Diabetes y apnea obstructiva del sueño. Un estudio de casos y controles / Diabetes and obstructive sleep apnoea: A case-control study

Introducción La apnea obstructiva del sueño (AOS) y la diabetes mellitus (DM) son enfermedades muy prevalentes frecuentemente asociadas. Su coexistencia se asocia de forma independiente con un aumento de la prevalencia de comorbilidades cardiovasculares. Al existir un infradiagnóstico de esta asociación, es necesario optimizar la sospecha clínica mediante el estudio de predictores independientes de DM o de prediabetes (preDM) en pacientes con AOS. Método Estudio de casos y controles, seleccionados de manera aleatoria simple y emparejados por sexo, índice de masa corporal (IMC) y edad, que pretende estudiar la asociación de la AOS con la DM y la preDM e identificar factores predictores independientes para ambas enfermedades, en las personas con AOS. Resultados Incluimos 208 casos con AOS y 208 controles, sin AOS. En los primeros, el 18,8% tenían DM, por solo el 10,1% en los segundos (p=0,00). La prevalencia de preDM fue del 41,8% vs el 10,6%, respectivamente (p=0,00). Ciento veinticuatro casos (59,6%) refirieron excesiva somnolencia diurna (ESD) (escala Epworth, 10,5±3,1) vs el 24,5% del grupo control (escala Epworth, 6,6±2,9). El índice de apnea-hipopnea (IAH) y los índices de desaturación de O2 (IDO, CT90 y CT80) fueron significativamente mayores en el grupo de casos. El riesgo de presentar DM se relacionó con la edad, la hipoxemia nocturna y la ESD. El riesgo de presentar preDM, con el IMC y con el IAH. Conclusiones La AOS se asocia a la DM y a la preDM. La edad, la hipoxemia nocturna y la ESD son predictores de DM. El IMC y el IAH lo son de la preDM. (AU)

Introduction Obstructive sleep apnoea (OSA) and diabetes mellitus (DM) are very prevalent diseases frequently associated. Their coexistence is independently associated with an increased prevalence of cardiovascular comorbidities. As this association is underdiagnosed, it is necessary to optimise clinical suspicion by studying independent predictors of DM or prediabetes (preDM) in patients with OSA. Method A simple randomised case-control study, matched for sex, body mass index (BMI) and age, aimed to study the association of OSA with DM and preDM and to identify independent predictors for both diseases in people with OSA. Results We included 208 cases with OSA and 208 controls without OSA. In the former, 18.8% had DM compared to only 10.1% in the latter (P=.00). Prevalence of preDM was 41.8% vs. 10.6%, respectively (P=.00). One hundred and twenty-four cases (59.6%) reported excessive daytime sleepiness (EDS) (Epworth scale, 10.5±3.1) vs. 24.5% of the control group (Epworth scale, 6.6±2.9). Apnoea-hypopnoea index (AHI) and O2 desaturation indices (IDO, CT90 and CT80) were significantly higher in the case group. The risk of MD was related to age, nocturnal hypoxaemia and EDS. The risk of pre-MD was related to BMI and AHI. Conclusions OSA is associated with DM and preDM. Age, nocturnal hypoxaemia and EDS are predictors of DM. BMI and AHI are predictors of pre-MD. (AU)

Diabetes y apnea obstructiva del sueño. Un estudio de casos y controles / Diabetes and obstructive sleep apnoea: A case-control study

Introducción La apnea obstructiva del sueño (AOS) y la diabetes mellitus (DM) son enfermedades muy prevalentes frecuentemente asociadas. Su coexistencia se asocia de forma independiente con un aumento de la prevalencia de comorbilidades cardiovasculares. Al existir un infradiagnóstico de esta asociación, es necesario optimizar la sospecha clínica mediante el estudio de predictores independientes de DM o de prediabetes (preDM) en pacientes con AOS. Método Estudio de casos y controles, seleccionados de manera aleatoria simple y emparejados por sexo, índice de masa corporal (IMC) y edad, que pretende estudiar la asociación de la AOS con la DM y la preDM e identificar factores predictores independientes para ambas enfermedades, en las personas con AOS. Resultados Incluimos 208 casos con AOS y 208 controles, sin AOS. En los primeros, el 18,8% tenían DM, por solo el 10,1% en los segundos (p=0,00). La prevalencia de preDM fue del 41,8% vs el 10,6%, respectivamente (p=0,00). Ciento veinticuatro casos (59,6%) refirieron excesiva somnolencia diurna (ESD) (escala Epworth, 10,5±3,1) vs el 24,5% del grupo control (escala Epworth, 6,6±2,9). El índice de apnea-hipopnea (IAH) y los índices de desaturación de O2 (IDO, CT90 y CT80) fueron significativamente mayores en el grupo de casos. El riesgo de presentar DM se relacionó con la edad, la hipoxemia nocturna y la ESD. El riesgo de presentar preDM, con el IMC y con el IAH. Conclusiones La AOS se asocia a la DM y a la preDM. La edad, la hipoxemia nocturna y la ESD son predictores de DM. El IMC y el IAH lo son de la preDM. (AU)

Introduction Obstructive sleep apnoea (OSA) and diabetes mellitus (DM) are very prevalent diseases frequently associated. Their coexistence is independently associated with an increased prevalence of cardiovascular comorbidities. As this association is underdiagnosed, it is necessary to optimise clinical suspicion by studying independent predictors of DM or prediabetes (preDM) in patients with OSA. Method A simple randomised case-control study, matched for sex, body mass index (BMI) and age, aimed to study the association of OSA with DM and preDM and to identify independent predictors for both diseases in people with OSA. Results We included 208 cases with OSA and 208 controls without OSA. In the former, 18.8% had DM compared to only 10.1% in the latter (P=.00). Prevalence of preDM was 41.8% vs. 10.6%, respectively (P=.00). One hundred and twenty-four cases (59.6%) reported excessive daytime sleepiness (EDS) (Epworth scale, 10.5±3.1) vs. 24.5% of the control group (Epworth scale, 6.6±2.9). Apnoea-hypopnoea index (AHI) and O2 desaturation indices (IDO, CT90 and CT80) were significantly higher in the case group. The risk of MD was related to age, nocturnal hypoxaemia and EDS. The risk of pre-MD was related to BMI and AHI. Conclusions OSA is associated with DM and preDM. Age, nocturnal hypoxaemia and EDS are predictors of DM. BMI and AHI are predictors of pre-MD. (AU)

Analysis of the quality of e-Consultations in chronic obstructive pulmonary disease.

INTRODUCTION: The quality of e-Consultations in the COPD is unknown. The objectives of this study were (i) to evaluate the quality of referrals; (ii) to define the characteristics of patients referred from Primary Care (PC) to the Unit of Pulmonology; and (iii) to describe differences between accepted and rejected patients. METHODS: A retrospective, observational study of e-Consultations requested by PC for suspected COPD throughout 2022. To quantify the quality of the e-Consultations, an arbitrary scale of 12 variables (score 0-10) was created. RESULTS: In total, 384 e-Consultations were reviewed, of which 167 (43.5 %) resulted in a face-to-face visit, and 217 (56.5 %) were rejected. No differences were observed between the two types of patients, except for confirmations of diagnostic suspicion of COPD [significantly higher in accepted patients (p = 0.042)]; physical examination data of rejected patients (more data provided; p = 0.015); and lung function (significantly better in rejected patients). The mean quality of referrals was acceptable (5.6 ± 2.1 score): 121 (31.3 %) had insufficient quality; 118 (30.5 %) acceptable; 75 (19.4 %) good, and 30 (7.8 %) excellent. Quality was low in half of the variables analyzed (6/12); acceptable in 3, and good in another 3. The capacity of resolution of referrals was good (one e-Consultation) in 199 requests (66.1 %); deficient (two e-Consultations) in 72 (23.9 %), and poor (≥3 e-Consultations) in 30 (10 %). Overdiagnosis was 40.2 % (86/214 e-Consultations). The risk could be classified in 247 patients (64.3 %; 135 low-risk; 90 high-risk). CONCLUSIONS: When adequate information is provided, e-Consultations help identify different levels of severity. However, the quality and capacity of resolution of referrals were suboptimal, with a high percentage of overdiagnoses.

[Diabetes and obstructive sleep apnoea: A case-control study]. / Diabetes y apnea obstructiva del sueño. Un estudio de casos y controles.

INTRODUCTION: Obstructive sleep apnoea (OSA) and diabetes mellitus (DM) are very prevalent diseases frequently associated. Their coexistence is independently associated with an increased prevalence of cardiovascular comorbidities. As this association is underdiagnosed, it is necessary to optimise clinical suspicion by studying independent predictors of DM or prediabetes (preDM) in patients with OSA. METHOD: A simple randomised case-control study, matched for sex, body mass index (BMI) and age, aimed to study the association of OSA with DM and preDM and to identify independent predictors for both diseases in people with OSA. RESULTS: We included 208 cases with OSA and 208 controls without OSA. In the former, 18.8% had DM compared to only 10.1% in the latter (P=.00). Prevalence of preDM was 41.8% vs. 10.6%, respectively (P=.00). One hundred and twenty-four cases (59.6%) reported excessive daytime sleepiness (EDS) (Epworth scale, 10.5±3.1) vs. 24.5% of the control group (Epworth scale, 6.6±2.9). Apnoea-hypopnoea index (AHI) and O2 desaturation indices (IDO, CT90 and CT80) were significantly higher in the case group. The risk of MD was related to age, nocturnal hypoxaemia and EDS. The risk of pre-MD was related to BMI and AHI. CONCLUSIONS: OSA is associated with DM and preDM. Age, nocturnal hypoxaemia and EDS are predictors of DM. BMI and AHI are predictors of pre-MD.

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.

Response to inhaled ceftazidime in patients with non-cystic fibrosis bronchiectasis and chronic bronchial infection unrelated to Pseudomonas aeruginosa.

INTRODUCTION: Inhaled antibiotics reduce the frequency of exacerbations. The objective was to assess the efficacy of inhaled ceftazidime in patients with non-cystic fibrosis bronchiectasis (NCFB) and concomitant chronic bronchial infection (CBI) caused by potentially pathogenic microorganisms (PPM) other than Pseudomonas aeruginosa (PA). MATERIAL AND METHOD: Quasi-experimental study in 21 patients with exacerbations who developed CBI by a PPM other than PA. RESULTS: Bacterial infection was resolved in 85.7% patients. Rehospitalizations, length of hospital stay, moderate exacerbations and blood levels of CRP decreased significantly. In addition, SGRQ questionnaire also decreased more than 4 points in 57.1% of the patients. CONCLUSION: The results suggest that inhaled ceftazidime in NCFB unrelated to PA is a plausible alternative to the standard therapies used in clinical practice.

Impacto del síndrome de apnea-hipopnea del sueño en la neuropatía diabética. Revisión sistemática / Impact of sleep apnoea-hypopnoea syndrome on diabetic neuropathy. A systematic review

Introducción: La diabetes mellitus y el síndrome de apnea-hipopnea del sueño parecen estar relacionados, pero no está bien definido si en los pacientes con ambas enfermedades existe un mayor riesgo de neuropatía periférica. Para ello, realizamos una revisión sistemática.MétodosBúsqueda bibliográfica en 3 bases de datos electrónicas usando una estrategia predefinida y la metodología PRISMA. Solamente se incluyeron estudios originales (cualquier tipo de diseño) y publicados a partir del año 2000 en inglés, francés, portugués o español. Se estableció una escala de calidad de los estudios.ResultadosSe seleccionaron 12 artículos, de los que 6 estudiaban pacientes diabéticos tipo 2. La prevalencia global de síndrome de apnea-hipopnea del sueño fue del 43,7% (1.559/3.564 pacientes). La neuropatía diabética fue más frecuente en los pacientes con síndrome de apnea-hipopnea del sueño en 9 estudios, aunque solo en 4 de manera significativa (60 vs. 27%, p<0,001; 64,5 vs. 36%, p=0,03; 37 vs. 23,4%, p<0,02; 66,6 vs. 0%, p=0,007). En un estudio, la neuropatía diabética fue más frecuente en los pacientes sin síndrome de apnea-hipopnea del sueño (aunque sin significación estadística) y en 2 no se hizo la comparación entre pacientes con/sin síndrome de apnea-hipopnea del sueño.ConclusionesLos resultados observados indican una relación entre diabetes mellitus y síndrome de apnea-hipopnea del sueño en la aparición de neuropatía diabética.

Introduction: Diabetes mellitus and sleep apnoea-hypopnoea syndrome appear to be related, but it is not well defined whether there is an increased risk of peripheral neuropathy in patients with both diseases. For this reason, we conducted a systematic review.MethodsBibliographic search in 3 electronic databases using a predefined strategy and the PRISMA methodology. Only original studies (any type of design) published from 2000 onwards in English, French, Portuguese or Spanish were included. A study quality scale was established.ResultsTwelve articles were selected, of which six studied type 2 diabetic patients. The overall prevalence of sleep apnoea-hypopnoea syndrome was 43.7% (1,559/3,564 patients). Diabetic neuropathy was more frequent in patients with sleep apnoea-hypopnoea syndrome in nine studies, although significantly only in four (60% vs 27%, P<.001; 64.5% vs 36%, P=.03; 37% vs 23.4%, P<.02; 66.6% vs 0%, P=.007). In one study, diabetic neuropathy was more frequent in patients without sleep apnoea-hypopnoea syndrome (although not statistically significant) and in 2 no comparison was made between patients with/without sleep apnoea/hypopnoea syndrome.ConclusionsThe observed results suggest a relationship between diabetes mellitus and sleep apnoea-hypopnoea syndrome in the occurrence of diabetic neuropathy. (AU)

Impact of sleep apnoea-hypopnoea syndrome on diabetic neuropathy. A systematic review. / Impacto del síndrome de apnea-hipopnea del sueño en la neuropatía diabética. Revisión sistemática.

INTRODUCTION: Diabetes mellitus and sleep apnoea-hypopnoea syndrome appear to be related, but it is not well defined whether there is an increased risk of peripheral neuropathy in patients with both diseases. For this reason, we conducted a systematic review. METHODS: Bibliographic search in 3 electronic databases using a predefined strategy and the PRISMA methodology. Only original studies (any type of design) published from 2000 onwards in English, French, Portuguese or Spanish were included. A study quality scale was established. RESULTS: Twelve articles were selected, of which six studied type 2 diabetic patients. The overall prevalence of sleep apnoea-hypopnoea syndrome was 43.7% (1,559/3,564 patients). Diabetic neuropathy was more frequent in patients with sleep apnoea-hypopnoea syndrome in nine studies, although significantly only in four (60% vs 27%, P<.001; 64.5% vs 36%, P=.03; 37% vs 23.4%, P<.02; 66.6% vs 0%, P=.007). In one study, diabetic neuropathy was more frequent in patients without sleep apnoea-hypopnoea syndrome (although not statistically significant) and in 2 no comparison was made between patients with/without sleep apnoea/hypopnoea syndrome. CONCLUSIONS: The observed results suggest a relationship between diabetes mellitus and sleep apnoea-hypopnoea syndrome in the occurrence of diabetic neuropathy.

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.

Development and validation of a clinical score to estimate progression to severe or critical state in COVID-19 pneumonia hospitalized patients.

The prognosis of a patient with COVID-19 pneumonia is uncertain. Our objective was to establish a predictive model of disease progression to facilitate early decision-making. A retrospective study was performed of patients admitted with COVID-19 pneumonia, classified as severe (admission to the intensive care unit, mechanic invasive ventilation, or death) or non-severe. A predictive model based on clinical, laboratory, and radiological parameters was built. The probability of progression to severe disease was estimated by logistic regression analysis. Calibration and discrimination (receiver operating characteristics curves and AUC) were assessed to determine model performance. During the study period 1152 patients presented with SARS-CoV-2 infection, of whom 229 (19.9%) were admitted for pneumonia. During hospitalization, 51 (22.3%) progressed to severe disease, of whom 26 required ICU care (11.4); 17 (7.4%) underwent invasive mechanical ventilation, and 32 (14%) died of any cause. Five predictors determined within 24 h of admission were identified: Diabetes, Age, Lymphocyte count, SaO2, and pH (DALSH score). The prediction model showed a good clinical performance, including discrimination (AUC 0.87 CI 0.81, 0.92) and calibration (Brier score = 0.11). In total, 0%, 12%, and 50% of patients with severity risk scores ≤ 5%, 6-25%, and > 25% exhibited disease progression, respectively. A risk score based on five factors predicts disease progression and facilitates early decision-making according to prognosis.

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

Advances in pleural effusion diagnostics.

Introduction: Pleural effusion is a common clinical problem. Yet, in a significant proportion of patients (~20%), the cause of pleural effusion remains unknown. Understanding the diagnostic value of pleural fluid tests is crucial for the development of accurate diagnostic models.Areas covered: This paper provides an overview of latest advances in the diagnosis of pleural effusion based on the best evidence available.Expert opinion: For pleural fluid tests to have a good diagnostic value, it is necessary that data obtained from clinical history, physical examination, and radiological studies are correctly interpreted. Thoracentesis and pleural biopsy should always be performed under image guidance to improve its diagnostic sensitivity and prevent complications. Nucleic acid amplification tests, pleural tissue cultures, and collection of pleural fluid in blood culture bottles improve the diagnostic yield of pleural fluid cultures. Although undiagnosed pleural effusions generally have a favorable prognosis, follow-up is recommended to prevent the development of a malignant pleural effusion.

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

¿Debe realizarse una toracocentesis para diagnosticar el derrame pleural de origen cardiaco? / Should thoracentesis be performed to diagnose pleural effusion of cardiac origin?

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Influenza A H1N1 Community-Acquired Pneumonia: Characteristics and Risk Factors-A Case-Control Study.

Introduction: Influenza A H1N1 community-acquired pneumonia (CAP) is a quite frequent respiratory disease. Despite being considered more serious than other CAPs, there are very few studies comparing its characteristics with noninfluenza CAP. We aim to establish the differences between pneumonia due to H1N1 virus and pneumonia not caused by H1N1 influenza virus and to determine the probability that a pneumonia is due to an H1N1 virus infection based on the most relevant variables. Methods: We used a case-control study where cases were H1N1 CAP patients with confirmed microbiological diagnosis and controls were patients with CAP admitted to hospital. H1N1 and other influenza types were discarded among controls. We calculated the probability of being a case or control using multivariate logistic regression. Results: We included 99 cases and 270 controls. Cases were younger than controls (53 vs 71 years, respectively). Mortality was much higher for H1N1 patients (13% vs 0.3%), and admission to intensive care unit was more frequent for H1N1 cases. The variables most associated with presenting H1N1 CAP were bilateral affectation on chest X-rays (OR: 5.70; 95% CI 2.69-10.40), followed by presence of arthromyalgias, with cases presenting close to three times more arthromyalgias compared to controls. Low leukocytes count and high AST values were also significantly associated with H1N1 CAP. H1N1 CAPs are characterized by bilateral affectation, low leukocyte count, presence of arthromyalgias, and high AST. Conclusions: A few and easy to obtain clinical parameters might be extremely useful to distinguish H1N1 CAP from CAPs of other origin.

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.

Tuberculosis y poliangitis microscópica. Una asociación muy poco frecuente / Tuberculosis and Microscopic Polyangiitis. A Rare Combination

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Pulmonary vasculitis.

Systemic vasculitides frequently affect the pulmonary vasculature. As the signs and symptoms of pulmonary vasculitis are variable and nonspecific, diagnosis and treatment represent a real challenge. Vasculitides should be given consideration, as these diseases present severe manifestations of rapidly progressing pulmonary disease. Examining other organs usually affected by vasculitides (e.g., the skin and kidneys) and determining autoantibody levels are essential to a better management of the disease. A radiological study would also contribute to establishing a diagnosis. The lungs are commonly involved in small-vessel vasculitis, anti-glomerular basement membrane disease, and vasculitides associated with antineutrophil cytoplasmic antibodies. Associated life-threatening diffuse alveolar haemorrhages and irreversible damage to other organs-usually the kidneys-are severe complications that require early diagnosis. Vasculitides are rare diseases that affect multiple organs. An increasing number of treatments-including biological agent-based therapies-requiring cooperation between specialists and centers have become available in the recent years. In the same way, clinicians should be familiar with the complications associated with immunosuppressive therapies.