RESUMO
BACKGROUND: The prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction. METHODS: This was an observational, multicenter, development, and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores. RESULTS: Our development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/-24 h of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71-0.78) which was higher than that of any previously reported predictive scores (0.68 [CI 0.64-0.71], 0.61 [CI 0.58-0.66], 0.67 [CI 0.63-0.70], 0.70 [CI 0.67-0.74] for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively). CONCLUSIONS: Using a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far.
Assuntos
COVID-19 , Adulto , Idoso , Cuidados Críticos , Mortalidade Hospitalar , Humanos , Unidades de Terapia Intensiva , Masculino , Estudos Multicêntricos como Assunto , Estudos Observacionais como Assunto , Gravidade do Paciente , Prognóstico , Estudos Retrospectivos , SARS-CoV-2RESUMO
BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. METHODS: A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract-transform-load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. RESULTS: Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. CONCLUSIONS: In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.
Assuntos
COVID-19/epidemiologia , Estado Terminal/epidemiologia , Data Warehousing/estatística & dados numéricos , Registros Eletrônicos de Saúde/estatística & dados numéricos , Hospitalização/estatística & dados numéricos , Unidades de Terapia Intensiva/estatística & dados numéricos , Cuidados Críticos , Humanos , Países BaixosRESUMO
INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. RESULTS: A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.
Assuntos
Extubação , COVID-19 , Falha de Tratamento , Adulto , COVID-19/terapia , Estado Terminal , Humanos , Aprendizado de MáquinaRESUMO
OBJECTIVE: Validated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current study was to evaluate the performance of early warning scores (EWS) in the ED when identifying patients with COVID-19 who will require intensive care unit (ICU) admission for high-flow-oxygen usage or mechanical ventilation. METHODS: Patients with a proven SARS-CoV-2 infection with complete resuscitate orders treated in nine hospitals between 27 February and 30 July 2020 needing hospital admission were included. Primary outcome was the performance of EWS in identifying patients needing ICU admission within 24 hours after ED presentation. RESULTS: In total, 1501 patients were included. Median age was 71 (range 19-99) years and 60.3% were male. Of all patients, 86.9% were admitted to the general ward and 13.1% to the ICU within 24 hours after ED admission. ICU patients had lower peripheral oxygen saturation (86.7% vs 93.7, p≤0.001) and had a higher body mass index (29.2 vs 27.9 p=0.043) compared with non-ICU patients. National Early Warning Score 2 (NEWS2) ≥ 6 and q-COVID Score were superior to all other studied clinical risk scores in predicting ICU admission with a fair area under the receiver operating characteristics curve of 0.740 (95% CI 0.696 to 0.783) and 0.760 (95% CI 0.712 to 0.800), respectively. NEWS2 ≥6 and q-COVID Score ≥3 discriminated patients admitted to the ICU with a sensitivity of 78.1% and 75.9%, and specificity of 56.3% and 61.8%, respectively. CONCLUSION: In this multicentre study, the best performing models to predict ICU admittance were the NEWS2 and the Quick COVID-19 Severity Index Score, with fair diagnostic performance. However, due to the moderate performance, these models cannot be clinically used to adequately predict the need for ICU admission within 24 hours in patients with SARS-CoV-2 infection presenting at the ED.
Assuntos
COVID-19/diagnóstico , Estado Terminal , Escore de Alerta Precoce , Adulto , Idoso , Idoso de 80 Anos ou mais , COVID-19/classificação , Feminino , Humanos , Unidades de Terapia Intensiva , Masculino , Pessoa de Meia-Idade , Admissão do Paciente , Valor Preditivo dos Testes , Curva ROC , TriagemRESUMO
OBJECTIVES: To prospectively investigate in patients with severe COVID-19-associated cytokine storm syndrome (CSS) whether an intensive course of glucocorticoids with or without tocilizumab accelerates clinical improvement, reduces mortality and prevents invasive mechanical ventilation, in comparison with a historic control group of patients who received supportive care only. METHODS: From 1 April 2020, patients with COVID-19-associated CSS, defined as rapid respiratory deterioration plus at least two out of three biomarkers with important elevations (C-reactive protein >100 mg/L; ferritin >900 µg/L; D-dimer >1500 µg/L), received high-dose intravenous methylprednisolone for 5 consecutive days (250 mg on day 1 followed by 80 mg on days 2-5). If the respiratory condition had not improved sufficiently (in 43%), the interleukin-6 receptor blocker tocilizumab (8 mg/kg body weight, single infusion) was added on or after day 2. Control patients with COVID-19-associated CSS (same definition) were retrospectively sampled from the pool of patients (n=350) admitted between 7 March and 31 March, and matched one to one to treated patients on sex and age. The primary outcome was ≥2 stages of improvement on a 7-item WHO-endorsed scale for trials in patients with severe influenza pneumonia, or discharge from the hospital. Secondary outcomes were hospital mortality and mechanical ventilation. RESULTS: At baseline all patients with COVID-19 in the treatment group (n=86) and control group (n=86) had symptoms of CSS and faced acute respiratory failure. Treated patients had 79% higher likelihood on reaching the primary outcome (HR: 1.8; 95% CI 1.2 to 2.7) (7 days earlier), 65% less mortality (HR: 0.35; 95% CI 0.19 to 0.65) and 71% less invasive mechanical ventilation (HR: 0.29; 95% CI 0.14 to 0.65). Treatment effects remained constant in confounding and sensitivity analyses. CONCLUSIONS: A strategy involving a course of high-dose methylprednisolone, followed by tocilizumab if needed, may accelerate respiratory recovery, lower hospital mortality and reduce the likelihood of invasive mechanical ventilation in COVID-19-associated CSS.
Assuntos
Anticorpos Monoclonais Humanizados/administração & dosagem , Betacoronavirus , Infecções por Coronavirus/tratamento farmacológico , Síndrome da Liberação de Citocina/tratamento farmacológico , Glucocorticoides/administração & dosagem , Pneumonia Viral/tratamento farmacológico , Idoso , Proteína C-Reativa/análise , COVID-19 , Infecções por Coronavirus/sangue , Infecções por Coronavirus/complicações , Infecções por Coronavirus/virologia , Síndrome da Liberação de Citocina/sangue , Síndrome da Liberação de Citocina/virologia , Citocinas/sangue , Quimioterapia Combinada , Feminino , Ferritinas/sangue , Produtos de Degradação da Fibrina e do Fibrinogênio/análise , Estudo Historicamente Controlado , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/sangue , Pneumonia Viral/complicações , Pneumonia Viral/virologia , Estudos Prospectivos , SARS-CoV-2 , Padrão de Cuidado , Resultado do Tratamento , Tratamento Farmacológico da COVID-19RESUMO
Background: Although there is no specific therapy for COVID-19, it is recommended that patients with severe SARS-CoV-2 infection are treated with corticosteroids and anti-IL-6 receptor monoclonal antibodies. Both COVID-19 itself and the treatment modalities mentioned above have suppressive effects on the immune system which may lead to an increased susceptibility to other infections. In patients with latent tuberculosis (TB) reactivation of TB infection after recovery from severe COVID-19 has been described. Most of these cases have occurred in parts of the world where tuberculosis is endemic. Case description: The patient is a female in her 70s who was born and raised in Southeast Asia and has lived in the Netherlands for more than 30 years. She was treated for a severe COVID-19 requiring mechanical ventilation for several weeks and pharmaceutical treatment with corticosteroids and anti-IL-6 receptor monoclonal antibodies (Sarilumab). She recovered well. Two years later she was readmitted with symptoms of a serious pulmonary infection and meningitis. Her condition deteriorated in a short time. An active TB infection was diagnosed. Despite adequate antibiotic treatment and supportive therapy her condition worsened and four days after admission to the ICU she deceased. Discussion: Reactivation of latent TB after recovery from a severe COVID-19 has been described several times and may occur several months after the SARS-CoV-2 infection. In this case the reactivation presented two years after COVID-19. This case illustrates that long-term follow-up of patients with latent TB that recover from a severe COVID-19 may be indicated. LEARNING POINTS: Reactivation of latent tuberculosis infection in patients treated for a severe COVID-19 may occur even two years after recovery from SARS-CoV-2 infection.Most cases of reactivation of tuberculosis after COVID-19 are described in regions where tuberculosis is endemic. However, it may also occur in countries with a relatively low prevalence of tuberculosis infection. The exact incidence of tuberculosis reactivation after COVID-19 is unknown and probably underestimated.A long-term follow-up of patients after severe COVID-19 treated with corticosteroids and/or anti-IL-6 receptor monoclonal antibodies with a history of tuberculosis or patients migrated from countries where tuberculosis is endemic seems to be important.
RESUMO
Introduction: Pulmonary embolism (PE) is a frequent complication in COVID-19. However, the influence of PE on the prognosis of COVID-19 remains unclear as previous studies were affected by misclassification bias. Therefore, we evaluated a cohort of COVID-19 patients whom all underwent systematic screening for PE (thereby avoiding misclassification) and compared clinical outcomes between patients with and without PE. Materials and methods: We included all COVID-19 patients who were admitted through the ED between April 2020 and February 2021. All patients underwent systematic work-up for PE in the ED using the YEARS-algorithm. The primary outcome was a composite of in-hospital mortality and ICU admission. We also evaluated long-term outcomes including PE occurrence within 90 days after discharge and one-year all-cause mortality. Results: 637 ED patients were included in the analysis. PE was diagnosed in 46 of them (7.2%). The occurrence of the primary outcome did not differ between patients with PE and those without (28.3% vs. 26.9%, p = 0.68). The overall rate of PE diagnosed in-hospital (after an initial negative PE screening in the ED) and in the first 90 days after discharge was 3.9% and 1.2% respectively. One-year all-cause mortality was similar between patients with and without PE (26.1% vs. 24.4%, p = 0.83). Conclusions: In a cohort of COVID-19 patients who underwent systematic PE screening in the ED, we found no differences in mortality rate and ICU admissions between patients with and without PE. This may indicate that proactive PE screening, and thus timely diagnosis and treatment of PE, may limit further clinical deterioration and associated mortality in COVID-19 patients.
RESUMO
Background: In the previously reported SAPS trial (https://clinicaltrials.gov/ct2/show/NCT01139489), procalcitonin-guidance safely reduced the duration of antibiotic treatment in critically ill patients. We assessed the impact of shorter antibiotic treatment on antimicrobial resistance development in SAPS patients. Materials and methods: Cultures were assessed for the presence of multi-drug resistant (MDR) or highly resistant organisms (HRMO) and compared between PCT-guided and control patients. Baseline isolates from 30 days before to 5 days after randomization were compared with those from 5 to 30 days post-randomization. The primary endpoint was the incidence of new MDR/HRMO positive patients. Results: In total, 8,113 cultures with 96,515 antibiotic test results were evaluated for 439 and 482 patients randomized to the PCT and control groups, respectively. Disease severity at admission was similar for both groups. Median (IQR) durations of the first course of antibiotics were 6 days (4-10) and 7 days (5-11), respectively (p = 0.0001). Antibiotic-free days were 7 days (IQR 0-14) and 6 days (0-13; p = 0.05). Of all isolates assessed, 13% were MDR/HRMO positive and at baseline 186 (20%) patients were MDR/HMRO-positive. The incidence of new MDR/HRMO was 39 (8.9%) and 45 (9.3%) in PCT and control patients, respectively (p = 0.82). The time courses for MDR/HRMO development were also similar for both groups (p = 0.33). Conclusions: In the 921 randomized patients studied, the small but statistically significant reduction in antibiotic treatment in the PCT-group did not translate into a detectable change in antimicrobial resistance. Studies with larger differences in antibiotic treatment duration, larger study populations or populations with higher MDR/HRMO incidences might detect such differences.
RESUMO
BACKGROUND: Fluid therapy is a common intervention in critically ill patients. It is increasingly recognised that deresuscitation is an essential part of fluid therapy and delayed deresuscitation is associated with longer invasive ventilation and length of intensive care unit (ICU) stay. However, optimal timing and rate of deresuscitation remain unclear. Lung ultrasound (LUS) may be used to identify fluid overload. We hypothesise that daily LUS-guided deresuscitation is superior to deresuscitation without LUS in critically ill patients expected to undergo invasive ventilation for more than 24 h in terms of ventilator free-days and being alive at day 28. METHODS: The "effect of lung ultrasound-guided fluid deresuscitation on duration of ventilation in intensive care unit patients" (CONFIDENCE) is a national, multicentre, open-label, randomised controlled trial (RCT) in adult critically ill patients that are expected to be invasively ventilated for at least 24 h. Patients with conditions that preclude a negative fluid balance or LUS examination are excluded. CONFIDENCE will operate in 10 ICUs in the Netherlands and enrol 1000 patients. After hemodynamic stabilisation, patients assigned to the intervention will receive daily LUS with fluid balance recommendations. Subjects in the control arm are deresuscitated at the physician's discretion without the use of LUS. The primary endpoint is the number of ventilator-free days and being alive at day 28. Secondary endpoints include the duration of invasive ventilation; 28-day mortality; 90-day mortality; ICU, in hospital and total length of stay; cumulative fluid balance on days 1-7 after randomisation and on days 1-7 after start of LUS examination; mean serum lactate on days 1-7; the incidence of reintubations, chest drain placement, atrial fibrillation, kidney injury (KDIGO stadium ≥ 2) and hypernatremia; the use of invasive hemodynamic monitoring, and chest-X-ray; and quality of life at day 28. DISCUSSION: The CONFIDENCE trial is the first RCT comparing the effect of LUS-guided deresuscitation to routine care in invasively ventilated ICU patients. If proven effective, LUS-guided deresuscitation could improve outcomes in some of the most vulnerable and resource-intensive patients in a manner that is non-invasive, easy to perform, and well-implementable. TRIAL REGISTRATION: ClinicalTrials.gov NCT05188092. Registered since January 12, 2022.
Assuntos
Estado Terminal , Pulmão , Adulto , Humanos , Pulmão/diagnóstico por imagem , Cuidados Críticos/métodos , Respiração Artificial/métodos , Unidades de Terapia Intensiva , Ultrassonografia de Intervenção , Ensaios Clínicos Controlados Aleatórios como Assunto , Estudos Multicêntricos como AssuntoRESUMO
OBJECTIVES: To evaluate the relationship among dysnatraemia at hospital presentation and duration of admission, risk of intensive care unit (ICU) admission and all-cause mortality and to assess the underlying pathophysiological mechanism of hyponatraemia in patients with COVID-19. Our hypothesis is that both hyponatraemia and hypernatraemia at presentation are associated with adverse outcomes. DESIGN: Observational study. SETTING: Secondary care; 11 Dutch hospitals (2 university and 9 general hospitals). PARTICIPANTS: An analysis was performed within the retrospective multicentre cohort study COVIDPredict. 7811 patients were included (60% men, 40% women) between 24 February 2020 and 9 August 2022. Patients who were ≥18 years with PCR-confirmed COVID-19 or CT with COVID-19 reporting and data system score≥4 and alternative diagnosis were included. Patients were excluded when serum sodium levels at presentation were not registered in the database or when they had been transferred from another participating hospital. OUTCOME MEASURES: We studied demographics, medical history, symptoms and outcomes. Patients were stratified according to serum sodium concentration and urinary sodium excretion. RESULTS: Hyponatraemia was present in 2677 (34.2%) patients and hypernatraemia in 126 (1.6%) patients. Patients with hyponatraemia presented more frequently with diarrhoea, lower blood pressure and tachycardia. Hyponatraemia was, despite a higher risk for ICU admission (OR 1.27 (1.11-1.46; p<0.001)), not associated with mortality or the risk for intubation. Patients with hypernatraemia had higher mortality rates (OR 2.25 (1.49-3.41; p<0.001)) and were at risk for ICU admission (OR 2.89 (1.83-4.58)) and intubation (OR 2.95 (1.83-4.74)). CONCLUSIONS: Hypernatraemia at presentation was associated with adverse outcomes in patients with COVID-19. Hypovolaemic hyponatraemia was found to be the most common aetiology of hyponatraemia. Hyponatraemia of unknown aetiology was associated with a higher risk for ICU admission and intubation and longer duration of admission.
Assuntos
COVID-19 , Hipernatremia , Hiponatremia , Masculino , Humanos , Feminino , Hiponatremia/epidemiologia , Hiponatremia/etiologia , Hipernatremia/epidemiologia , Hipernatremia/etiologia , COVID-19/complicações , Estudos de Coortes , Sódio , Unidades de Terapia Intensiva , Estudos Retrospectivos , HospitaisRESUMO
OBJECTIVES: The aim of this multicentre COVID-PREDICT study (a nationwide observational cohort study that aims to better understand clinical course of COVID-19 and to predict which COVID-19 patients should receive which treatment and which type of care) was to determine the association between atrial fibrillation (AF) and mortality, intensive care unit (ICU) admission, complications and discharge destination in hospitalised COVID-19 patients. SETTING: Data from a historical cohort study in eight hospitals (both academic and non-academic) in the Netherlands between January 2020 and July 2021 were used in this study. PARTICIPANTS: 3064 hospitalised COVID-19 patients >18 years old. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the incidence of new-onset AF during hospitalisation. Secondary outcomes were the association between new-onset AF (vs prevalent or non-AF) and mortality, ICU admissions, complications and discharge destination, performed by univariable and multivariable logistic regression analyses. RESULTS: Of the 3064 included patients (60.6% men, median age: 65 years, IQR 55-75 years), 72 (2.3%) patients had prevalent AF and 164 (5.4%) patients developed new-onset AF during hospitalisation. Compared with patients without AF, patients with new-onset AF had a higher incidence of death (adjusted OR (aOR) 1.71, 95% CI 1.17 to 2.59) an ICU admission (aOR 5.45, 95% CI 3.90 to 7.61). Mortality was non-significantly different between patients with prevalent AF and those with new-onset AF (aOR 0.97, 95% CI 0.53 to 1.76). However, new-onset AF was associated with a higher incidence of ICU admission and complications compared with prevalent AF (OR 6.34, 95% CI 2.95 to 13.63, OR 3.04, 95% CI 1.67 to 5.55, respectively). CONCLUSION: New-onset AF was associated with an increased incidence of death, ICU admission, complications and a lower chance to be discharged home. These effects were far less pronounced in patients with prevalent AF. Therefore, new-onset AF seems to represent a marker of disease severity, rather than a cause of adverse outcomes.
Assuntos
Fibrilação Atrial , COVID-19 , Idoso , Feminino , Humanos , Masculino , Fibrilação Atrial/tratamento farmacológico , Estudos de Coortes , COVID-19/complicações , COVID-19/epidemiologia , Mortalidade Hospitalar , Países Baixos/epidemiologia , Prognóstico , Fatores de Risco , Pessoa de Meia-IdadeRESUMO
BACKGROUND: For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. METHODS: From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. RESULTS: The median duration of prone episodes was 17 h (11-20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. CONCLUSIONS: In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.
RESUMO
PURPOSE: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. METHODS: Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. RESULTS: A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. CONCLUSION: In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves.
Assuntos
COVID-19 , COVID-19/epidemiologia , Registros Eletrônicos de Saúde , Mortalidade Hospitalar , Humanos , Unidades de Terapia Intensiva , Países Baixos/epidemiologia , Sistema de Registros , Estudos RetrospectivosRESUMO
ABSTRACT: Background: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort study of central venous catheters (CVCs) in critically ill COVID-19 patients. Eligible CVC insertions required an indwelling time of at least 48 hours and were identified using a full-admission electronic health record database. Risk factors were identified using logistic regression. Differences in survival rates at day 28 of follow-up were assessed using a log-rank test and proportional hazard model. Results: In 538 patients, a total of 914 CVCs were included. Prevalence and incidence of suspected catheter-related infection were 7.9% and 9.4 infections per 1,000 catheter indwelling days, respectively. Prone ventilation for more than 5 days was associated with increased risk of suspected catheter-related infection; odds ratio, 5.05 (95% confidence interval 2.12-11.0). Risk of death was significantly higher in patients with suspected catheter-related infection (hazard ratio, 1.78; 95% confidence interval, 1.25-2.53). Conclusions: This study shows that in critically ill patients with COVID-19, prevalence and incidence of suspected catheter-related infection are high, prone ventilation is a risk factor, and mortality is higher in case of catheter-related infection.
Assuntos
COVID-19 , Infecções Relacionadas a Cateter , Cateterismo Venoso Central , Cateteres Venosos Centrais , Humanos , Infecções Relacionadas a Cateter/epidemiologia , Infecções Relacionadas a Cateter/etiologia , Cateterismo Venoso Central/efeitos adversos , Estado Terminal , Incidência , Estudos Retrospectivos , COVID-19/epidemiologia , Cateteres Venosos Centrais/efeitos adversos , Fatores de RiscoRESUMO
Purpose: Inhibition of dipeptidyl peptidase (DPP-)4 could reduce coronavirus disease 2019 (COVID-19) severity by reducing inflammation and enhancing tissue repair beyond glucose lowering. We aimed to assess this in a prospective cohort study. Methods: We studied in 565 patients with type 2 diabetes in the CovidPredict Clinical Course Cohort whether use of a DPP-4 inhibitor prior to hospital admission due to COVID-19 was associated with improved clinical outcomes. Using crude analyses and propensity score matching (on age, sex and BMI), 28 patients using a DPP-4 inhibitor were identified and compared to non-users. Results: No differences were found in the primary outcome mortality (matched-analysis = odds-ratio: 0,94 [95% confidence interval: 0,69 - 1,28], p-value: 0,689) or any of the secondary outcomes (ICU admission, invasive ventilation, thrombotic events or infectious complications). Additional analyses comparing users of DPP-4 inhibitors with subgroups of non-users (subgroup 1: users of metformin and sulphonylurea; subgroup 2: users of any insulin combination), allowing to correct for diabetes severity, did not yield different results. Conclusions: We conclude that outpatient use of a DPP-4 inhibitor does not affect the clinical outcomes of patients with type 2 diabetes who are hospitalized because of COVID-19 infection.
RESUMO
OBJECTIVES: Recent reports suggest a high prevalence of hypertension and diabetes in COVID-19 patients, but the role of cardiovascular disease (CVD) risk factors in the clinical course of COVID-19 is unknown. We evaluated the time-to-event relationship between hypertension, dyslipidaemia, diabetes and COVID-19 outcomes. DESIGN: We analysed data from the prospective Dutch CovidPredict cohort, an ongoing prospective study of patients admitted for COVID-19 infection. SETTING: Patients from eight participating hospitals, including two university hospitals from the CovidPredict cohort were included. PARTICIPANTS: Admitted, adult patients with a positive COVID-19 PCR or high suspicion based on CT-imaging of the thorax. Patients were followed for major outcomes during the hospitalisation. CVD risk factors were established via home medication lists and divided in antihypertensives, lipid-lowering therapy and antidiabetics. PRIMARY AND SECONDARY OUTCOMES MEASURES: The primary outcome was mortality during the first 21 days following admission, secondary outcomes consisted of intensive care unit (ICU) admission and ICU mortality. Kaplan-Meier and Cox regression analyses were used to determine the association with CVD risk factors. RESULTS: We included 1604 patients with a mean age of 66±15 of whom 60.5% were men. Antihypertensives, lipid-lowering therapy and antidiabetics were used by 45%, 34.7% and 22.1% of patients. After 21-days of follow-up; 19.2% of the patients had died or were discharged for palliative care. Cox regression analysis after adjustment for age and sex showed that the presence of ≥2 risk factors was associated with increased mortality risk (HR 1.52, 95% CI 1.15 to 2.02), but not with ICU admission. Moreover, the use of ≥2 antidiabetics and ≥2 antihypertensives was associated with mortality independent of age and sex with HRs of, respectively, 2.09 (95% CI 1.55 to 2.80) and 1.46 (95% CI 1.11 to 1.91). CONCLUSIONS: The accumulation of hypertension, dyslipidaemia and diabetes leads to a stepwise increased risk for short-term mortality in hospitalised COVID-19 patients independent of age and sex. Further studies investigating how these risk factors disproportionately affect COVID-19 patients are warranted.
Assuntos
COVID-19 , Fatores de Risco de Doenças Cardíacas , Idoso , COVID-19/terapia , Feminino , Hospitalização , Humanos , Unidades de Terapia Intensiva , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Resultado do TratamentoRESUMO
OBJECTIVES: Develop simple and valid models for predicting mortality and need for intensive care unit (ICU) admission in patients who present at the emergency department (ED) with suspected COVID-19. DESIGN: Retrospective. SETTING: Secondary care in four large Dutch hospitals. PARTICIPANTS: Patients who presented at the ED and were admitted to hospital with suspected COVID-19. We used 5831 first-wave patients who presented between March and August 2020 for model development and 3252 second-wave patients who presented between September and December 2020 for model validation. OUTCOME MEASURES: We developed separate logistic regression models for in-hospital death and for need for ICU admission, both within 28 days after hospital admission. Based on prior literature, we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. We assessed model performance by the area under the receiver operating characteristic curve (AUC) and by calibration plots. RESULTS: Of 5831 first-wave patients, 629 (10.8%) died within 28 days after admission. ICU admission was fully recorded for 2633 first-wave patients in 2 hospitals, with 214 (8.1%) ICU admissions within 28 days. A simple model-COVID outcome prediction in the emergency department (COPE)-with age, respiratory rate, C reactive protein, lactate dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well calibrated and showed good discrimination for mortality in second-wave patients (AUC in four hospitals: 0.82 (95% CI 0.78 to 0.86); 0.82 (95% CI 0.74 to 0.90); 0.79 (95% CI 0.70 to 0.88); 0.83 (95% CI 0.79 to 0.86)). COPE was also able to identify patients at high risk of needing ICU admission in second-wave patients (AUC in two hospitals: 0.84 (95% CI 0.78 to 0.90); 0.81 (95% CI 0.66 to 0.95)). CONCLUSIONS: COPE is a simple tool that is well able to predict mortality and need for ICU admission in patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.
Assuntos
COVID-19 , Serviço Hospitalar de Emergência , Mortalidade Hospitalar , Hospitais , Humanos , Unidades de Terapia Intensiva , Estudos Retrospectivos , SARS-CoV-2RESUMO
Objective: To evaluate the association between overweight and obesity on the clinical course and outcomes in patients hospitalized with COVID-19. Design: Retrospective, observational cohort study. Methods: We performed a multicenter, retrospective, observational cohort study of hospitalized COVID-19 patients to evaluate the associations between overweight and obesity on the clinical course and outcomes. Results: Out of 1634 hospitalized COVID-19 patients, 473 (28.9%) had normal weight, 669 (40.9%) were overweight, and 492 (30.1%) were obese. Patients who were overweight or had obesity were younger, and there were more women in the obese group. Normal-weight patients more often had pre-existing conditions such as malignancy, or were organ recipients. During admission, patients who were overweight or had obesity had an increased probability of acute respiratory distress syndrome [OR 1.70 (1.26-2.30) and 1.40 (1.01-1.96)], respectively and acute kidney failure [OR 2.29 (1.28-3.76) and 1.92 (1.06-3.48)], respectively. Length of hospital stay was similar between groups. The overall in-hospital mortality rate was 27.7%, and multivariate logistic regression analyses showed that overweight and obesity were not associated with increased mortality compared to normal-weight patients. Conclusion: In this study, overweight and obesity were associated with acute respiratory distress syndrome and acute kidney injury, but not with in-hospital mortality nor length of hospital stay.
Assuntos
Injúria Renal Aguda/complicações , COVID-19/mortalidade , Mortalidade Hospitalar , Hospitalização , Obesidade/complicações , Síndrome do Desconforto Respiratório/complicações , Idoso , Feminino , Humanos , Unidades de Terapia Intensiva , Tempo de Internação , Masculino , Pessoa de Meia-Idade , Alta do Paciente , Respiração Artificial , Estudos Retrospectivos , Resultado do TratamentoRESUMO
OBJECTIVE: To establish whether one can build a mortality prediction model for COVID-19 patients based solely on demographics and comorbidity data that outperforms age alone. Such a model could be a precursor to implementing smart lockdowns and vaccine distribution strategies. METHODS: The training cohort comprised 2337 COVID-19 inpatients from nine hospitals in The Netherlands. The clinical outcome was death within 21 days of being discharged. The features were derived from electronic health records collected during admission. Three feature selection methods were used: LASSO, univariate using a novel metric, and pairwise (age being half of each pair). 478 patients from Belgium were used to test the model. All modeling attempts were compared against an age-only model. RESULTS: In the training cohort, the mortality group's median age was 77 years (interquartile range = 70-83), higher than the non-mortality group (median = 65, IQR = 55-75). The incidence of former/active smokers, male gender, hypertension, diabetes, dementia, cancer, chronic obstructive pulmonary disease, chronic cardiac disease, chronic neurological disease, and chronic kidney disease was higher in the mortality group. All stated differences were statistically significant after Bonferroni correction. LASSO selected eight features, novel univariate chose five, and pairwise chose none. No model was able to surpass an age-only model in the external validation set, where age had an AUC of 0.85 and a balanced accuracy of 0.77. CONCLUSION: When applied to an external validation set, we found that an age-only mortality model outperformed all modeling attempts (curated on www.covid19risk.ai) using three feature selection methods on 22 demographic and comorbid features.
Assuntos
COVID-19/mortalidade , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Bélgica/epidemiologia , COVID-19/diagnóstico , COVID-19/epidemiologia , Estudos de Coortes , Controle de Doenças Transmissíveis , Comorbidade , Registros Eletrônicos de Saúde , Feminino , Hospitalização , Humanos , Masculino , Pessoa de Meia-Idade , Países Baixos/epidemiologia , Prognóstico , Medição de Risco , Fatores de Risco , SARS-CoV-2/isolamento & purificaçãoRESUMO
OBJECTIVE: Develop and validate models that predict mortality of patients diagnosed with COVID-19 admitted to the hospital. DESIGN: Retrospective cohort study. SETTING: A multicentre cohort across 10 Dutch hospitals including patients from 27 February to 8 June 2020. PARTICIPANTS: SARS-CoV-2 positive patients (age ≥18) admitted to the hospital. MAIN OUTCOME MEASURES: 21-day all-cause mortality evaluated by the area under the receiver operator curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The predictive value of age was explored by comparison with age-based rules used in practice and by excluding age from the analysis. RESULTS: 2273 patients were included, of whom 516 had died or discharged to palliative care within 21 days after admission. Five feature sets, including premorbid, clinical presentation and laboratory and radiology values, were derived from 80 features. Additionally, an Analysis of Variance (ANOVA)-based data-driven feature selection selected the 10 features with the highest F values: age, number of home medications, urea nitrogen, lactate dehydrogenase, albumin, oxygen saturation (%), oxygen saturation is measured on room air, oxygen saturation is measured on oxygen therapy, blood gas pH and history of chronic cardiac disease. A linear logistic regression and non-linear tree-based gradient boosting algorithm fitted the data with an AUC of 0.81 (95% CI 0.77 to 0.85) and 0.82 (0.79 to 0.85), respectively, using the 10 selected features. Both models outperformed age-based decision rules used in practice (AUC of 0.69, 0.65 to 0.74 for age >70). Furthermore, performance remained stable when excluding age as predictor (AUC of 0.78, 0.75 to 0.81). CONCLUSION: Both models showed good performance and had better test characteristics than age-based decision rules, using 10 admission features readily available in Dutch hospitals. The models hold promise to aid decision-making during a hospital bed shortage.