Association of obesity on the outcome of critically ill patients affected by COVID-19 / Asociación de la obesidad en la evolución de los pacientes críticos afectados por COVID-19

Objective To evaluate the impact of obesity on ICU mortality. Design Observational, retrospective, multicentre study. Setting Intensive Care Unit (ICU). Patients Adults patients admitted with COVID-19 and respiratory failure. Interventions None. Primary variables of interest Collected data included demographic and clinical characteristics, comorbidities, laboratory tests and ICU outcomes. Body mass index (BMI) impact on ICU mortality was studied as (1) a continuous variable, (2) a categorical variable obesity/non-obesity, and (3) as categories defined a priori: underweight, normal, overweight, obesity and Class III obesity. The impact of obesity on mortality was assessed by multiple logistic regression and Smooth Restricted cubic (SRC) splines for Cox hazard regression. Results 5,206 patients were included, 20 patients (0.4%) as underweight, 887(17.0%) as normal, 2390(46%) as overweight, 1672(32.1) as obese and 237(4.5%) as class III obesity. The obesity group patients (n = 1909) were younger (61 vs. 65 years, p < 0.001) and with lower severity scores APACHE II (13 [9–17] vs. 13[10−17, p < 0.01) than non-obese. Overall ICU mortality was 28.5% and not different for obese (28.9%) or non-obese (28.3%, p = 0.65). Only Class III obesity (OR = 2.19, 95%CI 1.44–3.34) was associated with ICU mortality in the multivariate and SRC analysis. Conclusions COVID-19 patients with a BMI > 40 are at high risk of poor outcomes in the ICU. An effective vaccination schedule and prolonged social distancing should be recommended. (AU)

Objetivo Evaluar el impacto de la obesidad en la mortalidad de la UCI. Diseño Estudio observacional, retrospectivo y multicéntrico. Ámbito Unidad de Cuidados Intensivos (UCI). Pacientes Pacientes adultos con COVID-19 e insuficiencia respiratoria. Intervenciones Ninguna. Variables de interés principales Características demográficas y clínicas, comorbilidades, pruebas de laboratorio y evolución en la UCI. El impacto del índice de masa corporal (IMC) sobre la mortalidad se estudió como (1) una variable continua, (2) una variable categórica obesidad/no obesidad, y (3) como categorías definidas a priori: bajo peso, normal, sobrepeso, obesidad y obesidad clase III. El impacto de la obesidad se evaluó mediante regresión logística múltiple y splines cúbicos suaves restringidos (SRC) para la regresión de riesgos de Cox. Resultados Se incluyeron 5.206 pacientes, 20 (0,4%) con bajo peso, 887 (17,0%) con peso normal, 2.390 (46%) con sobrepeso, 1.672 (32,1%) con obesidad y 237 (4,5%) con obesidad clase III. Los pacientes obesos (n = 1909) eran más jóvenes (61 vs. 65 años, p < 0,001) y con un nivel más bajo de APACHE II (13 [9–17] frente a 13[10−17, p < 0,01) que los no obesos. La mortalidad global en la UCI fue del 28,5% y no fue diferente entre obesos (28,9%) y no obesos (28,3%,p = 0,65). Sólo la obesidad clase III (OR = 2,19; IC del 95%: 1,44−3,34) se asoció con la mortalidad en la UCI en el análisis multivariante y SRC. Conclusiones Los pacientes con COVID-19 con un IMC > 40 tienen un alto riesgo de mala evolución en la UCI. Debe recomendarse un calendario de vacunación eficaz y un distanciamiento social prolongado. (AU)

Association of obesity on the outcome of critically ill patients affected by COVID-19.

OBJECTIVE: To evaluate the impact of obesity on ICU mortality. DESIGN: Observational, retrospective, multicentre study. SETTING: Intensive Care Unit (ICU). PATIENTS: Adults patients admitted with COVID-19 and respiratory failure. INTERVENTIONS: None. PRIMARY VARIABLES OF INTEREST: Collected data included demographic and clinical characteristics, comorbidities, laboratory tests and ICU outcomes. Body mass index (BMI) impact on ICU mortality was studied as (1) a continuous variable, (2) a categorical variable obesity/non-obesity, and (3) as categories defined a priori: underweight, normal, overweight, obesity and Class III obesity. The impact of obesity on mortality was assessed by multiple logistic regression and Smooth Restricted cubic (SRC) splines for Cox hazard regression. RESULTS: 5,206 patients were included, 20 patients (0.4%) as underweight, 887(17.0%) as normal, 2390(46%) as overweight, 1672(32.1) as obese and 237(4.5%) as class III obesity. The obesity group patients (n = 1909) were younger (61 vs. 65 years, p < 0.001) and with lower severity scores APACHE II (13 [9-17] vs. 13[10-17, p < 0.01) than non-obese. Overall ICU mortality was 28.5% and not different for obese (28.9%) or non-obese (28.3%, p = 0.65). Only Class III obesity (OR = 2.19, 95%CI 1.44-3.34) was associated with ICU mortality in the multivariate and SRC analysis. CONCLUSIONS: COVID-19 patients with a BMI > 40 are at high risk of poor outcomes in the ICU. An effective vaccination schedule and prolonged social distancing should be recommended.

Effectiveness of prolonged versus standard-course of oseltamivir in critically ill patients with severe influenza infection: A multicentre cohort study.

The aim of this study is to investigate the effectiveness of prolonged versus standard course oseltamivir treatment among critically ill patients with severe influenza. A retrospective study of a prospectively collected database including adults with influenza infection admitted to 184 intensive care units (ICUs) in Spain from 2009 to 2018. Prolonged oseltamivir was defined if patients received the treatment beyond 5 days, whereas the standard-course group received oseltamivir for 5 days. The primary outcome was all-cause ICU mortality. Propensity score matching (PSM) was constructed, and the outcome was investigated through Cox regression and RCSs. Two thousand three hundred and ninety-seven subjects were included, of whom 1943 (81.1%) received prolonged oseltamivir and 454 (18.9%) received standard treatment. An optimal full matching algorithm was performed by matching 2171 patients, 1750 treated in the prolonged oseltamivir group and 421 controls in the standard oseltamivir group. After PSM, 387 (22.1%) patients in the prolonged oseltamivir and 119 (28.3%) patients in the standard group died (p = 0.009). After adjusting confounding factors, prolonged oseltamivir significantly reduced ICU mortality (odds ratio [OR]: 0.53, 95% confidence interval [CI]: 0.40-0.69). Prolonged oseltamivir may have protective effects on survival at Day 10 compared with a standard treatment course. Sensitivity analysis confirmed these findings. Compared with standard treatment, prolonged oseltamivir was associated with reduced ICU mortality in critically ill patients with severe influenza. Clinicians should consider extending the oseltamivir treatment duration to 10 days, particularly in higher-risk groups of prolonged viral shedding. Further randomized controlled trials are warranted to confirm these findings.

Impact of macrolide treatment on long-term mortality in patients admitted to the ICU due to CAP: a targeted maximum likelihood estimation and survival analysis.

INTRODUCTION: Patients with community-acquired pneumonia (CAP) admitted to the intensive care unit (ICU) have high mortality rates during the acute infection and up to ten years thereafter. Recommendations from international CAP guidelines include macrolide-based treatment. However, there is no data on the long-term outcomes of this recommendation. Therefore, we aimed to determine the impact of macrolide-based therapy on long-term mortality in this population. METHODS: Registered patients in the MIMIC-IV database 16 years or older and admitted to the ICU due to CAP were included. Multivariate analysis, targeted maximum likelihood estimation (TMLE) to simulate a randomised controlled trial, and survival analyses were conducted to test the effect of macrolide-based treatment on mortality six-month (6 m) and twelve-month (12 m) after hospital admission. A sensitivity analysis was performed excluding patients with Pseudomonas aeruginosa or MRSA pneumonia to control for Healthcare-Associated Pneumonia (HCAP). RESULTS: 3775 patients were included, and 1154 were treated with a macrolide-based treatment. The non-macrolide-based group had worse long-term clinical outcomes, represented by 6 m [31.5 (363/1154) vs 39.5 (1035/2621), p < 0.001] and 12 m mortality [39.0 (450/1154) vs 45.7 (1198/2621), p < 0.001]. The main risk factors associated with long-term mortality were Charlson comorbidity index, SAPS II, septic shock, and respiratory failure. Macrolide-based treatment reduced the risk of dying at 6 m [HR (95% CI) 0.69 (0.60, 0.78), p < 0.001] and 12 m [0.72 (0.64, 0.81), p < 0.001]. After TMLE, the protective effect continued with an additive effect estimate of - 0.069. CONCLUSION: Macrolide-based treatment reduced the hazard risk of long-term mortality by almost one-third. This effect remains after simulating an RCT with TMLE and the sensitivity analysis for the HCAP classification.

Risk factors for developing ventilator-associated lower respiratory tract infection in patients with severe COVID-19: a multinational, multicentre study, prospective, observational study.

Around one-third of patients diagnosed with COVID-19 develop a severe illness that requires admission to the Intensive Care Unit (ICU). In clinical practice, clinicians have learned that patients admitted to the ICU due to severe COVID-19 frequently develop ventilator-associated lower respiratory tract infections (VA-LRTI). This study aims to describe the clinical characteristics, the factors associated with VA-LRTI, and its impact on clinical outcomes in patients with severe COVID-19. This was a multicentre, observational cohort study conducted in ten countries in Latin America and Europe. We included patients with confirmed rtPCR for SARS-CoV-2 requiring ICU admission and endotracheal intubation. Only patients with a microbiological and clinical diagnosis of VA-LRTI were included. Multivariate Logistic regression analyses and Random Forest were conducted to determine the risk factors for VA-LRTI and its clinical impact in patients with severe COVID-19. In our study cohort of 3287 patients, VA-LRTI was diagnosed in 28.8% [948/3287]. The cumulative incidence of ventilator-associated pneumonia (VAP) was 18.6% [610/3287], followed by ventilator-associated tracheobronchitis (VAT) 10.3% [338/3287]. A total of 1252 bacteria species were isolated. The most frequently isolated pathogens were Pseudomonas aeruginosa (21.2% [266/1252]), followed by Klebsiella pneumoniae (19.1% [239/1252]) and Staphylococcus aureus (15.5% [194/1,252]). The factors independently associated with the development of VA-LRTI were prolonged stay under invasive mechanical ventilation, AKI during ICU stay, and the number of comorbidities. Regarding the clinical impact of VA-LRTI, patients with VAP had an increased risk of hospital mortality (OR [95% CI] of 1.81 [1.40-2.34]), while VAT was not associated with increased hospital mortality (OR [95% CI] of 1.34 [0.98-1.83]). VA-LRTI, often with difficult-to-treat bacteria, is frequent in patients admitted to the ICU due to severe COVID-19 and is associated with worse clinical outcomes, including higher mortality. Identifying risk factors for VA-LRTI might allow the early patient diagnosis to improve clinical outcomes.Trial registration: This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.

The Role of Biomarkers in Influenza and COVID-19 Community-Acquired Pneumonia in Adults.

Pneumonia is a growing problem worldwide and remains an important cause of morbidity, hospitalizations, intensive care unit admission and mortality. Viruses are the causative agents in almost a fourth of cases of community-acquired pneumonia (CAP) in adults, with an important representation of influenza virus and SARS-CoV-2 pneumonia. Moreover, mixed viral and bacterial pneumonia is common and a risk factor for severity of disease. It is critical for clinicians the early identification of the pathogen causing infection to avoid inappropriate antibiotics, as well as to predict clinical outcomes. It has been extensively reported that biomarkers could be useful for these purposes. This review describe current evidence and provide recommendations about the use of biomarkers in influenza and SARS-CoV-2 pneumonia, focusing mainly on procalcitonin (PCT) and C-reactive protein (CRP). Evidence was based on a qualitative analysis of the available scientific literature (meta-analyses, randomized controlled trials, observational studies and clinical guidelines). Both PCT and CRP levels provide valuable information about the prognosis of influenza and SARS-CoV-2 pneumonia. Additionally, PCT levels, considered along with other clinical, radiological and laboratory data, are useful for early diagnosis of mixed viral and bacterial CAP, allowing the proper management of the disease and adequate antibiotics prescription. The authors propose a practical PCT algorithm for clinical decision-making to guide antibiotic initiation in cases of influenza and SARS-CoV-2 pneumonia. Further well-design studies are needed to validate PCT algorithm among these patients and to confirm whether other biomarkers are indeed useful as diagnostic or prognostic tools in viral pneumonia.

Negative predictive value of procalcitonin to rule out bacterial respiratory co-infection in critical covid-19 patients.

BACKGROUND: Procalcitonin (PCT) and C-Reactive Protein (CRP) are useful biomarkers to differentiate bacterial from viral or fungal infections, although the association between them and co-infection or mortality in COVID-19 remains unclear. METHODS: The study represents a retrospective cohort study of patients admitted for COVID-19 pneumonia to 84 ICUs from ten countries between (March 2020-January 2021). Primary outcome was to determine whether PCT or CRP at admission could predict community-acquired bacterial respiratory co-infection (BC) and its added clinical value by determining the best discriminating cut-off values. Secondary outcome was to investigate its association with mortality. To evaluate the main outcome, a binary logistic regression was performed. The area under the curve evaluated diagnostic performance for BC prediction. RESULTS: 4635 patients were included, 7.6% fulfilled BC diagnosis. PCT (0.25[IQR 0.1-0.7] versus 0.20[IQR 0.1-0.5]ng/mL, p<0.001) and CRP (14.8[IQR 8.2-23.8] versus 13.3 [7-21.7]mg/dL, p=0.01) were higher in BC group. Neither PCT nor CRP were independently associated with BC and both had a poor ability to predict BC (AUC for PCT 0.56, for CRP 0.54). Baseline values of PCT<0.3ng/mL, could be helpful to rule out BC (negative predictive value 91.1%) and PCT≥0.50ng/mL was associated with ICU mortality (OR 1.5,p<0.001). CONCLUSIONS: These biomarkers at ICU admission led to a poor ability to predict BC among patients with COVID-19 pneumonia. Baseline values of PCT<0.3ng/mL may be useful to rule out BC, providing clinicians a valuable tool to guide antibiotic stewardship and allowing the unjustified overuse of antibiotics observed during the pandemic, additionally PCT≥0.50ng/mL might predict worsening outcomes.

Dexamethasone as risk-factor for ICU-acquired respiratory tract infections in severe COVID-19.

PURPOSE: Dexamethasone is the only drug that has consistently reduced mortality in patients with COVID-19, especially in patients needing oxygen or invasive mechanical ventilation. However, there is a growing concern about the relation of dexamethasone with the unprecedented rates of ICU-acquired respiratory tract infections (ICU-RTI) observed in patients with severe COVID-19. METHODS: This was a multicenter, prospective cohort study; conducted in ten countries in Latin America and Europe. We included patients older than 18 with confirmed SARS-CoV-2 requiring ICU admission. A multivariate logistic regression and propensity score matching (PSM) analysis was conducted to determine the relation between dexamethasone treatment and ICU-RTI. RESULTS: A total of 3777 patients were included. 2065 (54.7%) were treated with dexamethasone within the first 24 h of admission. After performing the PSM, patients treated with dexamethasone showed significantly higher proportions of VAP (282/1652 [17.1%] Vs. 218/1652 [13.2%], p = 0.014). Also, dexamethasone treatment was identified as an adjusted risk factor of ICU-RTI in the multivariate logistic regression model (OR 1.64; 95%CI: 1.37-1.97; p < 0.001). CONCLUSION: Patients treated with dexamethasone for severe COVID-19 had a higher risk of developing ICU-acquired respiratory tract infections after adjusting for days of invasive mechanical ventilation and ICU length of stay, suggesting a cautious use of this treatment.

Corticosteroid treatment and mortality in mechanically ventilated COVID-19-associated acute respiratory distress syndrome (ARDS) patients: a multicentre cohort study.

BACKGROUND: Some unanswered questions persist regarding the effectiveness of corticosteroids for severe coronavirus disease 2019 (COVID-19) patients. We aimed to assess the clinical effect of corticosteroids on intensive care unit (ICU) mortality among mechanically ventilated COVID-19-associated acute respiratory distress syndrome (ARDS) patients. METHODS: This was a retrospective study of prospectively collected data conducted in 70 ICUs (68 Spanish, one Andorran, one Irish), including mechanically ventilated COVID-19-associated ARDS patients admitted between February 6 and September 20, 2020. Individuals who received corticosteroids for refractory shock were excluded. Patients exposed to corticosteroids at admission were matched with patients without corticosteroids through propensity score matching. Primary outcome was all-cause ICU mortality. Secondary outcomes were to compare in-hospital mortality, ventilator-free days at 28 days, respiratory superinfection and length of stay between patients with corticosteroids and those without corticosteroids. We performed survival analysis accounting for competing risks and subgroup sensitivity analysis. RESULTS: We included 1835 mechanically ventilated COVID-19-associated ARDS, of whom 1117 (60.9%) received corticosteroids. After propensity score matching, ICU mortality did not differ between patients treated with corticosteroids and untreated patients (33.8% vs. 30.9%; p = 0.28). In survival analysis, corticosteroid treatment at ICU admission was associated with short-term survival benefit (HR 0.53; 95% CI 0.39-0.72), although beyond the 17th day of admission, this effect switched and there was an increased ICU mortality (long-term HR 1.68; 95% CI 1.16-2.45). The sensitivity analysis reinforced the results. Subgroups of age < 60 years, severe ARDS and corticosteroids plus tocilizumab could have greatest benefit from corticosteroids as short-term decreased ICU mortality without long-term negative effects were observed. Larger length of stay was observed with corticosteroids among non-survivors both in the ICU and in hospital. There were no significant differences for the remaining secondary outcomes. CONCLUSIONS: Our results suggest that corticosteroid treatment for mechanically ventilated COVID-19-associated ARDS had a biphasic time-dependent effect on ICU mortality. Specific subgroups showed clear effect on improving survival with corticosteroid use. Therefore, further research is required to identify treatment-responsive subgroups among the mechanically ventilated COVID-19-associated ARDS patients.

Mortality comparison between the first and second/third waves among 3,795 critical COVID-19 patients with pneumonia admitted to the ICU: A multicentre retrospective cohort study.

BACKGROUND: It is unclear whether the changes in critical care throughout the pandemic have improved the outcomes in coronavirus disease 2019 (COVID-19) patients admitted to the intensive care units (ICUs). METHODS: We conducted a retrospective cohort study in adults with COVID-19 pneumonia admitted to 73 ICUs from Spain, Andorra and Ireland between February 2020 and March 2021. The first wave corresponded with the period from February 2020 to June 2020, whereas the second/third waves occurred from July 2020 to March 2021. The primary outcome was ICU mortality between study periods. Mortality predictors and differences in mortality between COVID-19 waves were identified using logistic regression. FINDINGS: As of March 2021, the participating ICUs had included 3795 COVID-19 pneumonia patients, 2479 (65·3%) and 1316 (34·7%) belonging to the first and second/third waves, respectively. Illness severity scores predicting mortality were lower in the second/third waves compared with the first wave according with the Acute Physiology and Chronic Health Evaluation system (median APACHE II score 12 [IQR 9-16] vs 14 [IQR 10-19]) and the organ failure assessment score (median SOFA 4 [3-6] vs 5 [3-7], p<0·001). The need of invasive mechanical ventilation was high (76·1%) during the whole study period. However, a significant increase in the use of high flow nasal cannula (48·7% vs 18·2%, p<0·001) was found in the second/third waves compared with the first surge. Significant changes on treatments prescribed were also observed, highlighting the remarkable increase on the use of corticosteroids to up to 95.9% in the second/third waves. A significant reduction on the use of tocilizumab was found during the study (first wave 28·9% vs second/third waves 6·2%, p<0·001), and a negligible administration of lopinavir/ritonavir, hydroxychloroquine, and interferon during the second/third waves compared with the first wave. Overall ICU mortality was 30·7% (n = 1166), without significant differences between study periods (first wave 31·7% vs second/third waves 28·8%, p = 0·06). No significant differences were found in ICU mortality between waves according to age subsets except for the subgroup of 61-75 years of age, in whom a reduced unadjusted ICU mortality was observed in the second/third waves (first 38·7% vs second/third 34·0%, p = 0·048). Non-survivors were older, with higher severity of the disease, had more comorbidities, and developed more complications. After adjusting for confounding factors through a multivariable analysis, no significant association was found between the COVID-19 waves and mortality (OR 0·81, 95% CI 0·64-1·03; p = 0·09). Ventilator-associated pneumonia rate increased significantly during the second/third waves and it was independently associated with ICU mortality (OR 1·48, 95% CI 1·19-1·85, p<0·001). Nevertheless, a significant reduction both in the ICU and hospital length of stay in survivors was observed during the second/third waves. INTERPRETATION: Despite substantial changes on supportive care and management, we did not find significant improvement on case-fatality rates among critical COVID-19 pneumonia patients. FUNDING: Ricardo Barri Casanovas Foundation (RBCF2020) and SEMICYUC.

Prognostic Value of Procalcitonin and C-Reactive Protein in 1608 Critically Ill Patients with Severe Influenza Pneumonia.

Background: Procalcitonin (PCT) and C-Reactive protein (CRP) are well-established sepsis biomarkers. The association of baseline PCT levels and mortality in pneumonia remains unclear, and we still do not know whether biomarkers levels could be related to the causative microorganism (GPC, GNB). The objective of this study is to address these issues. Methods: a retrospective observational cohort study was conducted in 184 Spanish ICUs (2009-2018). Results: 1608 patients with severe influenza pneumonia with PCT and CRP available levels on admission were included, 1186 with primary viral pneumonia (PVP) and 422 with bacterial Co-infection (BC). Those with BC presented higher PCT levels (4.25 [0.6-19.5] versus 0.6 [0.2-2.3]ng/mL) and CRP (36.7 [20.23-118] versus 28.05 [13.3-109]mg/dL) as compared to PVP (p < 0.001). Deceased patients had higher PCT (ng/mL) when compared with survivors, in PVP (0.82 [0.3-2.8]) versus 0.53 [0.19-2.1], p = 0.001) and BC (6.9 [0.93-28.5] versus 3.8 [0.5-17.37], p = 0.039). However, no significant association with mortality was observed in the multivariate analysis. The PCT levels (ng/mL) were significantly higher in polymicrobial infection (8.4) and GPC (6.9) when compared with GNB (1.2) and Aspergillus (1.7). The AUC-ROC of PCT for GPC was 0.67 and 0.32 for GNB. The AUROC of CRP was 0.56 for GPC and 0.39 for GNB. Conclusions: a single PCT/CRP value at ICU admission was not associated with mortality in severe influenza pneumonia. None of the biomarkers have enough discriminatory power to be used for predicting the causative microorganism of the co-infection.

Early oseltamivir treatment improves survival in critically ill patients with influenza pneumonia.

BACKGROUND: The relationship between early oseltamivir treatment (within 48 h of symptom onset) and mortality in patients admitted to intensive care units (ICUs) with severe influenza is disputed. This study aimed to investigate the association between early oseltamivir treatment and ICU mortality in critically ill patients with influenza pneumonia. METHODS: This was an observational study of patients with influenza pneumonia admitted to 184 ICUs in Spain during 2009-2018. The primary outcome was to evaluate the association between early oseltamivir treatment and ICU mortality compared with later treatment. Secondary outcomes were to compare the duration of mechanical ventilation and ICU length of stay between the early and later oseltamivir treatment groups. To reduce biases related to observational studies, propensity score matching and a competing risk analysis were performed. RESULTS: During the study period, 2124 patients met the inclusion criteria. All patients had influenza pneumonia and received oseltamivir before ICU admission. Of these, 529 (24.9%) received early oseltamivir treatment. In the multivariate analysis, early treatment was associated with reduced ICU mortality (OR 0.69, 95% CI 0.51-0.95). After propensity score matching, early oseltamivir treatment was associated with improved survival rates in the Cox regression (hazard ratio 0.77, 95% CI 0.61-0.99) and competing risk (subdistribution hazard ratio 0.67, 95% CI 0.53-0.85) analyses. The ICU length of stay and duration of mechanical ventilation were shorter in patients receiving early treatment. CONCLUSIONS: Early oseltamivir treatment is associated with improved survival rates in critically ill patients with influenza pneumonia, and may decrease ICU length of stay and mechanical ventilation duration.

Infección grave por Coronavirus SARS-CoV-2: Experiencia en un hospital de tercer nivel con pacientes afectados por COVID-19 durante la pandemia 2020 / Severe infection due to the SARS-CoV-2 CORONAVIRUS: Experience of a tertiary hospital with COVID-19 patients during the 2020 pandemic

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Corticosteroid treatment in critically ill patients with severe influenza pneumonia: a propensity score matching study.

PURPOSE: To determine clinical predictors associated with corticosteroid administration and its association with ICU mortality in critically ill patients with severe influenza pneumonia. METHODS: Secondary analysis of a prospective cohort study of critically ill patients with confirmed influenza pneumonia admitted to 148 ICUs in Spain between June 2009 and April 2014. Patients who received corticosteroid treatment for causes other than viral pneumonia (e.g., refractory septic shock and asthma or chronic obstructive pulmonary disease [COPD] exacerbation) were excluded. Patients with corticosteroid therapy were compared with those without corticosteroid therapy. We use a propensity score (PS) matching analysis to reduce confounding factors. The primary outcome was ICU mortality. Cox proportional hazards and competing risks analysis was performed to assess the impact of corticosteroids on ICU mortality. RESULTS: A total of 1846 patients with primary influenza pneumonia were enrolled. Corticosteroids were administered in 604 (32.7%) patients, with methylprednisolone the most frequently used corticosteroid (578/604 [95.7%]). The median daily dose was equivalent to 80 mg of methylprednisolone (IQR 60-120) for a median duration of 7 days (IQR 5-10). Asthma, COPD, hematological disease, and the need for mechanical ventilation were independently associated with corticosteroid use. Crude ICU mortality was higher in patients who received corticosteroids (27.5%) than in patients who did not receive corticosteroids (18.8%, p < 0.001). After PS matching, corticosteroid use was associated with ICU mortality in the Cox (HR = 1.32 [95% CI 1.08-1.60], p < 0.006) and competing risks analysis (SHR = 1.37 [95% CI 1.12-1.68], p = 0.001). CONCLUSION: Administration of corticosteroids in patients with severe influenza pneumonia is associated with increased ICU mortality, and these agents should not be used as co-adjuvant therapy.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment.

BACKGROUND: Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU). OBJECTIVE: To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS). METHODS: The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors. RESULTS: Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS. CONCLUSIONS: Automatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors.

Risk Factors for Noninvasive Ventilation Failure in Critically Ill Subjects With Confirmed Influenza Infection.

BACKGROUND: Despite wide use of noninvasive ventilation (NIV) in several clinical settings, the beneficial effects of NIV in patients with hypoxemic acute respiratory failure (ARF) due to influenza infection remain controversial. The aim of this study was to identify the profile of patients with risk factors for NIV failure using chi-square automatic interaction detection (CHAID) analysis and to determine whether NIV failure is associated with ICU mortality. METHODS: This work was a secondary analysis from prospective and observational multi-center analysis in critically ill subjects admitted to the ICU with ARF due to influenza infection requiring mechanical ventilation. Three groups of subjects were compared: (1) subjects who received NIV immediately after ICU admission for ARF and then failed (NIV failure group); (2) subjects who received NIV immediately after ICU admission for ARF and then succeeded (NIV success group); and (3) subjects who received invasive mechanical ventilation immediately after ICU admission for ARF (invasive mechanical ventilation group). Profiles of subjects with risk factors for NIV failure were obtained using CHAID analysis. RESULTS: Of 1,898 subjects, 806 underwent NIV, and 56.8% of them failed. Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, infiltrates in chest radiograph, and ICU mortality (38.4% vs 6.3%) were higher (P < .001) in the NIV failure than in the NIV success group. SOFA score was the variable most associated with NIV failure, and 2 cutoffs were determined. Subjects with SOFA ≥ 5 had a higher risk of NIV failure (odds ratio = 3.3, 95% CI 2.4-4.5). ICU mortality was higher in subjects with NIV failure (38.4%) compared with invasive mechanical ventilation subjects (31.3%, P = .018), and NIV failure was associated with increased ICU mortality (odds ratio = 11.4, 95% CI 6.5-20.1). CONCLUSIONS: An automatic and non-subjective algorithm based on CHAID decision-tree analysis can help to define the profile of patients with different risks of NIV failure, which might be a promising tool to assist in clinical decision making to avoid the possible complications associated with NIV failure.