome coronario agudo. Las alteraciones en el ECG (OR = 4,26; IC95% = 1,89-9,59) se asociaron a MioP (72 casos, 7%). Ingresaron 62 PA (6%), hecho asociado a antecedente de insuficiencia renal (OR = 4,83; IC95% = 1,66-14,05), DT que se modifica con movimientos respiratorios/posturales (OR = 0,54, IC95% = 0,29-0,99), taquicardia (OR = 2,29, IC95% = 1,15-4,55) y MioP (OR = 8,73, IC95% = 4,65-16,38). Ingresaron 24 MioP (33%), hecho asociado a alteraciones en la ecoscopia dirigida (protocolo FOCUS; OR = 13,72, IC95% = 1,80-104). Conclusiones: La edad puede condicionar la presentación clínica en los pacientes con PA. Las alteraciones en el segmento ST en el ECG son sugestivos de implicación miocárdica. La insuficiencia renal, la taquicardia y la MioP son factores que incrementan la decisión de hospitalización en las PA; mientras que en las MioP, las alteraciones ecográficas

Objectives: To analyze the clinical features of acute pericarditis diagnosed in the emergency department according to patient age and myocardial involvement (myopericarditis) and to determine factors associated with hospitalization. Methods: Retrospective, descriptive, observational, single-center study of consecutive patients. We analyzed all cases of pericarditis diagnosed in the emergency department over a period of 10 years (2008-2017), reviewing clinical, electrocardiographic, and laboratory findings as well as ultrasound imaging for myocardial involvement. Characteristics were analyzed by age (under 50 years or 50 or older) and presence or not of myocardial involvement. Factors associated with hospitalization for both pericarditis and myopericarditis were identified by crude and adjusted odds ratios (ORs). Results: A total of 983 patients were diagnosed with pericarditis (34% women, mean age, 42 years). The younger patients more often reported sharp chest pain modified by breathing or posture changes. Older patients had more concurrent cardiovascular disease and described chest pain as pressure (oppressive); acute coronary syndrome was suspected more often in the older patients. The only independent predictor of myopericarditis was a finding of electrocardiographic abnormalities, recorded in 72 cases (7%) (OR, 4.26; 95% CI, 1.89-9.59). Sixty-two patients (6%) were admitted for pericarditis. Associated factors were renal insufficiency (OR, 4.83; 95% CI, 1.66-14.05), pain modified by breathing or posture changes (OR, 0.54; 95% CI, 0.29-0.99), tachycardia (OR, 2.29; 95% CI, 1.15-4.55), and myopericarditis (OR, 8.73; 95% CI, 4.65-16.38). Admission of 24 patients (33%) for myocarditis was related to focused cardiac ultrasound findings (OR, 13.72; 95% CI, 1.80-104). Conclusions: Age may affect the presentation of pericarditis. ST segment abnormalities on an electrocardiogram suggest myocardial involvement. Renal insufficiency, tachycardia, and myocardial involvement are the factors associated with a decision to admit patients with pericarditis. Ultrasound findings are associated with admission for myopericarditis

External validation of the emergency department assessment of chest pain score accelerated diagnostic pathway (EDACS-ADP).

OBJECTIVE: We validated prior emergency department (ED) assessments of the chest pain score accelerated diagnostic pathway (EDACS-ADP) in Korean patients. This score is designed to discriminate patients at a low risk of a major adverse cardiac event (MACE) from those with a potentially more serious condition. METHODS: We retrospectively evaluated 1273 patients who had presented at our ED with chest pain or symptoms of a suspected coronary artery disease and who underwent coronary computed tomographic angiography from January 2017 to December 2018. These cases had been classified as low or high risk using the EDACS-ADP. The primary outcome was a MACE onset within 30 days of presentation. RESULTS: Of the total study patients, 448 (35.2%) were classified as low risk by the EDACS-ADP and 5 cases (1.1%) of MACE arose. Overall, 221 patients in the study population (17.3%) developed a MACE. The sensitivity, and negative predictive values of the EDACS-ADP were 97.7% (95% CI 94.8-99.3), and 98.9% (97.4-99.5), respectively. CONCLUSION: The sensitivity and negative predictive values for the EDACS-ADP were high in Korean patients presenting at the ED. However, the MACE rate among low-risk patients is higher than that considered acceptable by the majority of ED physicians for patients that are to be discharged without further evaluation. Further studies may be warranted for the successful application of the EDACS-ADP.

Retrospective analysis of HEART Score results in cost saving.

BACKGROUND AND PURPOSE: Chest pain (CP) is one of the most frequent chief complaints of patients presenting to the emergency department (ED). Diagnoses range from life-threatening acute coronary syndrome (ACS) to less concerning musculoskeletal injury. Patients are frequently admitted for comprehensive cardiac evaluation. However, it is estimated that <10% are diagnosed with ACS. Identifying low-risk patients who can be safely discharged from the ED results in lower cost burden and less patient days. The HEART Score is a recently validated tool for undifferentiated CP in the ED used to identify low-risk patients. The purpose of this project was to ascertain if the HEART Score could be utilized in the Veteran population for the evaluation of undifferentiated chest pain. LOCAL PROBLEM: There is no standard assessment tool used in the ED at the Veterans Administration Pittsburgh Healthcare System (VAPHS) to evaluate CP in low-risk patents. METHODS: As part of a quality improvement initiative, a retrospective analysis was performed on patients presenting to the ED with CP over a 6-month period. A total of 197 VAPHS patients were identified through the computerized medical record system. HEART Scores were calculated for each patient. Patients scored as low risk (score of 0-3) were further evaluated for major adverse cardiac events (MACE) and cost saving. CONCLUSIONS: Approximately 28% (56) of the patients presenting to the ED with CP were at low risk based on the HEART Score. There were no MACE. There were cost savings compared with usual care ($1,145 vs. $4,700). IMPLICATIONS FOR PRACTICE: The HEART Score can be safely used to identify low-risk patients and result in cost savings for Veteran population.

The importance of characteristics of angina symptoms for the prediction of coronary artery disease in a cohort of stable patients in the modern era.

OBJECTIVE: Angina is an important clinical symptom indicating underlying coronary artery disease (CAD). Its characteristics are important for the diagnosis and risk stratification of patients with CAD. Currently, we aimed to investigate the association of chest pain characteristics with the presence of obstructive CAD in a contemporary cohort of patients undergoing coronary angiography for suspected stable CAD. METHODS: Consecutive patients undergoing coronary angiography for suspected stable CAD (n = 686) in a single university hospital cardiology department were enrolled. Chest pain was classified as typical angina, atypical angina, nonangina chest pain, and lack of symptoms. The presence of significant angiographic CAD was diagnosed by standard coronary angiography. RESULTS: Typical angina symptoms were associated with a higher prevalence of CAD (odds ratio [OR], 3.47, p < 0.001), whereas atypical angina symptoms were associated with a lower prevalence of CAD (OR, 0.49, p = 0.003) than the nonangina symptoms/or asymptomatic status. In multivariate analysis, typical angina symptoms remained an independent predictor of CAD (OR, 2.54, p < 0.001), with a greater predictive accuracy than other clinical risk factors (area under the curve [AUC], 0.715, p < 0.001) and similar to the accuracy of the high-sensitivity C-reactive protein (AUC, 0.712, p < 0.001). In a multivariate model, the combination of all studied factors further improved the predictive accuracy (AUC, 0.81, p < 0.001). CONCLUSION: In a contemporary cohort of patients referred for coronary angiography for stable CAD, the presence of typical angina symptoms was the most important independent predictor of obstructive CAD. The association of atypical angina symptoms with low CAD prevalence compared to nonangina chest pain or absence of significant symptoms probably reflects different management and referral strategies in these groups of patients.

An external validation of the HEART pathway among Emergency Department patients with chest pain.

The impact of an outpatient disposition strategy for patients with HEART score 0-3 (HEART pathway) on HEART score prognostic accuracy is unclear. Our objective is to perform an external validation the HEART score in the setting of recent implementation of the HEART pathway. We conducted an external validation study of the HEART pathway among patients presenting to our ED with chest pain 6 weeks after institutional implementation of a HEART pathway outpatient disposition pathway. We reviewed the charts of 625 consecutive patients with chest pain. Data abstracted included all elements of the HEART score to include history, electrocardiogram (ECG) read, patient age, patient risk factors, and troponin levels. We also reviewed each patient's record for evidence of major adverse cardiac events (MACE) to include mortality, myocardial infarction, or coronary revascularization over 6 weeks following their initial ED visit. We double-abstracted 10% of the charts for quality assurance purposes. Of 625 charts, 449 patients met all criteria for study inclusion. Of these, 25 subjects (5.56%) experience 6-week MACE. No subject with a score of 3 or less has a MACE at 6 weeks (100% sensitivity, 38.7% specificity). The area under the receiver operator curve (AUROC) is 0.898 (95% confidence interval 0.847-0.950). Kappa coefficients for inter-rater reliability range from 0.62 for the history component of the HEART score to 1.0 for troponin. A low HEART score (0-3) maintains excellent sensitivity for predicting 6-week MACE in the setting of an outpatient disposition pathway for these patients.

Reliability of the CARE rule and the HEART score to rule out an acute coronary syndrome in non-traumatic chest pain patients.

In patients consulting in the Emergency Department for chest pain, a HEART score ≤ 3 has been shown to rule out an acute coronary syndrome (ACS) with a low risk of major adverse cardiac event (MACE) occurrence. A negative CARE rule (≤ 1) that stands for the first four elements of the HEART score may have similar rule-out reliability without troponin assay requirement. We aim to prospectively assess the performance of the CARE rule and of the HEART score to predict MACE in a chest pain population. Prospective two-center non-interventional study. Patients admitted to the ED for non-traumatic chest pain were included, and followed-up at 6 weeks. The main study endpoint was the 6-week rate of MACE (myocardial infarction, coronary angioplasty, coronary bypass, and sudden unexplained death). 641 patients were included, of whom 9.5% presented a MACE at 6 weeks. The CARE rule was negative for 31.2% of patients, and none presented a MACE during follow-up [0, 95% confidence interval: (0.0-1.9)]. The HEART score was ≤ 3 for 63.0% of patients, and none presented a MACE during follow-up [0% (0.0-0.9)]. With an incidence below 2% in the negative group, the CARE rule seemed able to safely rule out a MACE without any biological test for one-third of patients with chest pain and the HEART score for another third with a single troponin assay.

Prognosticating Clinical Prediction Scores Without Clinical Gestalt for Patients With Chest Pain in the Emergency Department.

BACKGROUND: Assessment of patients with chest pain is a regular challenge in the emergency department (ED). Recent guidelines recommended quantitative assessment of ischemic risk by means of risk scores. OBJECTIVE: Our aim was to assess the performance of Thrombosis in Myocardial Infarction (TIMI); Global Registry of Acute Coronary Events (GRACE); history, electrocardiogram, age, risk factors, and troponin (HEART) scores; and the North America Chest Pain Rule (NACPR) without components of clinical gestalt in predicting 30-day major adverse cardiac events (MACE). METHODS: We performed a prospective cohort study in adult patients who attended the ED with undifferentiated chest pain. Clinical prediction rules were applied and calculated. The clinical prediction rules were modified from the original ones, excluding components requiring judgment by clinical gestalt. The primary outcome was MACE. Performance of the tests were evaluated by receive operating characteristic curves and the area under curves (AUC). RESULTS: There were 1081 patients included in the study. Thirty-day MACE occurred in 164 (15.2%) patients. The AUC of the GRACE score was 0.756, which was inferior to the TIMI score (AUC 0.809) and the HEART score (AUC 0.845). A TIMI score ≥ 1 had a sensitivity of 97% and a specificity of 45.7%. A GRACE score ≥ 50 had a sensitivity of 99.4% and a specificity of 7.5%. A HEART score ≥ 1 had a sensitivity of 98.8% and a specificity of 11.7%. The NACPR had a sensitivity of 93.3% and a specificity of 51.5%. CONCLUSIONS: Without clinical gestalt, the modified HEART score had the best discriminative capacity in predicting 30-day MACE.

A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation.

BACKGROUND:: Currently, there is no validated multivariate model to predict probability of obstructive coronary disease in patients with acute chest pain. OBJECTIVE:: To develop and validate a multivariate model to predict coronary artery disease (CAD) based on variables assessed at admission to the coronary care unit (CCU) due to acute chest pain. METHODS:: A total of 470 patients were studied, 370 utilized as the derivation sample and the subsequent 100 patients as the validation sample. As the reference standard, angiography was required to rule in CAD (stenosis ≥ 70%), while either angiography or a negative noninvasive test could be used to rule it out. As predictors, 13 baseline variables related to medical history, 14 characteristics of chest discomfort, and eight variables from physical examination or laboratory tests were tested. RESULTS:: The prevalence of CAD was 48%. By logistic regression, six variables remained independent predictors of CAD: age, male gender, relief with nitrate, signs of heart failure, positive electrocardiogram, and troponin. The area under the curve (AUC) of this final model was 0.80 (95% confidence interval [95%CI] = 0.75 - 0.84) in the derivation sample and 0.86 (95%CI = 0.79 - 0.93) in the validation sample. Hosmer-Lemeshow's test indicated good calibration in both samples (p = 0.98 and p = 0.23, respectively). Compared with a basic model containing electrocardiogram and troponin, the full model provided an AUC increment of 0.07 in both derivation (p = 0.0002) and validation (p = 0.039) samples. Integrated discrimination improvement was 0.09 in both derivation (p < 0.001) and validation (p < 0.0015) samples. CONCLUSION:: A multivariate model was derived and validated as an accurate tool for estimating the pretest probability of CAD in patients with acute chest pain. FUNDAMENTO:: Atualmente, não existe um modelo multivariado validado para predizer a probabilidade de doença coronariana obstrutiva em pacientes com dor torácica aguda. OBJETIVO:: Desenvolver e validar um modelo multivariado para predizer doença arterial coronariana (DAC) com base em variáveis avaliadas à admissão na unidade coronariana (UC) devido a dor torácica aguda. MÉTODOS:: Foram estudados um total de 470 pacientes, 370 utilizados como amostra de derivação e os subsequentes 100 pacientes como amostra de validação. Como padrão de referência, a angiografia foi necessária para descartar DAC (estenose ≥ 70%), enquanto a angiografia ou um teste não invasivo negativo foi utilizado para confirmar a doença. Foram testadas como preditoras 13 variáveis basais relacionadas à história médica, 14 características de desconforto torácico e oito variáveis relacionadas ao exame físico ou testes laboratoriais. RESULTADOS:: A prevalência de DAC foi de 48%. Por regressão logística, seis variáveis permaneceram como preditoras independentes de DAC: idade, gênero masculino, alívio com nitrato, sinais de insuficiência cardíaca, e eletrocardiograma e troponina positivos. A área sob a curva (area under the curve, AUC) deste modelo final foi de 0,80 (intervalo de confiança de 95% [IC95%] = 0,75 - 0,84) na amostra de derivação e 0,86 (IC95% = 0,79 - 0,93) na amostra de validação. O teste de Hosmer-Lemeshow indicou uma boa calibração em ambas as amostras (p = 0,98 e p = 0,23, respectivamente). Em comparação com o modelo básico contendo eletrocardiograma e troponina, o modelo completo ofereceu um incremento na AUC de 0,07 tanto na amostra de derivação (p = 0,0002) quanto na de validação (p = 0,039). A melhoria na discriminação integrada foi de 0,09 nas amostras de derivação (p < 0,001) e validação (p < 0,0015). CONCLUSÃO:: Um modelo multivariado foi derivado e validado como uma ferramenta acurada para estimar a probabilidade pré-teste de DAC em pacientes com dor torácica aguda.

A Multivariate Model for Prediction of Obstructive Coronary Disease in Patients with Acute Chest Pain: Development and Validation / Um Modelo Multivariado para Predição de Doença Coronariana Obstrutiva em Pacientes com Dor Torácica Aguda: Desenvolvimento e Validação

Abstract Background: Currently, there is no validated multivariate model to predict probability of obstructive coronary disease in patients with acute chest pain. Objective: To develop and validate a multivariate model to predict coronary artery disease (CAD) based on variables assessed at admission to the coronary care unit (CCU) due to acute chest pain. Methods: A total of 470 patients were studied, 370 utilized as the derivation sample and the subsequent 100 patients as the validation sample. As the reference standard, angiography was required to rule in CAD (stenosis ≥ 70%), while either angiography or a negative noninvasive test could be used to rule it out. As predictors, 13 baseline variables related to medical history, 14 characteristics of chest discomfort, and eight variables from physical examination or laboratory tests were tested. Results: The prevalence of CAD was 48%. By logistic regression, six variables remained independent predictors of CAD: age, male gender, relief with nitrate, signs of heart failure, positive electrocardiogram, and troponin. The area under the curve (AUC) of this final model was 0.80 (95% confidence interval [95%CI] = 0.75 - 0.84) in the derivation sample and 0.86 (95%CI = 0.79 - 0.93) in the validation sample. Hosmer-Lemeshow's test indicated good calibration in both samples (p = 0.98 and p = 0.23, respectively). Compared with a basic model containing electrocardiogram and troponin, the full model provided an AUC increment of 0.07 in both derivation (p = 0.0002) and validation (p = 0.039) samples. Integrated discrimination improvement was 0.09 in both derivation (p < 0.001) and validation (p < 0.0015) samples. Conclusion: A multivariate model was derived and validated as an accurate tool for estimating the pretest probability of CAD in patients with acute chest pain.

Resumo Fundamento: Atualmente, não existe um modelo multivariado validado para predizer a probabilidade de doença coronariana obstrutiva em pacientes com dor torácica aguda. Objetivo: Desenvolver e validar um modelo multivariado para predizer doença arterial coronariana (DAC) com base em variáveis avaliadas à admissão na unidade coronariana (UC) devido a dor torácica aguda. Métodos: Foram estudados um total de 470 pacientes, 370 utilizados como amostra de derivação e os subsequentes 100 pacientes como amostra de validação. Como padrão de referência, a angiografia foi necessária para descartar DAC (estenose ≥ 70%), enquanto a angiografia ou um teste não invasivo negativo foi utilizado para confirmar a doença. Foram testadas como preditoras 13 variáveis basais relacionadas à história médica, 14 características de desconforto torácico e oito variáveis relacionadas ao exame físico ou testes laboratoriais. Resultados: A prevalência de DAC foi de 48%. Por regressão logística, seis variáveis permaneceram como preditoras independentes de DAC: idade, gênero masculino, alívio com nitrato, sinais de insuficiência cardíaca, e eletrocardiograma e troponina positivos. A área sob a curva (area under the curve, AUC) deste modelo final foi de 0,80 (intervalo de confiança de 95% [IC95%] = 0,75 - 0,84) na amostra de derivação e 0,86 (IC95% = 0,79 - 0,93) na amostra de validação. O teste de Hosmer-Lemeshow indicou uma boa calibração em ambas as amostras (p = 0,98 e p = 0,23, respectivamente). Em comparação com o modelo básico contendo eletrocardiograma e troponina, o modelo completo ofereceu um incremento na AUC de 0,07 tanto na amostra de derivação (p = 0,0002) quanto na de validação (p = 0,039). A melhoria na discriminação integrada foi de 0,09 nas amostras de derivação (p < 0,001) e validação (p < 0,0015). Conclusão: Um modelo multivariado foi derivado e validado como uma ferramenta acurada para estimar a probabilidade pré-teste de DAC em pacientes com dor torácica aguda.

Utility of the Diamond-Forrester Classification in Stratifying Acute Chest Pain in an Academic Chest Pain Center.

BACKGROUND: Because the Diamond-Forrester (DF) model is predictive of obstructive coronary artery disease (CAD), it is often used to risk stratify acute chest pain patients. We sought to further evaluate the clinical utility of the DF model within a chest pain evaluation center. METHODS: Consecutive patients with chest pain and no known CAD or evidence of active ischemia were asked to participate in a prospective registry. Patients were classified based on cardiovascular risk factors, age, and DF classification. We compared data from the emergency department course, Duke Activity Status Index (DASI) and Seattle Angina Questionnaire (SAQ), hospitalization rates, and results of testing between patients with typical angina and all others. Multivariate logistic regression was also used to assess for predictors of CAD by computed tomography coronary angiography (CTCA) or positive exercise treadmill testing (ETT). RESULTS: Among 209 patients, 163 had atypical/noncardiac and 46 had typical chest pain. The SAQ and DASI scores were lower in the typical chest pain group (indicating more severe impairment), which were not statistically significantly different. There were no significant differences in risk factors or the results of CTCA, ETT, or cardiac catheterization. In the regression analysis, SAQ score, DASI score, and DF classification were not predictive of CAD by CTCA. Worsening angina frequency scores on the SAQ were marginally associated with positive ETT (OR, 1.04; P=0.04). CONCLUSION: In a contemporary low-risk acute chest pain population, typical angina, as defined by the DF classification, was not predictive of CAD or useful for identifying patients with higher symptom burden.

Risk scoring for prediction of acute cardiac complications from imbalanced clinical data.

Fast and accurate risk stratification is essential in the emergency department (ED) as it allows clinicians to identify chest pain patients who are at high risk of cardiac complications and require intensive monitoring and early intervention. In this paper, we present a novel intelligent scoring system using heart rate variability, 12-lead electrocardiogram (ECG), and vital signs where a hybrid sampling-based ensemble learning strategy is proposed to handle data imbalance. The experiments were conducted on a dataset consisting of 564 chest pain patients recruited at the ED of a tertiary hospital. The proposed ensemble-based scoring system was compared with established scoring methods such as the modified early warning score and the thrombolysis in myocardial infarction score, and showed its effectiveness in predicting acute cardiac complications within 72 h in terms of the receiver operation characteristic analysis.

Reconstruction of the decision-making process in assessing musculoskeletal chest pain: an exploratory study using recursive partitioning.

OBJECTIVE: The purposes of this study were to identify the most important determinants from the patient history and clinical examination in diagnosing musculoskeletal chest pain (MSCP) in patients with acute noncardiac chest pain when supported by a structured protocol and to construct a decision tree for identification of MSCP in acute noncardiac chest pain. METHODS: Consecutive patients with noncardiac chest pain (n = 302) recruited from an emergency cardiology department were assessed. Using data from self-report questionnaires, interviews, and clinical assessment, patient characteristics were associated with the MSCP diagnosis, and the decision-making process of the clinician was reconstructed using recursive procedures in the tradition of constructing Classification and Regression Trees. RESULTS: Thirty-eight percent of patients had MSCP. There was no single determinant that predicted the condition completely. However, many items with high associations could be identified, mainly with high negative predictive value. The decision-making process was reconstructed giving rise to a 5-step, linear decision tree without branches. CONCLUSIONS: Clinicians use a combination of indicators including systematic palpation of the spine and chest wall and items from the case history to diagnose MSCP. However, the high negative predictive values of the main determinants suggest that the MSCP diagnosis may be a diagnosis by exclusion.

Community-acquired pneumonia in younger patients is an entity on its own.

Community-acquired pneumonia (CAP) is now most frequent in elderly patients. CAP in the younger patient has attracted much less attention. Therefore, we compared patients with CAP aged 18 to <65 yrs with those aged ≥ 65 yrs. Data from the prospective multicentre Competence Network for Community Acquired Pneumonia Study Group (CAPNETZ) database were analysed for potential differences in baseline characteristics, comorbidities, clinical presentation, microbial investigations, aetiologies, antimicrobial treatment and outcomes. Overall, 7,803 patients were studied. The proportion of younger patients (aged <65 yrs) was 52.3% (18 to <30 yrs 6.4%; <40 yrs 17.1%; <50 yrs 29.4%). Comorbidity was present in only half of the younger patients (46.6% versus 88.2%). Fever and chest pain were more common. Most younger patients presented with mild CAP (74.0% had a CRB-65 [corrected] score of 0 (confusion of new onset, [corrected] respiratory rate of ≥ 30 breaths · min(-1), blood pressure <90 mmHg or diastolic blood pressure ≤ 60 mmHg, age ≥ 65 yrs)). Overall, Streptococcus pneumoniae and Mycoplasma pneumoniae were the most frequent pathogens in the younger patients. Short-term mortality was very low (1.7% versus 8.2%) and even lower in patients without comorbidity (0.3% versus 2.4%). Long-term mortality was 3.2% versus 15.9%, also lower in patients without comorbidity (0.8% versus 6.1%). Most of the differences found clearly arise after the fifth or within the middle of the sixth decade. CAP in the younger patient is a clinically distinct entity.

Identifying symptom groups from Emergency Department presenting complaint free text using SNOMED CT.

Patients presenting to Emergency Departments may be categorised into different symptom groups for the purpose of research and quality improvement. The grouping is challenging due to the variability in the way presenting complaints are recorded by clinical staff. This work proposes analysis of the presenting complaint free-text using the semantics encoded in the SNOMED CT ontology. This work demonstrates a validated prototype system that can classify unstructured free-text narratives into patient's symptom group. A rule-based mechanism was developed using variety of keywords to identify the patient's symptom group. The system was validated against the manual identification of the symptom groups by two expert clinical research nurses on 794 patient presentations from six participating hospitals. The comparison of system results with one clinical research nurse showed 99.3% sensitivity; 80.0% specificity and 0.9 F-score for identifying "chest pain" symptom group.