scholarly journals Evaluation of N/LP Ratio as a Predictor of Disease Progression and Mortality in COVID-19 Patients Admitted to the Intensive Care Unit

2021 ◽  
Author(s):  
Başak Çakır Güney ◽  
Mert Hayıroğlu ◽  
Didar Şenocak ◽  
Vedat Çiçek ◽  
Tufan Çınar ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
Hospital Death ◽  
Survival Status ◽  
Inflammatory Index ◽  
Icu Stay

Objective: This research aimed to evaluate whether the neutrophil to lymphocyte and platelet (N/LP) ratio may be used to predict the risk of admission to the intensive care unit (ICU), the need for mechanical ventilation and in-hospital mortality in Coronavirus disease 2019 (COVID-19) cases. Methods: The study was conducted retrospectively on the data of 134 COVID-19 patients who were admitted to the ICU. The N/LP ratio was calculated as follows: neutrophil count x 100 / (lymphocyte count x platelet count). Each member of the research cohort was categorised into 1 of 2 groups based on their survival status (survivor and non-survivor groups). Results: In total, 82 (61%) patients died during the ICU stay. Patients who required mechanical ventilation and died in the ICU stay had significantly higher N/LP ratio than those who did not require it and survived [10 (IQR=4.94-19.38) vs 2.51 (IQR=1.67-5.49), p<0.001] and [11.27 (IQR=4.53-30.02) vs 1.65 (IQR=1-3.24), p<0.001], respectively. The N/LP ratio was linked with the requirement of mechanical ventilation and in-hospital death according to multivariable analysis. In receiver operating characteristic curve analysis, we found that N/LP in predicting admission to the ICU was >4.18 with 61% sensitivity and 62% specificity, it was >5.07 with 74% sensitivity and 73% specificity for the need for mechanical ventilation, and >3.69 with 81% sensitivity and 81% specificity to predict in-hospital death. Conclusion: To our knowledge, this is the first study showing that the N/LP ratio, which is a novel and widely applicable inflammatory index, may be used to predict the risk of ICU admission, mechanical ventilation and in-hospital death in patients with COVID-19 disease.

scholarly journals Clinical course and severity outcome indicators among COVID 19 hospitalized patients in relation to comorbidities distribution Mexican cohort

2020 ◽  
Author(s):  
Genny Carrillo ◽  
Nina Mendez Dominguez ◽  
Kassandra D Santos Zaldivar ◽  
Andrea Rochel Perez ◽  
Mario Azuela Morales ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Respiratory Diseases ◽  
Risk Estimation ◽  
Clinical Manifestations ◽  
Case Fatality ◽  
Hospitalized Patients ◽  
Hospital Death ◽  
Outcome Indicators

Introduction: COVID-19 affected worldwide, causing to date, around 500,000 deaths. In Mexico, by April 29, the general case fatality was 6.52%, with 11.1% confirmed case mortality and hospital recovery rate around 72%. Once hospitalized, the odds for recovery and hospital death rates depend mainly on the patients' comorbidities and age. In Mexico, triage guidelines use algorithms and risk estimation tools for severity assessment and decision-making. The study's objective is to analyze the underlying conditions of patients hospitalized for COVID-19 in Mexico concerning four severity outcomes. Materials and Methods: Retrospective cohort based on registries of all laboratory-confirmed patients with the COVID-19 infection that required hospitalization in Mexico. Independent variables were comorbidities and clinical manifestations. Dependent variables were four possible severity outcomes: (a) pneumonia, (b) mechanical ventilation (c) intensive care unit, and (d) death; all of them were coded as binary Results: We included 69,334 hospitalizations of laboratory-confirmed and hospitalized patients to June 30, 2020. Patients were 55.29 years, and 62.61% were male. Hospital mortality among patients aged<15 was 9.11%, 51.99% of those aged >65 died. Male gender and increasing age predicted every severity outcome. Diabetes and hypertension predicted every severity outcome significantly. Obesity did not predict mortality, but CKD, respiratory diseases, cardiopathies were significant predictors. Conclusion: Obesity increased the risk for pneumonia, mechanical ventilation, and intensive care admittance, but it was not a predictor of in-hospital death. Patients with respiratory diseases were less prone to develop pneumonia, to receive mechanical ventilation and intensive care unit assistance, but they were at higher risk of in-hospital death.

scholarly journals COVID outcome prediction in the emergency department (COPE): using retrospective Dutch hospital data to develop simple and valid models for predicting mortality and need for intensive care unit admission in patients who present at the emergency department with suspected COVID-19

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e051468
Author(s):  
David van Klaveren ◽  
Alexandros Rekkas ◽  
Jelmer Alsma ◽  
Rob J C G Verdonschot ◽  
Dick T J J Koning ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Outcome Prediction ◽  
Characteristic Curve ◽  
Hospital Death ◽  
Hospital Data ◽  
Dutch Hospital ◽  
Icu Admission ◽  
Second Wave

ObjectivesDevelop 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.DesignRetrospective.SettingSecondary care in four large Dutch hospitals.ParticipantsPatients 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 measuresWe 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.ResultsOf 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)).ConclusionsCOPE 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.

scholarly journals Incidence of Delirium in Critically Ill Cancer Patients

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Luis A. Sánchez-Hurtado ◽  
Nancy Hernández-Sánchez ◽  
Mario Del Moral-Armengol ◽  
Humberto Guevara-García ◽  
Francisco J. García-Guillén ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Cancer Patients ◽  
Critically Ill ◽  
Potential Risk ◽  
Assessment Method ◽  
Icu Stay ◽  
Potential Risk Factors

Objective. The aim of this study was to estimate the incidence of delirium and its risk factors among critically ill cancer patients in an intensive care unit (ICU). Materials and Methods. This is a prospective cohort study. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) was measured daily at morning to diagnose delirium by a physician. Delirium was diagnosed when the daily was positive during a patient’s ICU stay. All patients were followed until they were discharged from the ICU. Using logistic regression, we estimated potential risk factors for developing delirium. The primary outcome was the development of ICU delirium. Results. There were 109 patients included in the study. Patients had a mean age of 48.6 ± 18.07 years, and the main reason for admission to the ICU was septic shock (40.4%). The incidence of delirium was 22.9%. The mortality among all subjects was 15.6%; the mortality rate in patients who developed delirium was 12%. The only variable that had an association with the development of delirium in the ICU was the days of use of mechanical ventilation (OR: 1.06; CI 95%: 0.99–1.13;p=0.07). Conclusion. Delirium is a frequent condition in critically ill cancer patients admitted to the ICU. The duration in days of mechanical ventilation is potential risk factors for developing delirium during an ICU stay. Delirium was not associated with a higher rate of mortality in this group of patients.

Association of Healthcare Access With Intensive Care Unit Utilization and Mortality in Patients of Hispanic Ethnicity Hospitalized With COVID-19

2021 ◽  
Vol 16 (11) ◽  
Author(s):  
Ferdinand Velasco ◽  
Donghan M Yang ◽  
Minzhe Zhang ◽  
Tanna Nelson ◽  
Thomas Sheffield ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Clinical Outcomes ◽  
Disease Severity ◽  
Healthcare System ◽  
Multivariable Analysis ◽  
Hospital Death ◽  
Primary Language ◽  
Hispanic Patients ◽  
English Speaking

BACKGROUND: Racial and ethnic minority groups in the United States experience a disproportionate burden of COVID-19 deaths. OBJECTIVE: To evaluate whether outcome differences between Hispanic and non-Hispanic COVID-19 hospitalized patients exist and, if so, to identify the main malleable contributing factors. DESIGN, SETTING, PARTICIPANTS: Retrospective, cross-sectional, observational study of 6097 adult COVID-19 patients hospitalized within a single large healthcare system from March to November 2020. EXPOSURES: Self-reported ethnicity and primary language. MAIN OUTCOMES AND MEASURES: Clinical outcomes included intensive care unit (ICU) utilization and in-hospital death. We used age-adjusted odds ratios (OR) and multivariable analysis to evaluate the associations between ethnicity/language groups and outcomes. RESULTS: 32.1% of patients were Hispanic, 38.6% of whom reported a non-English primary language. Hispanic patients were less likely to be insured, have a primary care provider, and have accessed the healthcare system prior to the COVID-19 admission. After adjusting for age, Hispanic inpatients experienced higher ICU utilization (non-English-speaking: OR, 1.75; 95% CI, 1.47-2.08; English-speaking: OR, 1.13; 95% CI, 0.95-1.33) and higher mortality (non-English-speaking: OR, 1.43; 95% CI, 1.10-1.86; English-speaking: OR, 1.53; 95% CI, 1.19-1.98) compared to non-Hispanic inpatients. There were no observed treatment disparities among ethnic groups. After adjusting for age, Hispanic inpatients had elevated disease severity at admission (non-English-speaking: OR, 2.27; 95% CI, 1.89-2.72; English-speaking: OR, 1.33; 95% CI, 1.10-1.61). In multivariable analysis, the associations between ethnicity/language and clinical outcomes decreased after considering baseline disease severity (P < .001). CONCLUSION: The associations between ethnicity and clinical outcomes can be explained by elevated disease severity at admission and limited access to healthcare for Hispanic patients, especially non-English-speaking Hispanics.

scholarly journals Semiquantitative Cough Strength Score for Predicting Reintubation After Planned Extubation

2015 ◽  
Vol 24 (6) ◽  
pp. e86-e90 ◽  
Author(s):  
Jun Duan ◽  
Lintong Zhou ◽  
Meiling Xiao ◽  
Jinhua Liu ◽  
Xiangmei Yang
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Spontaneous Breathing ◽  
Operating Characteristic ◽  
Peak Flow ◽  
Characteristic Curve ◽  
Spontaneous Breathing Trial ◽  
Extubation Outcome ◽  
Cough Strength ◽  
Operating Characteristic Curve

Background Semiquantitative cough strength score (SCSS, graded 0–5) and cough peak flow (CPF) have been used to predict extubation outcome in patients in whom extubation is planned; however, the correlation of the 2 assessments is unclear. Methods In the intensive care unit of a university-affiliated hospital, 186 patients who were ready for extubation after a successful spontaneous breathing trial were enrolled in the study. Both SCSS and CPF were assessed before extubation. Reintubation was recorded 72 hours after extubation. Results Reintubation rate was 15.1% within 72 hours after planned extubation. Patients in whom extubation was successful had higher SCSSs than did reintubated patients (mean [SD], 3.2 [1.6] vs 2.2 [1.6], P = .002) and CPF (74.3 [40.0] vs 51.7 [29.4] L/min, P = .005). The SCSS showed a positive correlation with CPF (r = 0.69, P &lt; .001). Mean CPFs were 38.36 L/min, 39.51 L/min, 44.67 L/min, 57.54 L/min, 78.96 L/min, and 113.69 L/min in patients with SCSSs of 0, 1, 2, 3, 4, and 5, respectively. The discriminatory power for reintubation, evidenced by area under the receiver operating characteristic curve, was similar: 0.677 for SCSS and 0.678 for CPF (P = .97). As SCSS increased (from 0 to 1 to 2 to 3 to 4 to 5), the reintubation rate decreased (from 29.4% to 25.0% to 19.4% to 16.1% to 13.2% to 4.1%). Conclusions SCSS was convenient to measure at the bedside. It was positively correlated with CPF and had the same accuracy for predicting reintubation after planned extubation.

scholarly journals COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242127 ◽  
Author(s):  
Siegbert Rieg ◽  
Maja von Cube ◽  
Johannes Kalbhenn ◽  
Stefan Utzolino ◽  
Katharina Pernice ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Tertiary Care ◽  
Study Entry ◽  
Hospital Death ◽  
Care Model ◽  
Cox Regression Analysis ◽  
Hospitalised Patients

Background Reported mortality of hospitalised Coronavirus Disease-2019 (COVID-19) patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under state of the art care have not been systematically studied. Methods This retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced acute respiratory distress syndrome (ARDS) and extracorporeal membrane-oxygenation (ECMO) referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers. Results Between February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) ECMO support. Using multistate methodology, the estimated probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the intensive care unit (ICU) and 57% if mechanical ventilation was required at study entry. Age ≥65 years and male sex were predictors for in-hospital death. Predominant complications–as judged by two independent reviewers–determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications. Conclusion In a dynamic care model COVID-19-related in-hospital mortality remained very high. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.

scholarly journals Hemotransfusion and mechanical ventilation time are associated with intra-hospital mortality in patients with traumatic brain injury admitted to intensive care unit

2016 ◽  
Vol 74 (8) ◽  
pp. 644-649 ◽  
Author(s):  
Kelson James Almeida ◽  
Ânderson Batista Rodrigues ◽  
Luiz Euripedes Almondes Santana Lemos ◽  
Marconi Cosme Soares de Oliveira Filho ◽  
Brisa Fideles Gandara ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Traumatic Brain Injury ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Hospital Death ◽  
Factors Associated ◽  
Ventilation Time ◽  
Mechanical Ventilation Time

ABSTRACT Objective To identify the factors associated with the intra-hospital mortality in patients with traumatic brain injury (TBI) admitted to intensive care unit (ICU). Methods The sample included patients with TBI admitted to the ICU consecutively in a period of one year. It was defined as variables the epidemiological characteristics, factors associated with trauma and variables arising from clinical management in the ICU. Results The sample included 87 TBI patients with a mean age of 28.93 ± 12.72 years, predominantly male (88.5%). The intra-hospital mortality rate was of 33.33%. The initial univariate analysis showed a significant correlation of intra-hospital death and the following variables: the reported use of alcohol (p = 0.016), hemotransfusion during hospitalization (p = 0.036), and mechanical ventilation time (p = 0.002). Conclusion After multivariate analysis, the factors associated with intra-hospital mortality in TBI patients admitted to the intensive care unit were the administration of hemocomponents and mechanical ventilation time.

scholarly journals A study of dysnatremia in patients admitted in medical intensive care unit of a tertiary care teaching hospital

2021 ◽  
Vol 8 (2) ◽  
pp. 220
Author(s):  
Mantavya Patel ◽  
Sanjay Kumar Paliwal ◽  
Syed Javed
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Medical Intensive Care Unit ◽  
Tertiary Care ◽  
Female Ratio ◽  
Survival Status ◽  
Icu Stay ◽  
Significant Difference ◽  
Male Female Ratio ◽  
Medical Intensive Care

Background: Both dysnatremia at admission and that acquired in the intensive care unit (ICU) have been shown to have a direct influence on prognosis. The present was planned to study dysnatremia in adult patients admitting in medical intensive care unit (MICU).Methods: The present prospective observational study was conducted on patients admitted in medical ICU over a period of 1 year who developed dysnatremia during ICU stay. Patient’s age, sex, diagnosis at the time of diagnosis, comorbidities, serum sodium levels, risk factors, length of ICU stay, and survival status were noted.Results: Out of total 798 patients during the study period; 207 (25.94%) were found to have hypernatremia and 87 (10.9%) were hyponatremic. In hypernatremic group male/ female ratio was 125/82 and it was 50/37 in hyponatremic group. The mean ICU stay was significantly more in hypernatremic patients (4.76±3.57) compared to hyponatremic group (4.06±2.80). (p˂0.05) Mortality in both hypernatremic patients and hyponatremic patients was found significantly more in hypervolemic group which was 84.38% and 53.84% respectively. (p˂0.05)Conclusions: This study concluded that nowadays hypernatremia is more common with longer ICU stay. In both hypernatremia and hyponatremia mortality was found similar without any significant difference.

Complications and risk factors for severe outcome in children with measles

2019 ◽  
Vol 105 (9) ◽  
pp. 896-899 ◽  
Author(s):  
Andrea Lo Vecchio ◽  
Andrzej Krzysztofiak ◽  
Carlotta Montagnani ◽  
Piero Valentini ◽  
Nadia Rossi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Retrospective Study ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Operating Characteristic Curve ◽  
Organ Complications

Objective and designRisk factors for severe measles are poorly investigated in high-income countries. The Italian Society for Paediatric Infectious Diseases conducted a retrospective study in children hospitalised for measles from January 2016 to August 2017 to investigate the risk factors for severe outcome defined by the presence of long-lasting sequelae, need of intensive care or death.ResultsNineteen hospitals enrolled 249 children (median age 14.5 months): 207 (83%) children developed a complication and 3 (1%) died. Neutropaenia was more commonly reported in children with B3-genotype compared with other genotypes (29.5% vs 7.7%, p=0.01). Pancreatitis (adjusted OR [aOR] 9.19, p=0.01) and encephalitis (aOR 7.02, p=0.04) were related to severe outcome in multivariable analysis, as well as C reactive protein (CRP) (aOR 1.1, p=0.028), the increase of which predicted severe outcome (area under the receiver operating characteristic curve 0.67, 95% CI 0.52 to 0.82). CRP values >2 mg/dL were related to higher risk of complications (OR 2.0, 95% CI 1.15 to 3.7, p=0.01) or severe outcome (OR 4.13, 95% CI 1.43 to 11.8, p<0.01).ConclusionThe risk of severe outcome in measles is independent of age and underlying conditions, but is related to the development of organ complications and may be predicted by CRP value.

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