Hypersensitivity pneumonitis: application of a new diagnostic algorithm to a time series of the disease.

BACKGROUND: The diagnostic criteria for Hypersensitivity pneumonitis (HP) have changed over time. Our aim is to apply a recent diagnostic algorithm to a historical series of patients diagnosed with HP to assess its distribution according to current diagnostic criteria and the diagnostic confidence achieved. RESEARCH DESIGN AND METHODS: Application to each patient the algorithm criteria. The diagnosis was HP (≥90%), provisional high (70-89%) or low confidence (51-69%) or non-HP (unlikely) (≤50%); or HP, provisional or non-HP, if they had lung biopsy. RESULTS: 129 patients [mean age 64 ± 12 years; 79 (61.2%) women] were included of which 16 (12.4%) were diagnosed on the basis of high clinical suspicion. After applying the algorithm, 106 patients (82.2%) could be evaluated and 83 (78.3%) had a diagnosis of HP or high confidence. Lung biopsy was able to establish a diagnosis of certainty in another 21 patients and a provisional diagnosis in 9 more [total, 113 (87.6%)]. The 16 patients without strict diagnostic criteria for HP had a low confidence diagnosis. A total of 56 lung biopsies (64.4%) could have been avoided according to the new guidelines. CONCLUSIONS: The application of this algorithm achieves a high diagnostic yield in HP, significantly reducing the number of lung biopsies required.

Effect of an intensive tobacco cessation program on the smoker narrative: A content analysis and grounded theory.

INTRODUCTION: The smoker's narrative during smoking quitting provides insight into aspects not fully explored in daily clinical practice. The aim of the study was to analyze the smoker narrative using two types of methodologies: content analysis and grounded theory, before and after smoking cessation intervention, provided to the smoker in a specialized Smoking Cessation Unit accredited by the Spanish Society of Pneumology and Thoracic Surgery. METHODS: A prospective observational study of current smokers included in a tobacco cessation program between 2017 and 2020 was conducted at the Smoking Cessation Unit of Santiago de Compostela Health Area, Spain. Routine clinical variables and patient narrative data were collected. A descriptive analysis of the sample, the content of the textual corpus, and a grounded theory were performed in semi-structured interviews at baseline and at follow-up at 6 months. RESULTS: A total of 116 patients were included (mean age 55.6 ± 10.6 years; 56.9% male; mean nicotine dependence score 5.7 ± 1.6). Quantitative analysis of the narrative shows that the most frequent phrases and words are associated with smoking, nicotine craving, and predisposition for smoking cessation. After the intervention, phrases related to the manifestation of abstinence, response to pharmacological treatment, and self-perception of smoking cessation were predominant. In the qualitative analysis, the most frequent categories in the smoker's textual corpus were dependence, motivation, and emotionality, which decreased after the intervention (11.4%, 21.4%, and 9.9%, respectively) accompanied by increased satisfaction (19.2%) and the manifestation of abstinence (21.5%). CONCLUSIONS: Motivation, nicotine dependence, and sensitivity to emotions are all closely intertwined in the current smoker narrative and can be modified as a consequence of treatment.

A pulmonary rehabilitation program reduces hospitalizations in chronic obstructive pulmonary disease patients: A cost-effectiveness study.

BACKGROUND: Although pulmonary rehabilitation (PR) is recommended in patients with chronic obstructive pulmonary disease (COPD), there is a scarcity of data demonstrating the cost-effectiveness and effectiveness of PR in reducing exacerbations. METHODS: A quasi-experimental study in 200 patients with COPD was conducted to determine the number of exacerbations 1 year before and after their participation in a PR program. Quality of life was measured using the COPD assessment test and EuroQol-5D. The costs of the program and exacerbations were assessed the year before and after participation in the PR program. The incremental cost-effectiveness ratio (ICER) was estimated in terms of quality-adjusted life years (QALYs). RESULTS: The number of admissions, length of hospital stay, and admissions to the emergency department decreased after participation in the PR program by 48.2%, 46.6%, and 42.5%, respectively (P < 0.001 for all). Results on quality of life tests improved significantly (P < 0.001 for the two tests). The cost of PR per patient and the cost of pre-PR and post-PR exacerbations were €1867.7 and €7895.2 and €4201.9, respectively. The PR resulted in a cost saving of €1826 (total, €365,200) per patient/year, and the gain in QALYs was+0.107. ICER was -€17,056. The total cost was <€20,000/QALY in 78% of patients. CONCLUSIONS: PR contributes to reducing the number of exacerbations in patients with COPD, thereby slowing clinical deterioration. In addition, it is cost-effective in terms of QALYs.

Development of prognostic models to estimate the probability of lung injury one year after COVID-19-related hospitalization-a prospective study.

Background: Long-term effects of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection still under study. The objectives of this study were to identify persistent pulmonary lesions 1 year after coronavirus disease 2019 (COVID-19) hospitalization and assess whether it is possible to estimate the probability that a patient develops these complications in the future. Methods: A prospective study of ≥18 years old patients hospitalized for SARS-COV-2 infection who develop persistent respiratory symptoms, lung function abnormalities or have radiological findings 6-8 weeks after hospital discharge. Logistic regression models were used to identify prognostic factors associated with a higher risk of developing respiratory problems. Models performance was assessed in terms of calibration and discrimination. Results: A total of 233 patients [median age 66 years [interquartile range (IQR): 56, 74]; 138 (59.2%) male] were categorized into two groups based on whether they stayed in the critical care unit (79 cases) or not (154). At the end of follow-up, 179 patients (76.8%) developed persistent respiratory symptoms, and 22 patients (9.4%) showed radiological fibrotic lesions with pulmonary function abnormalities (post-COVID-19 fibrotic pulmonary lesions). Our prognostic models created to predict persistent respiratory symptoms [post-COVID-19 functional status at initial visit (the higher the score, the higher the risk), and history of bronchial asthma] and post-COVID-19 fibrotic pulmonary lesions [female; FVC% (the higher the FVC%, the lower the probability); and critical care unit stay] one year after infection showed good (AUC 0.857; 95% CI: 0.799-0.915) and excellent performance (AUC 0.901; 95% CI: 0.837-0.964), respectively. Conclusions: Constructed models show good performance in identifying patients at risk of developing lung injury one year after COVID-19-related hospitalization.

Pleural effusion due to nonmalignant gastrointestinal disease.

Although pleural effusion is a frequent finding in clinical practice, determining its aetiology may be challenging, and up to 20% of cases remain undiagnosed. Pleural effusion may occur secondary to a nonmalignant gastrointestinal disease. A gastrointestinal origin is confirmed based on a review of the medical history of the patient, thorough physical examination and abdominal ultrasonography. In this process, it is crucial to correctly interpret findings on pleural fluid obtained by thoracentesis. In the absence of high clinical suspicion, identifying the aetiology of this type of effusion may be difficult. Clinical symptoms will be determined by the gastrointestinal process causing pleural effusion. In this setting, correct diagnosis relies on the specialist's ability to evaluate pleural fluid appearance, test for the appropriate biochemical parameters and determine whether it is necessary or not to send a specimen for culture. The established diagnosis will determine how pleural effusion is approached. Although this clinical condition is self-limited, many cases will require a multidisciplinary approach because some effusions can only be resolved with specific therapies.

Cost-Effectiveness of a New Outpatient Pulmonology Care Model Based on Physician-to-Physician Electronic Consultation.

Introduction: This study assesses the impact of an electronic physician-to-physician consultation program on the waiting list and the costs of a Pulmonology Unit. Materials and Methods: A prepost intervention study was conducted after a new ambulatory pulmonary care protocol was implemented and the capacity of the unit was adopted. In the new model, physicians at all levels of healthcare send electronic consultations to specialists. Results: In the preintervention year (2019), the Unit of Pulmonology attended 7,055 consultations (466 e-consultations and 6,589 first face-to-face visits), which decreased to 6,157 (3,934 e-consultations and 2,223 first face-to-face visits; 12.7% reduction) in the postintervention year (all were e-consultations). The mean wait time for the first appointment was 25.7 days in 2019 versus 3.2 days in 2021 (p < 0.001). In total, 43.5% of cases were solved via physician-to-physiciane-consultation. A total of 2,223 patients needed a face-to-face visit, with a mean wait time of 7.5 days. The mean of patients in the waiting listing decreased from 450.8 in 2019 to 44.8 in 2021 (90% reduction). The annual time devoted to e-consultations and first face-to-face visits following an e-consultation diminished significantly after the intervention (1,724 hours versus 2,312.8; 25.4% reduction). Each query solved via e-consultation represented a saving of €652.8, resulting in a total annual saving of €827,062. Conclusions: Physician-to-physiciane-consultations reduce waiting times, improve access of complex patients to specialty care, and ensure that cases are managed at the appropriate level. E-consultation reduces costs, which benefits both, society and the healthcare system.

Sarcoidosis. Disease progression based on radiological and functional course: Predictive factors.

BACKGROUND: Sarcoidosis is a multiorgan granulomatous disease with a variable course. OOBJECTIVES: The purpose of this study is to identify the patients that are more likely to experience disease progression. METHODS: A retrospective study in patients ≥18 years. Pulmonary function and radiological stage (Scadding criteria) were assessed at diagnosis, and at 1, 3 and 5 years. Sarcoidosis progression was established based on deterioration of radiological or pulmonary function (decrease ≥10% of FVC and/or ≥15% of diffusing capacity of the lung (DLCO). RESULTS: The sample included 277 caucasian patients [mean age, 50±13.6; 69.7% between 31-60 years; 56.3% men]. In total, 65% had stage II sarcoidosis, whereas only 8.3% had stage III/IV disease. Mean pulmonary function (FVC, FEV1, FEV1/FVC and DLCO) at diagnosis was 103±21.8, 96±22.2, 76.2±8 and 81.7±21.7, respectively. The percentage of patients with normal FVC and DLCO was 72.2% and 51.8%, respectively. Radiological stage did not change significantly during follow-up (5 years; p=0.080) and only progressed in 13 patients (5.7%). At 3 years, FVC improved, whereas DLCO exacerbated significantly (p<0.001 for the two). Disease progressed in 34.5% of the patients (57/165) whose pulmonary function and radiological stage were available (both baseline and at 3 years). Age was associated with disease progression [OR=1.04 (95%CI=1.01, 1.06)]. Risk increased by 4% for each year older a patient was at diagnosis. CONCLUSIONS: At 3 years, a third of patients experienced sarcoidosis progression. Age was the only factor associated with disease prognosis.

Health outcomes: Towards the accreditation of respiratory medicine departments / Resultados de salud: hacia la acreditación de los servicios de neumología

National health systems must ensure compliance with conditions such as equity, efficiency, quality, and transparency. Since it is the right of society to know the health outcomes of its healthcare system, our aim was to develop a proposal for the accreditation of respiratory medicine departments in terms of care, teaching, and research, measuring health outcomes using quality of care indicators. The management tools proposed in this article should be implemented to improve outcomes and help us achieve our objectives. Promoting accreditation can serve as a stimulus to improve clinical management and enable professionals to take on greater leadership roles and take action to improve outcomes in patient care. (AU)

Los sistemas nacionales de salud deben garantizar a los ciudadanos el cumplimiento de unas condiciones básicas como la equidad, la eficiencia, la calidad y la transparencia. En aras del derecho que tiene la sociedad a conocer los resultados de salud de su área sanitaria, el objetivo de este artículo es elaborar una propuesta de acreditación de los servicios de neumología desde el punto de vista asistencial, docente e investigador, midiendo sus resultados de salud a través de indicadores de calidad en la atención. Para mejorar estos, deberíamos utilizar unas herramientas de gestión (que se desarrollan en el artículo) y que, sin duda, nos ayudarían a conseguir los objetivos propuestos. La mejora del nivel de acreditación puede servir como estímulo para perfeccionar la gestión clínica y para que los profesionales ejerzan una capacidad de dirección cada vez mayor y adopten medidas para reforzar los resultados en la atención a sus pacientes. (AU)

Health Outcomes: Towards the Accreditation of Respiratory Medicine Departments. / Resultados de salud: hacia la acreditación de los servicios de neumología.

National health systems must ensure compliance with conditions such as equity, efficiency, quality, and transparency. Since it is the right of society to know the health outcomes of its healthcare system, our aim was to develop a proposal for the accreditation of respiratory medicine departments in terms of care, teaching, and research, measuring health outcomes using quality of care indicators. The management tools proposed in this article should be implemented to improve outcomes and help us achieve our objectives. Promoting accreditation can serve as a stimulus to improve clinical management and enable professionals to take on greater leadership roles and take action to improve outcomes in patient care.

Health outcomes: Towards the accreditation of respiratory medicine departments.

National health systems must ensure compliance with conditions such as equity, efficiency, quality, and transparency. Since it is the right of society to know the health outcomes of its healthcare system, our aim was to develop a proposal for the accreditation of respiratory medicine departments in terms of care, teaching, and research, measuring health outcomes using quality of care indicators. The management tools proposed in this article should be implemented to improve outcomes and help us achieve our objectives. Promoting accreditation can serve as a stimulus to improve clinical management and enable professionals to take on greater leadership roles and take action to improve outcomes in patient care.

Malignant Pleural Effusion: Diagnosis and Management.

Symptomatic malignant pleural effusion is a common clinical problem. This condition is associated with very high mortality, with life expectancy ranging from 3 to 12 months. Studies are contributing evidence on an increasing number of therapeutic options (therapeutic thoracentesis, thoracoscopic pleurodesis or thoracic drainage, indwelling pleural catheter, surgery, or a combination of these therapies). Despite the availability of therapies, the management of malignant pleural effusion is challenging and is mainly focused on the relief of symptoms. The therapy to be administered needs to be designed on a case-by-case basis considering patient's preferences, life expectancy, tumour type, presence of a trapped lung, resources available, and experience of the treating team. At present, the management of malignant pleural effusion has evolved towards less invasive approaches based on ambulatory care. This approach spares the patient the discomfort caused by more invasive interventions and reduces the economic burden of the disease. A review was performed of the diagnosis and the different approaches to the management of malignant pleural effusion, with special emphasis on their indications, usefulness, cost-effectiveness, and complications. Further research is needed to shed light on the current matters of controversy and help establish a standardized, more effective management of this clinical problem.

Identification of Pleural Response Patterns: A Cluster Analysis / Identificación de patrones de respuesta pleural: un análisis de conglomerados

BACKGROUND: Pleural effusion occurs as a response of the pleura to aggressions. The pleura reacts differently according to the type of injury. However, pleural reactions have not yet been characterized. The objective of this study was to identify homogeneous clusters of patients based on the analytical characteristics of their pleural fluid and identify pleural response patterns. METHODS: A prospective study was conducted of consecutive patients seen in our unit for pleural effusion. Principal component and cluster analyses were carried out to identify pleural response patterns based on a combination of pleural fluid biomarkers. RESULTS: A total of 1613 patients were grouped into six clusters, namely: cluster 1 (10.5% of the cohort, primarily composed of patients with malignant pleural effusions); cluster 2 (17.4%, pleural effusions with inflammatory biomarkers); cluster 3 (16.1%, primarily composed of patients with infectious pleural effusions); cluster 4 (2.5%, a subcluster of cluster 3, superinfectious effusions); cluster 5 (23.4%, paucicellular pleural effusions); and cluster 6 (30.1%, miscellaneous). Significant differences were observed across clusters in terms of the analytical characteristics of PF (p < 0.001 for all), age (p < 0.001), and gender (p = 0.016). A direct relationship was found between the type of cluster and the etiology of pleural effusion. CONCLUSION: Pleural response is heterogeneous. The pleura may respond differently to the same etiology or similarly to different etiologies, which hinders diagnosis of pleural effusion

INTRODUCCIÓN: El derrame pleural ocurre como una respuesta de la pleura a las agresiones. La pleura reacciona de manera diferente según el tipo de lesión. Sin embargo, las reacciones pleurales aún no se han clasificado. El objetivo de este estudio fue identificar grupos homogéneos de pacientes basados en las características analíticas de su líquido pleural e identificar patrones de respuesta pleural. MÉTODOS: Se realizó un estudio prospectivo de pacientes consecutivos ingresados en nuestra unidad por presentar derrame pleural. Se llevaron a cabo análisis de componentes principales y análisis de conglomerados para identificar los patrones de respuesta pleural basados en las combinaciones de biomarcadores del líquido pleural. RESULTADOS: Un total de 1.613 pacientes se agruparon en 6 grupos: conglomerado 1 (10,5% de la cohorte, compuesto principalmente por pacientes con derrames pleurales malignos); conglomerado 2 (17,4%, derrames pleurales con biomarcadores inflamatorios); conglomerado 3 (16,1%, compuesto principalmente por pacientes con derrames pleurales infecciosos); conglomerado 4 (2,5%, un subgrupo del conglomerado 3, derrames superinfecciosos); conglomerado 5 (23,4%, derrames pleurales paucicelulares), y el conglomerado 6 (30,1%, miscelánea). Se observaron diferencias significativas entre los grupos en las características analíticas del líquido pleural (p < 0,001 para todos), la edad (p < 0,001) y el género (p = 0,016). Se encontró una relación directa entre el tipo de conglomerado y la etiología del derrame pleural. CONCLUSIONES: La respuesta pleural es heterogénea. La pleura puede responder de manera diferente a una misma etiología o de manera similar en diferentes etiologías, lo que dificulta el diagnóstico de derrame pleural

Identification of Pleural Response Patterns: A Cluster Analysis.

BACKGROUND: Pleural effusion occurs as a response of the pleura to aggressions. The pleura reacts differently according to the type of injury. However, pleural reactions have not yet been characterized. The objective of this study was to identify homogeneous clusters of patients based on the analytical characteristics of their pleural fluid and identify pleural response patterns. METHODS: A prospective study was conducted of consecutive patients seen in our unit for pleural effusion. Principal component and cluster analyses were carried out to identify pleural response patterns based on a combination of pleural fluid biomarkers. RESULTS: A total of 1613 patients were grouped into six clusters, namely: cluster 1 (10.5% of the cohort, primarily composed of patients with malignant pleural effusions); cluster 2 (17.4%, pleural effusions with inflammatory biomarkers); cluster 3 (16.1%, primarily composed of patients with infectious pleural effusions); cluster 4 (2.5%, a subcluster of cluster 3, superinfectious effusions); cluster 5 (23.4%, paucicellular pleural effusions); and cluster 6 (30.1%, miscellaneous). Significant differences were observed across clusters in terms of the analytical characteristics of PF (p<0.001 for all), age (p<0.001), and gender (p=0.016). A direct relationship was found between the type of cluster and the etiology of pleural effusion. CONCLUSION: Pleural response is heterogeneous. The pleura may respond differently to the same etiology or similarly to different etiologies, which hinders diagnosis of pleural effusion.

La combinación de la determinación de parámetros bioquímicos del líquido pleural mejora la predicción diagnóstica de la infección pleural complicada/empiema / The Combined Use of Pleural Fluid Parameters Improves Diagnostic Accuracy in Complicated Pleural Infection/Empyema

Introducción: Predecir cuándo un derrame pleural infeccioso puede evolucionar hacia una infección complicada/empiema es difícil de establecer. Nuestro propósito es analizar si un modelo predictivo construido con parámetros bioquímicos del líquido pleural puede ayudar a identificar estos derrames. Métodos: Se estudió de forma prospectiva a todos los pacientes diagnosticados de derrame pleural infeccioso y se clasificaron en no complicados y complicados/empiemas. Se realizó un análisis de regresión logística para estimar la probabilidad de infección pleural complicada/empiema. Con base en parámetros bioquímicos del líquido pleural, se construyó un modelo predictivo y se determinaron su discriminación (áreas bajo la curva ROC), calibración y precisión diagnóstica. Resultados: Se incluyó a 177 pacientes (74 infecciones pleurales no complicadas y 103 complicadas/empiemas). El área bajo la curva del modelo construido (pH, lactato deshidrogenasa e interleucina 6) fue 0,9783, significativamente mejor que cualquiera de las variables bioquímicas utilizadas de forma individual (0,921, 0,949 y 0,837, respectivamente; p < 0,001 usando todos los parámetros). La tasa de clasificación correcta fue del 96% de los derrames (170/177; 72/74 [97,3%] de los no complicados y 98/103 [95,1%] de los complicados/empiemas). Conclusión: El modelo predictivo analizado tiene una buena rentabilidad para el diagnóstico de las infecciones pleurales complicadas/empiemas, superior a la de cualquiera de las variables individuales que lo componen

Introduction: Identifying infectious pleural effusions (IPE) that will progress to complicated infection or empyema is challenging. The purpose of this study was to determine whether a model based on multiple biochemical parameters in pleural fluid can predict which IPEs will produce empyema. Methods: A prospective study was performed of all cases of IPEs treated in our unit. IPEs were classified as uncomplicated or complicated (empyema). Logistic regression was used to estimate the risk for complicated pleural infection (empyema). A predictive model was developed using biochemical parameters in pleural fluid. Discriminatory power (areas under the ROC curve), calibration, and diagnostic accuracy of the model were assessed. Results: A total of 177 patients were included in the study (74 with uncomplicated infectious pleural effusion, and 103 with complicated pleural effusion/empyema). The area under the curve (AUC) for the model (pH, lactate dehydrogenase and interleukin 6) was 0.9783, which is significantly superior to the AUC of the individual biochemical parameters alone (0.921, 0.949, and 0.837, respectively; P <.001 using all parameters). The rate of correct classification of infectious pleural effusions was 96% [170/177: 72/74 (97.3%) for uncomplicated and 98/103 (95.1%) for complicated effusion (empyema)]. Conclusion: The multiple-marker model showed better diagnostic performance for predicting complicated infectious pleural effusion (empyema) compared to individual parameters alone

Diagnosis of infectious pleural effusion using predictive models based on pleural fluid biomarkers.

INTRODUCTION: Diagnosis of pleural infection (PI) may be challenging. The purpose of this paper is to develop and validate a clinical prediction model for the diagnosis of PI based on pleural fluid (PF) biomarkers. METHODS: A prospective study was conducted on pleural effusion. Logistic regression was used to estimate the likelihood of having PI. Two models were built using PF biomarkers. The power of discrimination (area under the curve) and calibration of the two models were evaluated. RESULTS: The sample was composed of 706 pleural effusion (248 malignant; 28 tuberculous; 177 infectious; 48 miscellaneous exudates; and 212 transudates). Areas under the curve for Model 1 (leukocytes, percentage of neutrophils, and C-reactive protein) and Model 2 (the same markers plus interleukin-6 [IL-6]) were 0.896 and 0.909, respectively (not significant differences). However, both models showed higher capacity of discrimination than their biomarkers when used separately (P < 0.001 for all). Rates of correct classification for Models 1 and 2 were 88.2% (623/706: 160/177 [90.4%] with infectious pleural effusion [IPE] and 463/529 [87.5%] with non-IPE) and 89.2% (630/706: 153/177 [86.4%] of IPE and 477/529 [90.2%] of non-IPE), respectively. CONCLUSIONS: The two predictive models developed for IPE showed a good diagnostic performance, superior to that of any of the markers when used separately. Although IL-6 contributes a slight greater capacity of discrimination to the model that includes it, its routine determination does not seem justified.

Necesidad de titular el oxígeno portátil mediante pruebas de marcha de 6 minutos / Need for Portable Oxygen Titration During 6-Minute Walk Tests

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¿Puede causar derrame pleural la insuficiencia cardiaca derecha? / Can Right Heart Failure Cause Pleural Effusion?

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The Combined Use of Pleural Fluid Parameters Improves Diagnostic Accuracy in Complicated Pleural Infection/Empyema. / La combinación de la determinación de parámetros bioquímicos del líquido pleural mejora la predicción diagnóstica de la infección pleural complicada/empiema.

INTRODUCTION: Identifying infectious pleural effusions (IPE) that will progress to complicated infection or empyema is challenging. The purpose of this study was to determine whether a model based on multiple biochemical parameters in pleural fluid can predict which IPEs will produce empyema. METHODS: A prospective study was performed of all cases of IPEs treated in our unit. IPEs were classified as uncomplicated or complicated (empyema). Logistic regression was used to estimate the risk for complicated pleural infection (empyema). A predictive model was developed using biochemical parameters in pleural fluid. Discriminatory power (areas under the ROC curve), calibration, and diagnostic accuracy of the model were assessed. RESULTS: A total of 177 patients were included in the study (74 with uncomplicated infectious pleural effusion, and 103 with complicated pleural effusion/empyema). The area under the curve (AUC) for the model (pH, lactate dehydrogenase and interleukin 6) was 0.9783, which is significantly superior to the AUC of the individual biochemical parameters alone (0.921, 0.949, and 0.837, respectively; P<.001 using all parameters). The rate of correct classification of infectious pleural effusions was 96% [170/177: 72/74 (97.3%) for uncomplicated and 98/103 (95.1%) for complicated effusion (empyema)]. CONCLUSION: The multiple-marker model showed better diagnostic performance for predicting complicated infectious pleural effusion (empyema) compared to individual parameters alone.