Relación entre la apnea obstructiva del sueño y la diabetes mellitus tipo 2 / Relationship between obstructive sleep apnea and type 2 diabetes mellitus

Introducción: La asociación entre la apnea obstructiva del sueño (AOS) y el metabolismo de la glucosa sigue siendo controvertida. Este estudio investiga la relación entre la AOS y la diabetes mellitus tipo 2 (DM) y prediabetes (preDM) incidentes, así como el efecto del tratamiento con presión positiva continua en la vía aérea (CPAP) a largo plazo. Métodos: Estudio de seguimiento en cohorte retrospectiva clínica de pacientes con AOS y controles seleccionados de manera aleatoria. Los datos sobre DM incidente y preDM, así como de la CPAP se obtuvieron de los registros hospitalarios. La relación entre AOS basal y la DM incidente se examinó con modelos de regresión de Cox. Resultados: De un total de 356 pacientes, 169 con AOS y 187 controles fueron seguidos por una mediana de 98 meses; 47 enfermos (13,2%) desarrollaron DM y 43 (12,1%) preDM. La incidencia acumulada a los cinco años de DM fue de 10,7% (6,5-13,9%). De los sujetos con preDM en la muestra basal, 87% evolucionaron a DM incidente. Se demuestra que el índice de masa corporal (IMC), la hipoxia nocturna y el índice de apnea hipopnea (IAH) son factores de riesgo para el desarrollo de DM, y que la CPAP los disminuye. Conclusiones: Los pacientes con AOS tienen mayor probabilidad de desarrollar DM. Los factores de riesgo implicados son el IMC, la hipoxia nocturna y el IAH. El uso regular de CPAP a largo plazo se asoció con una disminución de estos. (AU)

Introduction: The association between obstructive sleep apnea (OSA) and glucose metabolism remains controversial. This study investigates the relationship between OSA and incident type 2 diabetes (DM) and prediabetes (preDM), as well as the effect of long-term CPAP (continuous positive airway pressure) treatment. Methods: Follow-up study in a retrospective clinical cohort of patients with OSA and randomly selected controls. Data on incident DM and preDM as well as CPAP were obtained from hospital records. The relationship between baseline OSA and incident DM was examined using COX regression models. Results: Three hundred and fifty-six patients, 169 with OSA and 187 controls were followed for a median of 98 months; 47 patients (13.2%) developed DM and 43 (12.1%) developed preDM. The 5-year cumulative incidence of DM was 10.7% (6.5–13.9%). 87% of subjects with preDM in the baseline sample progressed to incident DM. It is shown that body mass index (BMI), nocturnal hypoxia and apnea hypopnea index (AHI) are risk factors for the development of DM and that CPAP reduces this risk. Conclusions: Patients with OSA have a higher risk of developing DM. The risk factors involved are BMI, nocturnal hypoxia and AHI. Regular long-term CPAP use was associated with a decreased risk. (AU)

Relationship between obstructive sleep apnea and type 2 diabetes mellitus. / Relación entre la apnea obstructiva del sueño y la diabetes mellitus tipo 2.

INTRODUCTION: The association between obstructive sleep apnea (OSA) and glucose metabolism remains controversial. This study investigates the relationship between OSA and incident type 2 diabetes (DM) and prediabetes (preDM), as well as the effect of long-term CPAP (continuous positive airway pressure) treatment. METHODS: Follow-up study in a retrospective clinical cohort of patients with OSA and randomly selected controls. Data on incident DM and preDM as well as CPAP were obtained from hospital records. The relationship between baseline OSA and incident DM was examined using COX regression models. RESULTS: Three hundred and fifty-six patients, 169 with OSA and 187 controls were followed for a median of 98 months; 47 patients (13.2%) developed DM and 43 (12.1%) developed preDM. The 5-year cumulative incidence of DM was 10.7% (6.5-13.9%). 87% of subjects with preDM in the baseline sample progressed to incident DM. It is shown that body mass index (BMI), nocturnal hypoxia and apnea hypopnea index (AHI) are risk factors for the development of DM and that CPAP reduces this risk. CONCLUSIONS: Patients with OSA have a higher risk of developing DM. The risk factors involved are BMI, nocturnal hypoxia and AHI. Regular long-term CPAP use was associated with a decreased risk.

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)

Usefulness of a predictive model to hospitalize patients with low-risk community-acquired pneumonia.

INTRODUCTION: A high proportion of patients with low-risk community-acquired pneumonia (CAP) (classes I-III of the Pneumonia Severity Index) are hospitalized. The purpose of this study was to determine whether validated severity scales are used in clinical practice to make admission decisions, identify the variables that influence this decision, and evaluate the potential predictive value of these variables. MATERIALS AND METHODS: A prospective, observational study of patients ≥ 18 years of age with a diagnosis of low-risk CAP hospitalized or referred from the Emergency Department to outpatient consultations. A multivariate logistic regression predictive model was built to predict the decision to hospitalize a patient. RESULTS: The study population was composed of 1,208 patients (806 inpatients and 402 outpatients). The severity of CAP was estimated in 250 patients (20.7%). The factors that determined hospitalization were "abnormal findings in complementary studies" (643/806: 79.8%; due to respiratory failure in 443 patients) and "signs of clinical deterioration" [64/806 (7.9%): hypotension (16/64, 25%); hemoptoic expectoration (12/64, 18.8%); tachypnea (10/64, 15.6%)]. In total, ambulatory management was not contraindicated in 24.7% of hospitalized patients (199). The predictive model built to decide about hospitalization had a good power of discrimination (AUC 0.876; 95%CI: 0.855-0.897). CONCLUSIONS: Scales are rarely used to estimate the severity of CAP at the emergency department. The decision to hospitalize or not a patient largely depends on the clinical experience of the physician. Our predictive model showed a good power to discriminate the patients who required hospitalization. Further studies are warranted to validate these results.

[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.

Characteristics of pleural effusion due to amyloidosis.

The characteristics of patients with pleural amyloidosis (PA) are poorly known. A systematic review was performed of studies reporting clinical findings, pleural fluid (PF) characteristics, and the most effective treatment of PA. Case descriptions and retrospective studies were included. The review included 95 studies with a total sample of 196 patients. The mean age was 63 years, male/female ratio was 1.6:1, and 91.9% of patients were >50 years. The most common symptom was dyspnea (88 patients). PF was generally serious (63%), predominantly lymphocytic, and with the biochemical characteristics of transudates (43.4%) or exudates (42.6%). Pleural effusion was generally bilateral (55%) and <1/3 of the hemithorax (50%), although in 21% pleural effusion (PE) exceeded 2/3. Pleural biopsy was performed in 67 patients (yield: 83.6%; 56/67) and was positive in 54% of exudates and 62.5% of unilateral effusions. Of the 251 treatments prescribed, only 31 were effective (12.4%). The combination of chemotherapy and corticosteroids was effective in 29.6% of cases, whereas talc pleurodesis was effective in 21.4% and indwelling pleural catheter in 75% of patients (only four patients). PA is more frequent in adults from 50 years of age. PF is usually bilateral, serous, and indistinctly a transudate or exudate. A pleural biopsy can aid in diagnosis if effusion is unilateral or an exudate. Treatments are rarely effective and there may be definitive therapeutic options for PE in these patients.

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.

Pulmonary Manifestations of Primary Humoral Deficiencies.

Primary immunodeficiencies are a group of conditions characterized by developmental or functional alterations in the immune system caused by hereditary genetic defects. Primary immunodeficiencies may affect either the innate or the adaptive (humoral and cellular) immune system. Pulmonary complications in primary humoral deficiencies are frequent and varied and are associated with high morbidity and mortality rates. The types of complications include bronchiectasis secondary to recurrent respiratory infections and interstitial pulmonary involvement, which can be associated with autoimmune cytopenias, lymphoproliferation, and a range of immunological manifestations. Early detection is key to timely management. Immunoglobulin replacement therapy reduces the severity of disease, the frequency of exacerbations, and hospital admissions in some primary humoral deficiencies. Therefore, the presence of pulmonary disease with concomitant infectious and/or autoimmune complications should raise suspicion of primary humoral deficiencies and warrants a request for immunoglobulin determination in blood. Once diagnosis is confirmed; early immunoglobulin replacement therapy will improve the course of the disease. Further studies are needed to better understand the pathogenesis of pulmonary disease related to primary humoral deficiencies and favor the development of targeted therapies that improve the prognosis of patients.

Effect of high versus low dose of dexamethasone on clinical worsening in patients hospitalised with moderate or severe COVID-19 pneumonia: an open-label, randomised clinical trial.

BACKGROUND: Low-dose dexamethasone demonstrated clinical improvement in patients with coronavirus disease 2019 (COVID-19) needing oxygen therapy; however, evidence on the efficacy of high-dose dexamethasone is limited. METHODS: We performed a randomised, open-label, controlled trial involving hospitalised patients with confirmed COVID-19 pneumonia needing oxygen therapy. Patients were randomly assigned in a 1:1 ratio to receive low-dose dexamethasone (6 mg once daily for 10 days) or high-dose dexamethasone (20 mg once daily for 5 days, followed by 10 mg once daily for an additional 5 days). The primary outcome was clinical worsening within 11 days since randomisation. Secondary outcomes included 28-day mortality, time to recovery and clinical status at day 5, 11, 14 and 28 on an ordinal scale ranging from 1 (discharged) to 7 (death). RESULTS: A total of 200 patients (mean±sd age 64±14 years; 62% male) were enrolled. 32 (31.4%) out of 102 patients enrolled in the low-dose group and 16 (16.3%) out of 98 in the high-dose group showed clinical worsening within 11 days since randomisation (rate ratio 0.427, 95% CI 0.216-0.842; p=0.014). The 28-day mortality was 5.9% in the low-dose group and 6.1% in the high-dose group (p=0.844). There was no significant difference in time to recovery, and in the seven-point ordinal scale at days 5, 11, 14 and 28. CONCLUSIONS: Among hospitalised COVID-19 patients needing oxygen therapy, high dose of dexamethasone reduced clinical worsening within 11 days after randomisation, compared with low dose.

Evaluation of the impact of an integrated care pathway for pulmonary embolism: a quasi-experimental pre-post study.

BACKGROUND: An integrated care pathway (ICP) is intended to improve the management of prevalent resource-consuming, life-threatening diseases. The purpose of this study was to determine whether the quality of patient care improved with the establishment of a dedicated unit for pulmonary embolism (PE). METHODS: A quasi-experimental pre-post study (pre: years 2010-2013; post: 2015-2020; year 2014, "washing" period) of PE patients ≥18 years (January 2010-June 2020). The intervention involved the implementation of an ICP for PE. RESULTS: The sample was composed of 1,142 patients (510 pre-intervention and 612 post-intervention) without significant differences between the two populations. In the post-intervention period, significant reductions were observed in the median length of hospital stay (LOS) (8 vs. 6 days); time to start of oral anticoagulation therapy (4.5 vs. 3.5 days; P<0.001); and the percentage of patients with high-risk PE in whom recanalization was not contraindicated (66.7% vs. 96%; P=0.009). In-hospital and 30-day mortality decreased, although not significantly (4.5% vs. 2.8%; P=0.188; 6.1% vs. 5.2%; P=0.531, respectively). Multivariate logistic regression analysis showed that the median LOS intervention decreased significantly according to the service where patients were referred to, and with the use of the simplified PESI. During follow-up, lifelong anticoagulation was prescribed to a higher proportion of patients in the post-intervention period (30.7% vs. 69.3%; P<0.001). CONCLUSIONS: Although an ICP for PE does not reduce mortality significantly, it improves the quality of patient care.

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.

Impact of cardiovascular risk factors on the clinical presentation and survival of pulmonary embolism without identifiable risk factor.

BACKGROUND: The nature of pulmonary embolism (PE) without identifiable risk factor (IRF) remains unclear. The objective of this study is to investigate the potential relationship between cardiovascular risk factors (CVRFs) and PE without IRF (unprovoked) and assess their role as markers of disease severity and prognosis. METHODS: A case-control study was performed of patients with PE admitted to our hospital [2010-2019]. Subjects with PE without IRF were included in the cohort of cases, whereas patients with PE with IRF were allocated to the control group. Variables of interest included age, active smoking, obesity, and diagnosis of arterial hypertension, dyslipidemia or diabetes mellitus. RESULTS: A total of 1,166 patients were included in the study, of whom 64.2% had PE without IRF. The risk for PE without IRF increased with age [odds ratio (OR): 2.68; 95% confidence interval (CI): 1.95-3.68], arterial hypertension (OR: 1.63; 95% CI: 1.27-2.07), and dyslipidemia (OR: 1.63; 95% CI: 1.24-2.15). The risk for PE without IRF was higher as the number of CVRF increased, being 3.99 (95% CI: 2.02-7.90) for subjects with ≥3 CVRF. The percentage of high-risk unprovoked PE increased significantly as the number of CVRF rose [0.6% for no CVRF; 23.8% for a CRF, P<0.001 (OR: 9.92; 95% CI: 2.82-34.9); 37.5% for two CRFs, P<0.001 (OR: 14.8; 95% CI: 4.25-51.85); and 38.1% for ≥3, P<0.001 (OR: 14.1; 95% CI: 4.06-49.4)]. No significant differences were observed in 1-month survival between cases and controls, whereas differences in 24-month survival reached significance. CONCLUSIONS: A relationship was observed between CVRF and PE without IRF, as the risk for unprovoked PE increased with the number of CVRF. In addition, the number of CVRF was associated with PE without IRF severity, but not with prognosis.

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