Impact of outdoor air pollution on severity and mortality in COVID-19 pneumonia.

The relationship between exposure to air pollution and the severity of coronavirus disease 2019 (COVID-19) pneumonia and other outcomes is poorly understood. Beyond age and comorbidity, risk factors for adverse outcomes including death have been poorly studied. The main objective of our study was to examine the relationship between exposure to outdoor air pollution and the risk of death in patients with COVID-19 pneumonia using individual-level data. The secondary objective was to investigate the impact of air pollutants on gas exchange and systemic inflammation in this disease. This cohort study included 1548 patients hospitalised for COVID-19 pneumonia between February and May 2020 in one of four hospitals. Local agencies supplied daily data on environmental air pollutants (PM10, PM2.5, O3, NO2, NO and NOX) and meteorological conditions (temperature and humidity) in the year before hospital admission (from January 2019 to December 2019). Daily exposure to pollution and meteorological conditions by individual postcode of residence was estimated using geospatial Bayesian generalised additive models. The influence of air pollution on pneumonia severity was studied using generalised additive models which included: age, sex, Charlson comorbidity index, hospital, average income, air temperature and humidity, and exposure to each pollutant. Additionally, generalised additive models were generated for exploring the effect of air pollution on C-reactive protein (CRP) level and SpO2/FiO2 at admission. According to our results, both risk of COVID-19 death and CRP level increased significantly with median exposure to PM10, NO2, NO and NOX, while higher exposure to NO2, NO and NOX was associated with lower SpO2/FiO2 ratios. In conclusion, after controlling for socioeconomic, demographic and health-related variables, we found evidence of a significant positive relationship between air pollution and mortality in patients hospitalised for COVID-19 pneumonia. Additionally, inflammation (CRP) and gas exchange (SpO2/FiO2) in these patients were significantly related to exposure to air pollution.

Factores de riesgo de deterioro clínico en pacientes ingresados por COVID-19: estudio caso-control / Risk factors for clinical deterioration in patients admitted for COVID-19: A case-control study

Introducción: Existe controversia sobre los mejores factores predictores de deterioro clínico en la COVID-19. Objetivo: Identificar factores predictores de riesgo de deterioro en pacientes hospitalizados por COVID-19. Métodos Diseño: caso-control anidado dentro de una cohorte. Ámbito: 13 centros de agudos de Osakidetza-Servicio Vasco de Salud. Participantes: se consideró casos a pacientes hospitalizados por COVID-19 con deterioro clínico, definido como la aparición de síndrome de distrés respiratorio del adulto grave, ingreso en UCI o fallecimiento. Se emparejaron 2controles por caso en función de la edad. Se recogieron variables sociodemográficas, comorbilidades, tratamientos basales, síntomas y fecha de inicio, consultas previas, así como variables clínicas, analíticas y radiológicas. Se creó un modelo explicativo del deterioro clínico mediante regresión logística condicional. Resultados: Se incluyeron 99 casos y 198 controles. Mediante análisis de regresión logística las variables independientes asociadas con deterioro clínico fueron: saturación de O2 en Urgencias ≤ 90% (OR=16,6, IC del 95%, 4-68), radiografía de tórax patológica (OR=5,6, IC del 95%, 1,7-18,4), PCR> 100mg/dL (OR=3,62, IC del 95% 1,62-8) y trombocitopenia <150.000 plaquetas (OR=4, IC del 95%, 1,84-8,6) y, entre los antecedentes, haber padecido infarto agudo de miocardio (OR=15,7, IC del 95%, 3,29-75,09), EPOC (OR=3,05, IC del 95%, 1,43-6,5) o hipertensión arterial (OR=2,21, IC del 95%1,11-4,4). El área bajo la curva alcanzado por el modelo fue 0,86. En el análisis univariado, se asociaron con mejor evolución clínica el sexo femenino, la presencia de tos seca y dolor de garganta, pero no resultaron significativas en el análisis multivariado. Conclusiós:Las variables identificadas podrían ser de utilidad en la práctica clínica para la detección de pacientes con alto riesgo de mala evolución (AU)

Introduction: There is controversy regarding the best predictors of clinical deterioration in COVID-19. Objective: This work aims to identify predictors of risk factors for deterioration in patients hospitalized due to COVID-19. Methods Design: Nested case-control study within a cohort. Setting: 13 acute care centers of the Osakidetza-Basque Health Service. Participants: Patients hospitalized for COVID-19 with clinical deterioration—defined as onset of severe ARDS, ICU admission, or death—were considered cases. Two controls were matched to each case based on age. Sociodemographic data; comorbidities; baseline treatment; symptoms; date of onset; previous consultations; and clinical, analytical, and radiological variables were collected. An explanatory model of clinical deterioration was created by means of conditional logistic regression. Results: A total of 99 cases and 198 controls were included. According to the logistic regression analysis, the independent variables associated with clinical deterioration were: emergency department O2 saturation ≤90% (OR 16.6; 95%CI 4-68), pathological chest X-ray (OR 5.6; 95%CI 1.7-18.4), CRP>100mg/dL (OR 3.62; 95%CI 1.62-8), thrombocytopenia with <150,000 platelets (OR 4; 95%CI 1.84-8.6); and a medical history of acute myocardial infarction (OR 15.7; 95%CI, 3.29-75.09), COPD (OR 3.05; 95%CI 1.43-6.5), or HT (OR 2.21; 95%CI 1.11-4.4). The model's AUC was 0.86. On the univariate analysis, female sex and presence of dry cough and sore throat were associated with better clinical progress, but were not found to be significant on the multivariate analysis. Conclusion: The variables identified could be useful in clinical practice for the detection of patients at high risk of poor outcomes (AU)

Risk factors for clinical deterioration in patients admitted for COVID-19: A case-control study.

INTRODUCTION: There is controversy regarding the best predictors of clinical deterioration in COVID-19. OBJECTIVE: This work aims to identify predictors of risk factors for deterioration in patients hospitalized due to COVID-19. METHODS DESIGN: Nested case-control study within a cohort. SETTING: 13 acute care centers of the Osakidetza-Basque Health Service. PARTICIPANTS: patients hospitalized for COVID-19 with clinical deterioration-defined as onset of severe ARDS, ICU admission, or death-were considered cases. Two controls were matched to each case based on age. Sociodemographic data; comorbidities; baseline treatment; symptoms; date of onset; previous consultations; and clinical, analytical, and radiological variables were collected. An explanatory model of clinical deterioration was created by means of conditional logistic regression. RESULTS: A total of 99 cases and 198 controls were included. According to the logistic regression analysis, the independent variables associated with clinical deterioration were: emergency department O2 saturation ≤90% (OR 16.6; 95%CI 4-68), pathological chest X-ray (OR 5.6; 95%CI 1.7-18.4), CRP > 100 mg/dL (OR 3.62; 95%CI 1.62-8), thrombocytopenia with <150,000 platelets (OR 4; 95%CI 1.84-8.6); and a medical history of acute myocardial infarction (OR 15.7; 95%CI, 3.29-75.09), COPD (OR 3.05; 95%CI 1.43-6.5), or HT (OR 2.21; 95%CI 1.11-4.4). The model's AUC was 0.86. On the univariate analysis, female sex and presence of dry cough and sore throat were associated with better clinical progress, but were not found to be significant on the multivariate analysis. CONCLUSION: The variables identified could be useful in clinical practice for the detection of patients at high risk of poor outcomes.

[Risk factors for clinical deterioration in patients admitted for COVID-19: A case-control study]. / Factores de riesgo de deterioro clínico en pacientes ingresados por COVID-19: estudio caso-control.

INTRODUCTION: There is controversy regarding the best predictors of clinical deterioration in COVID-19. OBJECTIVE: This work aims to identify predictors of risk factors for deterioration in patients hospitalized due to COVID-19. METHODS DESIGN: Nested case-control study within a cohort. Setting: 13 acute care centers of the Osakidetza-Basque Health Service. Participants: Patients hospitalized for COVID-19 with clinical deterioration-defined as onset of severe ARDS, ICU admission, or death-were considered cases. Two controls were matched to each case based on age. Sociodemographic data; comorbidities; baseline treatment; symptoms; date of onset; previous consultations; and clinical, analytical, and radiological variables were collected. An explanatory model of clinical deterioration was created by means of conditional logistic regression. RESULTS: A total of 99 cases and 198 controls were included. According to the logistic regression analysis, the independent variables associated with clinical deterioration were: emergency department O2 saturation ≤90% (OR 16.6; 95%CI 4-68), pathological chest X-ray (OR 5.6; 95%CI 1.7-18.4), CRP >100 mg/dL (OR 3.62; 95%CI 1.62-8), thrombocytopenia with < 150,000 platelets (OR 4; 95%CI 1.84-8.6); and a medical history of acute myocardial infarction (OR 15.7; 95%CI, 3.29-75.09), COPD (OR 3.05; 95%CI 1.43-6.5), or HT (OR 2.21; 95%CI 1.11-4.4). The model's AUC was 0.86. On the univariate analysis, female sex and presence of dry cough and sore throat were associated with better clinical progress, but were not found to be significant on the multivariate analysis. CONCLUSION: The variables identified could be useful in clinical practice for the detection of patients at high risk of poor outcomes.

Utility of two biomarkers for directing care among patients with non-severe community-acquired pneumonia.

The aim of the present study is to evaluate the usefulness of two biomarkers-procalcitonin (PCT) and C-reactive protein (CRP)-in addition to the CURB-65 score for assessing the site of care and the etiology of non-severe community-acquired pneumonia (CAP). We conducted a prospective observational study from April 1, 2006, to June 30, 2007, in a single teaching hospital in northern Spain among patients with non-severe CAP. In addition to collecting data needed to determine the CURB-65 score, microbial cultures were taken and levels of PCT and CRP were measured. We compared the prognostic accuracy of these biomarkers with the CURB-65 score to predict hospitalization and microbial etiology using receiver operating characteristic (ROC) curves. A total of 344 patients with non-severe CAP were enrolled; 73 were admitted to the hospital and 271 were treated on an outpatient basis. An etiologic diagnostic was made for 44 %, with atypical pathogens predominating. Levels of PCT and CRP increased with increasing CURB-65 scores. Patients admitted to the hospital had higher PCT and CRP levels than outpatients (p < 0.001). For predicting hospitalization, PCT had a better area under the ROC curve (AUC) (0.81) than the CURB-65 score alone (0.77). For PCT plus the CURB-65 score, the AUC increased significantly from 0.77 to 0.83. In patients with bacterial CAP, the biomarker levels were significantly higher than among patients with atypical or viral etiology (p < 0.001). PCT with a cut-off point of 0.15 ng/mL was the best predictor for bacterial etiology and for select patients eligible for outpatient care. In conclusion, levels of PCT and CRP positively correlate with increasing severity of CAP and may have a role in predicting both patients who can safely receive outpatient care and the microbial etiology in patients with low CURB-65 scores.

Score to identify the severity of adult patients with influenza A (H1N1) 2009 virus infection at hospital admission.

The objective of this paper was to develop a prognostic index for severe complications among hospitalized patients with influenza A (H1N1) 2009 virus infection. We conducted a prospective observational cohort study of 618 inpatients with 2009 H1N1 virus infection admitted to 36 Spanish hospitals between July 2009 and February 2010. Risk factors evaluated included host-related factors and clinical data at admission. We developed a composite index of severe in-hospital complications (SIHC), which included: mortality, mechanical ventilation, septic shock, acute respiratory distress syndrome, and requirement for resuscitation maneuvers. Six factors were independently associated with SIHC: age >45 years, male sex, number of comorbidities, pneumonia, dyspnea, and confusion. From the ß parameter obtained in the multivariate model, a weight was assigned to each factor to compute the individual influenza risk score. The score shows an area under the receiver operating characteristic (ROC) curve of 0.77. The SIHC rate was 1.9 % in the low-risk group, 10.3 % in the intermediate-risk group, and 29.6 % in the high-risk group. The odds ratio for complications was 21.8 for the high-risk group compared with the low-risk group. This easy-to-score influenza A (H1N1) 2009 virus infection risk index accurately stratifies patients hospitalized for H1N1 virus infection into low-, intermediate-, and high-risk groups for SIHC.

The health, activity, dyspnea, obstruction, age, and hospitalization: prognostic score for stable COPD patients.

UNLABELLED: Multidimensional instruments for determining the severity and prognosis of chronic obstructive pulmonary disease (COPD) must be used in daily clinical practice. OBJECTIVE: To develop and validate a new COPD severity score using variables readily obtained in clinical practice and to compare its predictive capacity with that of other multidimensional indexes. Data collected from a prospective cohort of 611 stable COPD patients were used to derive a clinical prediction rule that was later validated in a separate prospective cohort of 348 patients. In the multivariate analyses, six independent predictive factors were correlated with overall and respiratory mortality: health status, physical activity, dyspnea, airway obstruction (FEV(1)), age, and hospitalizations for COPD exacerbations in the previous two years. These create the HADO-AH score. Based on the ß parameter obtained in the multivariate model, a score was assigned to each predictive variable. The area under the curve for 5-year mortality was 0.79 (95% CI, 0.74-0.83) in the derivation cohort and 0.76 (95% CI, 0.71-0.81) in the validation cohort. The HADO-AH score was a significantly better predictor of mortality than the HADO-score and the Body-mass index, Obstruction, Dyspnea, Exercise-index were statistically significant (p < 0.0004 and p = 0.021, respectively), but was similar to the Age, Dyspnea, and Obstruction-index (p = 0.345). The HADO-AH score provides estimates of all-cause and respiratory mortality that are equal to, or better than, those of other multidimensional instruments. Because it uses only easily accessible measures, it could be useful at all levels of care.

Development of a prognostic index for 90-day mortality in patients discharged after admission to hospital for community-acquired pneumonia.

BACKGROUND: Although patients admitted to hospital for community-acquired pneumonia (CAP) experience substantial short-term mortality following hospital discharge, few studies have focused on identifying factors that predict mortality after admission to hospital in this population. The objective of this study was to develop and validate a prognostic index for 90-day mortality after hospital discharge among patients with CAP. METHODS: The prognostic index was derived in 1117 adult patients discharged between 2003 and 2007 from a general hospital following admission for CAP. It was validated in 646 consecutive patients with CAP discharged from three other hospitals between 1 November 2005 and 31 July 2006. Risk factors evaluated included host-related factors, severity upon admission, in-hospital management and bacteriology. RESULTS: In the derivation cohort, three factors were independently associated with 90-day mortality: pre-illness functional status, Charlson index (composite measure of co-morbid illnesses) and severity on admission. Mortality at 90 days was 0.7% in the low-risk group, 3.5% in the intermediate-risk group and 17.2% in the high-risk group. In the validation cohort, 90-day mortality in the three groups was 0.6%, 3.9% and 19.6%, respectively. Compared with the low-risk group, the odds ratio for mortality was 43.5 for the high-risk group. The risk categories showed an area under the receiver operating characteristic curve of 0.79 in the derivation cohort and 0.82 in the validation cohort. CONCLUSIONS: The prognostic index accurately stratifies patients admitted to hospital for CAP into low-, intermediate- and high-risk groups for 90-day mortality on discharge. The use of this index could help clinicians improve outcomes in this vulnerable population by targeting specific interventions to each group.

Validation of a predictive rule for the management of community-acquired pneumonia.

The CURB-65 score (Confusion, Urea > 7 mmol x L(-1), Respiratory rate > or = 30 x min(-1), low Blood pressure, and age > or = 65 yrs) has been proposed as a tool for augmenting clinical judgement for stratifying patients with community-acquired pneumonia (CAP) into different management groups. The six-point CURB-65 score was retrospectively applied in a prospective, consecutive cohort of adult patients with a diagnosis of CAP seen in the emergency department of a 400-bed teaching hospital from March 1, 2000 to February 29, 2004. A total of 1,100 inpatients and 676 outpatients were included. The 30-day mortality rate in the entire cohort increased directly with increasing CURB-65 score: 0, 1.1, 7.6, 21, 41.9 and 60% for CURB-65 scores of 0, 1, 2, 3, 4, and 5, respectively. The score was also significantly associated with the need for mechanical ventilation and rate of hospital admission in the entire cohort, and with duration of hospital stay among inpatients. The CURB-65 score (Confusion, Urea > 7 mmol x L(-1), Respiratory rate > or = 30 x min(-1), low Blood pressure, and age > or = 65 yrs), and a simpler CRB-65 score that omits the blood urea measurement, helps classify patients with community-acquired pneumonia into different groups according to the mortality risk and significantly correlates with community-acquired pneumonia management key points. The new score can also be used as a severity adjustment measure.

[Patients hospitalized with community-acquired pneumonia: a comparative study of outcomes by medical specialty area]. / Pacientes ingresados por neumonía adquirida en la comunidad: estudio comparativo en función de la especialidad del servicio médico responsable.

OBJECTIVE: Variability in the management of patients hospitalized with community-acquired pneumonia (CAP) is attributable to many factors. The objective of this study was to determine whether such variability is influenced by the medical specialty area where the patient is treated. PATIENTS AND METHODS: The treatment and outcomes for a random sample of patients with CAP admitted to 4 hospitals over 2 periods (1 year starting March 1, 1998, and 1.5 years starting March 1, 2000) were compared by medical specialty department. Multiple linear and logistic regression models were used to analyze differences. RESULTS: Differences were found between departments in the coverage of atypical pathogens (P<.001). The adjusted mean length of stay in hospital varied between 6.8 and 9.1 days (P<.01), and the duration of intravenous treatment varied between 4.6 and 7.3 days (P<.05). Adjusted models showed that mortality in hospital and at 30 days was significantly higher for patients treated in internal medicine departments (odds ratios, 2.1 and 2, respectively) than for those treated in pulmonology departments. CONCLUSIONS: Interdepartmental differences were observed in how patients hospitalized with CAP were treated and in the outcomes achieved. This variation is probably influenced by the differences that were found in the use of antibiotics.

A prediction rule to identify allocation of inpatient care in community-acquired pneumonia.

The current authors developed a new prediction rule based on the five risk classes defined by the Pneumonia Severity Index to identify allocation of inpatient care in community-acquired pneumonia. The decision to hospitalise in low-risk classes (I-III) was unquestionable, if the presence of one or more of the following were evident: arterial oxygen tension <8.0 kPa (60 mmHg), shock, decompensated coexisting illnesses, pleural effusion, inability to maintain oral intake, social problem, and lack of response to previous adequate empirical antibiotic therapy. The results at 18 months after implementation of this new prediction rule are reported in a series of 616 patients. The mortality rate was 0.5% in 221 patients treated as outpatients versus 8.9% in 395 patients treated as inpatients. Specific additional criteria for hospitalisation included in the prediction rule were present in 106 of the 178 low-risk patients treated as inpatients, whereas in the remaining 72, the decision to hospitalise was apparently unjustified by the prediction rule. These 72 patients showed a better outcome (significantly shorter hospitalisation, days on intravenous antibiotics, mortality, and complicated course) than high-risk patients and low-risk patients who met the additional specific criteria for deciding hospital admission. Therefore, admission in these low-risk patients might have been avoided by strict adherence to the new prediction rule. Another relevant finding was that the Pneumonia Severity Index alone did not identify all patients who needed to be admitted to the hospital.

Usefulness of a national registry of alpha-1-antitrypsin deficiency. The Spanish experience.

Severe alpha-1-antitrypsin (AAT) deficiency, phenotype Pi ZZ, is a rare condition with an estimated prevalence of 1/4500 individuals in Spain. Given this low prevalence, it seems useful to accumulate all the information derived from the care of these patients. In this context, the Spanish Registry of patients with AAT deficiency was founded in 1993; its main objectives were to establish guidelines adapted to our country for the treatment and management of AAT-deficient patients, offer expert support to physicians all over the country treating these patients, and provide technical support on the determination of Pi phenotyping and genotyping of individuals suspected of being AAT-deficient. From 1993 to January 1998 the number of enrollees increased from 48 to 223, of which 216 were Pi ZZ. Seventy-three per cent were male and only 31.5% were never smokers, mean age was 46 years (SD = 13 years) and mean FEV1 53% predicted (SD = 31%). 83% were index cases who, compared with non-index cases, were older (49 +/- 11 vs. 35 +/- 13 years, P < 0.001), more likely to have a smoking history (85% vs. 47%, P < 0.01) and displayed more severe impairment in pulmonary function (FEV1% = 40% +/- 19% vs. 96% +/- 23%, P < 0.001). Augmentation therapy was administered to 129 patients (58%). Treated patients had more severe impairment in pulmonary function than the untreated (FEV1% = 40% +/- 21% vs. 72% +/- 32%, P < 0.001) and were more likely to be index cases (81% vs. 43%, P < 0.001). Characteristics of the patients included are similar to those described for other Registries. The Registry has extended knowledge of the disease throughout the country and has established local guidelines for treatment and follow-up. It may be a valid database for future co-operation in international initiatives.