Predictive Risk Factors at Admission and a "Burning Point" During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19.
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ABSTRACT: Background
We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19).Methods
We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed.Results
Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028; 95% confidence interval (CI), 1.004-1.052], sequential organ failure assessment (SOFA) score (OR, 4.367; 95% CI, 3.230-5.903), neutrophil-to-lymphocyte ratio (NLR; OR, 1.094; 95% CI, 1.024-1.168), D-dimer (OR, 1.476; 95% CI, 1.107-1.968), lactate dehydrogenase (LDH; OR, 1.004; 95% CI, 1.001-1.006), international normalised ratio (INR; OR, 1.027; 95% CI, 0.999-1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358; 95% CI, 2.188-8.678], and large vs. small [OR, 9.567; 95% CI, 3.982-22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941-0.972) in the training set and an AUC of 0.958 (95% CI, 0.936-0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2; increase per day [I/d], +0.49), NLR (value, 10.61; I/d, +2.07), C-reactive protein (CRP; value, 46.9 mg/L; I/d, +4.95), glucose (value, 7.83 mmol/L; I/d, +0.2), D-dimer (value, 6.08 μg/L; I/d, +0.28), LDH (value, 461 U/L; I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L; I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization.Conclusion
The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.
SUBMITTER: Yin Z
PROVIDER: S-EPMC9291637 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundIdentifying factors that can predict severe disease in patients needing hospitalization for COVID-19 is crucial for early recognition of patients at greatest risk.Objective(1) Identify factors predicting intensive care unit (ICU) transfer and (2) develop a simple calculator for clinicians managing patients hospitalized with COVID-19.MethodsA total of 2,685 patients with laboratory-confirmed COVID-19 admitted to a large metropolitan health system in Georgia, USA between March and July 2020 were included in the study. Seventy-five percent of patients were included in the training dataset (admitted March 1 to July 10). Through multivariable logistic regression, we developed a prediction model (probability score) for ICU transfer. Then, we validated the model by estimating its performance accuracy (area under the curve [AUC]) using data from the remaining 25% of patients (admitted July 11 to July 31).ResultsWe included 2,014 and 671 patients in the training and validation datasets, respectively. Diabetes mellitus, coronary artery disease, chronic kidney disease, serum C-reactive protein, and serum lactate dehydrogenase were identified as significant risk factors for ICU transfer, and a prediction model was developed. The AUC was 0.752 for the training dataset and 0.769 for the validation dataset. We developed a free, web-based calculator to facilitate use of the prediction model (https://icucovid19.shinyapps.io/ICUCOVID19/).ConclusionOur validated, simple, and accessible prediction model and web-based calculator for ICU transfer may be useful in assisting healthcare providers in identifying hospitalized patients with COVID-19 who are at high risk for clinical deterioration. Triage of such patients for early aggressive treatment can impact clinical outcomes for this potentially deadly disease.
| S-EPMC7978341 | biostudies-literature
Project description:RationaleSleep disturbance during intensive care unit (ICU) admission is common and severe. Sleep disturbance has been observed in survivors of critical illness even after transfer out of the ICU. Not only is sleep important to overall health and well being, but patients after critical illness are also in a physiologically vulnerable state. Understanding how sleep disturbance impacts recovery from critical illness after hospital discharge is therefore clinically meaningful.ObjectivesThis Systematic Review aimed to summarize studies that identify the prevalence of and risk factors for sleep disturbance after hospital discharge for critical illness survivors.Data sourcesPubMed (January 4, 2017), MEDLINE (January 4, 2017), and EMBASE (February 1, 2017).Data extractionDatabases were searched for studies of critically ill adult patients after hospital discharge, with sleep disturbance measured as a primary outcome by standardized questionnaire or objective measurement tools. From each relevant study, we extracted prevalence and severity of sleep disturbance at each time point, objective sleep parameters (such as total sleep time, sleep efficiency, and arousal index), and risk factors for sleep disturbance.SynthesisA total of 22 studies were identified, with assessment tools including subjective questionnaires, polysomnography, and actigraphy. Subjective questionnaire studies reveal a 50-66.7% (within 1 mo), 34-64.3% (>1-3 mo), 22-57% (>3-6 mo), and 10-61% (>6 mo) prevalence of abnormal sleep after hospital discharge after critical illness. Of the studies assessing multiple time points, four of five questionnaire studies and five of five polysomnography studies show improved aspects of sleep over time. Risk factors for poor sleep varied, but prehospital factors (chronic comorbidity, pre-existing sleep abnormality) and in-hospital factors (severity of acute illness, in-hospital sleep disturbance, pain medication use, and ICU acute stress symptoms) may play a role. Sleep disturbance was frequently associated with postdischarge psychological comorbidities and impaired quality of life.ConclusionsSleep disturbance is common in critically ill patients up to 12 months after hospital discharge. Both subjective and objective studies, however, suggest that sleep disturbance improves over time. More research is needed to understand and optimize sleep in recovery from critical illness.
| S-EPMC5711402 | biostudies-literature
Project description:Initial differential diagnosis and prognosis for patients admitted to intensive care with suspected sepsis remain arduous. Hepcidin has emerged as a potential biomarker for sepsis. Here we report data on the relevance of levels of hepcidin versus other biomarkers as a diagnostic and prognostic tool for sepsis. 164 adult patients admitted to the intensive care unit (ICU) within 24 h upon arrival to the hospital were included. Blood samples collected daily for seven consecutive days and hepcidin levels, heparin binding protein (HBP) levels and standard biomarkers were determined. Blood cultures were initiated at inclusion. Clinical scores were evaluated daily and mortality after 28- and 180-days was recorded. One hundred of the patients were found to fulfil the criteria for sepsis whereas 64 did not. Hepcidin levels at admission were significantly higher in the septic than in the non-septic patients. In septic patients hepcidin levels declined significantly already at 24 h followed by a steady decline. A significant negative correlation was observed between hepcidin levels and SAPS 3 in patients with sepsis. Hepcidin levels at inclusion were significantly higher among septic patients that survived 180-days and predicted mortality. Our data show that hepcidin levels are indicative of sepsis in patients admitted to the ICU and has a prognostic value for mortality.
| S-EPMC9434539 | biostudies-literature
Project description:ObjectivesTo examine the association between hospitalization, critical illness, and infection occurring during middle- and late-life and structural brain abnormalities in older adults.DesignProspective cohort study.SettingAtherosclerosis Risk in Communities (ARIC) Study.ParticipantsA community sample of adults who were 44 to 66 years of age at study baseline.MeasurementsActive surveillance of local hospitals and annual participant contact were used to gather hospitalization information (including International Classification of Diseases, Ninth Revision, codes) on all participants over a 24-year surveillance period. Subsequently, a subset of participants underwent 3-Tesla brain magnetic resonance imaging (MRI) to quantify total and regional brain volumes, white matter hyperintensity (WMH) volume, and white matter microstructural integrity (fractional anisotropy (FA) and mean diffusivity (MD) as measured using diffusion tensor imaging (DTI)).ResultsOf the 1,689 participants included (mean age at MRI 76±5), 72% were hospitalized, 14% had a major infection, and 4% had a critical illness during the surveillance period. Using covariate-adjusted regression, hospitalization was associated with 0.12-standard deviation (SD) greater WMH volume (95% confidence interval (CI)=0.00-0.24) and poorer white matter microstructural integrity (0.17-SD lower FA, 95% CI=-0.27 to -0.06; 0.16-SD greater MD, 95% CI=0.07-0.25) than no hospitalization. There was a dose-dependent relationship between number of hospitalizations, smaller brain volumes, and lower white matter integrity (p-trends ≤.048). In hospitalized participants, critical illness was associated with smaller Alzheimer's disease (AD) signature region (-1.64 cm3 , 95% CI=-3.16 to -0.12); major infection was associated with smaller AD signature region (-1.28 cm3 , 95% CI=-2.21 to -0.35) and larger ventricular volume (3.79 cm3 , 95% CI= 0.81-6.77).ConclusionsWhereas all-cause hospitalization was primarily associated with lower white matter integrity, critical illness and major infection were associated with smaller brain volume, particularly within regions implicated in AD.
| S-EPMC6181772 | biostudies-literature
Project description:ImportanceAnemia is common and has been associated with poor outcomes in the critically ill population, yet the timing and extent of hemoglobin recovery remains incompletely described, which may have important implications for clinical outcomes following discharge from intensive care.ObjectivesTo describe longitudinal changes in anemia status during and after critical illness and assess the associations between hemoglobin concentrations and postdischarge mortality.Design, setting, and participantsA population-based cohort study was conducted from January 1, 2010, to December 31, 2016, in Olmsted County, Minnesota; data analysis was performed from June 1 to December 30, 2019. Participants included 6901 adults (age ≥18 years) admitted to intensive care.Main outcomes and measuresHemoglobin concentrations in the 12 months before hospitalization, during hospitalization, and in the 12 months after discharge, categorized by anemia severity (mild, hemoglobin ≥10.0 to <12.0 g/dL in women or ≥10.0 to <13.5 g/dL in men; moderate, hemoglobin ≥8.0 to <10.0 g/dL; and severe, hemoglobin <8.0 g/dL). Complete recovery from anemia, defined as attainment of nonanemic status by 12 months post hospitalization, and 12-month mortality were also evaluated.ResultsOf the 6901 patients included in the study, 3792 were men (55%); median (interquartile range [IQR]) age was 67 (IQR, 52-79) years. Prehospitalization hemoglobin concentrations were available in 83% of the population (n = 5694), with median hemoglobin concentrations of 13.1 (IQR, 11.6-14.4) g/dL. Forty-one percent of the patients (n = 2320) had anemia preceding hospitalization. Hemoglobin values at hospital discharge were 10.8 g/dL (IQR, 9.5-12.4 g/dL), with 80% (n = 5182 of 6460) having anemia: 58% mild, 39% moderate, and 3% severe. The prevalence of anemia post hospitalization was 56% (95% CI, 55%-58%) at 3 months, 52% (95% CI, 50%-54%) at 6 months, and 45% (95% CI, 43%-47%) at 12 months among those alive with available hemoglobin measurements. Rates of complete recovery from anemia at 12 months were 58% (95% CI, 56%-61%) for mild anemia, 39% (95% CI, 36%-42%) for moderate anemia, and 24% (95% CI, 15%-34%) for severe anemia. Of those without baseline anemia surviving hospitalization, 74% of the patients were anemic at hospital discharge, with rates of complete 12-month recovery of 73% (95% CI, 69%-76%) for mild anemia, 62% (95% CI, 57%-68%) for moderate anemia, and 59% (95% CI, 35%-82%) for severe anemia. Higher hospital discharge hemoglobin concentrations were associated with decreased mortality after multivariable adjustment (hazard ratio, 0.95 per 1-g/dL increase; 95% CI, 0.90-0.99, P = .02).Conclusions and relevanceThe findings of this study suggest that anemia is common and often persistent in the first year after critical illness. Further studies are warranted to identify distinct anemia recovery profiles and assess associations with clinical outcomes.
| S-EPMC7516623 | biostudies-literature
Project description:BackgroundWe have previously demonstrated that elevated serum estradiol (E(2)) at intensive care unit (ICU) admission is associated with death in the critically ill, regardless of sex. However, little is known about how changes in initial E(2) during the course of care might signal increasing patient acuity or risk of death. We hypothesized that changes from baseline serum E(2) during the course of critical illness are more strongly associated with mortality than a single E(2) level at admission.Study designA prospective cohort of 1,408 critically ill or injured nonpregnant adult patients requiring ICU care for ≥48 hours with admission and subsequent E(2) levels was studied. Demographics, illness severity, and E(2) levels were examined, and the probability of mortality was modeled with multivariate logistic regression. Changes in E(2) were examined by both analysis of variance and logistic regression.ResultsOverall mortality was 14.1% [95% confidence interval (CI) 12.3% to 16%]. Both admission and subsequent E(2) levels were independently associated with mortality [admission E(2) odds ratio 1.1 (CI 1.0 to 1.2); repeat estradiol odds ratio 1.3 (CI 1.2 to1.4)], with subsequent values being stronger. Changes in E(2) were independently associated with mortality [odds ratio 1.1 (CI 1.0 to 1.16)] and improved regression model performance. The regression model produced an area under the receiver operating characteristic curve of 0.80 (CI 0.77 to 0.83).ConclusionsAlthough high admission levels of E(2) are associated with mortality, changes from baseline E(2) in critically ill or injured adults are independently associated with mortality. Future studies of E(2) dynamics may yield new indicators of patient acuity and illuminate underlying mechanisms for targeted therapy.
| S-EPMC3073628 | biostudies-literature
Project description:Background and aimsRisk factors for poor outcomes after critical illness are incompletely understood. While nutritional risk is associated with mortality in critically ill patients, its association with disability, cognitive, and health-related quality of life is unclear in survivors of critical illness. This study's objective was to determine whether greater nutritional risk at ICU admission is associated with greater disability, worse cognition, and worse HRQOL at 3 and 12-month follow-up.MethodsWe enrolled adults (≥18 years of age) with respiratory failure or shock treated in medical and surgical intensive care units from two U.S. centers. We measured nutritional risk using the modified Nutrition Risk in Critically Ill (mNUTRIC) score (range 0-9 [highest risk]) at intensive care unit admission. We measured associations between mNUTRIC scores and discharge destination, disability in basic activities of daily living (ADLs) using the Katz ADL, instrumental ADLs using the Functional Activities Questionnaire (FAQ), global cognition using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), executive function using the Trail Making Test Part B (Trails B), and health-related quality of life using the SF-36, adjusting for sex, education, BMI, baseline frailty, disability, and cognition, severity of illness, days of delirium, coma, and mechanical ventilation.ResultsOf the 821 patients enrolled in the ICU, 636 patients survived to hospital discharge. We assessed outcomes in 448 of 535 survivors (84%) at 3 months and 382 of 476 survivors (80%) at 12 months. Higher mNUTRIC scores predicted greater odds of discharge to an institution (OR 2.0, 95% CI: 1.6 to 2.6; P < 0.01). Higher mNUTRIC scores were associated with a trend towards greater disability in basic activities of daily living (IRR 1.3, 95% CI 1.0 to 1.7) at 3 months that did not reach significance (p = 0.09) with no association demonstrated at 12 months. There were no associations between mNUTRIC scores and FAQ, RBANS, or Trails B scores. mNUTRIC scores were inconsistently associated with SF-36 physical and mental component scale scores.ConclusionsGreater nutritional risk at ICU admission is associated with disability in survivors of critical illness. Future studies should evaluate interventions in those at high nutritional risk as a means to speed recovery.
| S-EPMC8243837 | biostudies-literature
Project description:For patients recovering from severe acute illness, admission to a long-term acute care hospital (LTAC) is an increasingly common alternative to continued management in an intensive care unit (ICU).To examine the effectiveness of LTAC transfer in patients with chronic critical illness.Retrospective cohort study in United States hospitals from 2002 to 2006.Medicare beneficiaries with chronic critical illness, defined as mechanical ventilation and at least 14 days of intensive care.Survival, costs, and hospital readmissions. We used multivariate analyses and instrumental variables to account for differences in patient characteristics, the timing of LTAC transfer, and selection bias.A total of 234,799 patients met our definition of chronic critical illness. Of these, 48,416 (20.6%) were transferred to an LTAC. In the instrumental variable analysis, patients transferred to an LTAC experienced similar survival compared with patients who remained in an ICU [adjusted hazard ratio=0.99; 95% confidence interval (CI), 0.96 to 1.01; P=0.27). Total hospital-related costs in the 180 days after admission were lower among patients transferred to LTACs (adjusted cost difference=-$13,422; 95% CI, -26,662 to -223, P=0.046). This difference was attributable to a reduction in skilled nursing facility admissions (adjusted admission rate difference=-0.591; 95% CI, -0.728 to -0.454; P<0.001). Total Medicare payments were higher (adjusted cost difference=$15,592; 95% CI, 6343 to 24,842; P=0.001).Patients with chronic critical illness transferred to LTACs experience similar survival compared with patients who remain in ICUs, incur fewer health care costs driven by a reduction in postacute care utilization, however, invoke higher overall Medicare payments.
| S-EPMC3500575 | biostudies-literature
Project description:ObjectiveTo investigate the clinical outcomes of patients with rheumatoid arthritis (RA) with COVID-19.MethodsThis retrospective study consisted of 361 patients with RA+ and 45,954 patients with RA- (March 2020 to August 2022) who tested positive for SARS-CoV-2 by polymerase-chain-reaction in the Montefiore Health System, which serves a large low-income, minority-predominant population in the Bronx and was an epicenter of the initial pandemic and subsequent surges. Primary outcomes were hospitalization, critical illness, and all-cause mortality associated with SARS-CoV-2 infection. Comparisons were made with and without adjustment for covariates, as well as with 1083 matched controls of patients with RA- and COVID-19.ResultsPatients with RA+ and COVID-19 were older (62.2 ± 23.5 vs. 45.5 ± 26.3; P < 0.001), were more likely females (83.1% vs. 55.8%; P < 0.001), were Black (35.5% vs. 30.3%; P < 0.05), and had higher rates of comorbidities (P < 0.05), hospitalization (52.4% vs. 32.5%; P < 0.005), critical illness (10.5% vs. 6.9%; P < 0.05), and mortality (11.1% vs. 6.2%; P < 0.01) compared with patients with RA- and COVID-19. Patients with RA+ with COVID-19 had higher odds of critical illness (adjusted odds ratio [aOR] = 1.46, 95% confidence interval [CI]: 1.09-1.93; P = 0.008) but no differences in hospitalization (aOR = 1.18 [95% CI: 0.93-1.49]; P = 0.16) and mortality (aOR = 1.34 [95% CI: 0.92-1.89]; P = 0.10) after adjusting for covariates. Odds ratio analysis identified age, hospitalization status, female sex, chronic kidney disease, chronic obstructive pulmonary disease, and Black race to be significant risk factors for COVID-19-related mortality. Pre-COVID-19 steroid and biologic therapy to treat RA were not significantly associated with worse outcomes (P > 0.05). Outcomes were not different between patients with RA+ and propensity-matched RA- controls (P > 0.05).ConclusionOur findings suggest that risk factors for adverse COVID-19 outcomes were not attributed to RA per se but rather age and preexisting medical conditions of patients with RA.
| S-EPMC10502846 | biostudies-literature
Project description:ContextStudies suggest that many survivors of critical illness experience long-term cognitive impairment but have not included premorbid measures of cognitive functioning and have not evaluated risk for dementia associated with critical illness.ObjectivesTo determine whether decline in cognitive function was greater among older individuals who experienced acute care or critical illness hospitalizations relative to those not hospitalized and to determine whether the risk for incident dementia differed by these exposures.Design, setting, and participantsAnalysis of data from a prospective cohort study from 1994 through 2007 comprising 2929 individuals 65 years old and older without dementia at baseline residing in the community in the Seattle area and belonging to the Group Health Cooperative. Participants with 2 or more study visits were included, and those who had a hospitalization for a diagnosis of primary brain injury were censored at the time of hospitalization. Individuals were screened with the Cognitive Abilities Screening Instrument (CASI) (score range, 0-100) every 2 years at follow-up visits, and those with a score less than 86 underwent a clinical examination for dementia.Main outcome measuresScore on the CASI at follow-up study visits and incident dementia diagnosed in study participants, adjusted for baseline cognitive scores, age, and other risk factors.ResultsDuring a mean (SD) follow-up of 6.1 (3.2) years, 1601 participants had no hospitalization, 1287 had 1 or more noncritical illness hospitalizations, and 41 had 1 or more critical illness hospitalizations. The CASI score was assessed more than 45 days after discharge for 94.3% of participants. Adjusted CASI scores averaged 1.01 points lower for visits following acute care illness hospitalization compared with follow-up visits not following any hospitalization (95% confidence interval [CI], -1.33 to -0.70; P < .001) and 2.14 points lower on average for visits following critical illness hospitalization (95% CI, -4.24 to -0.03; P = .047). There were 146 cases of dementia among those not hospitalized, 228 cases of dementia among those with 1 or more noncritical illness hospitalizations, and 5 cases of dementia among those with 1 or more critical illness hospitalizations. The adjusted hazard ratio for incident dementia was 1.4 following a noncritical illness hospitalization (95% CI, 1.1 to 1.7; P = .001) and 2.3 following a critical illness hospitalization (95% CI, 0.9 to 5.7; P = .09).ConclusionsAmong a cohort of older adults without dementia at baseline, those who experienced acute care hospitalization and critical illness hospitalization had a greater likelihood of cognitive decline compared with those who had no hospitalization. Noncritical illness hospitalization was significantly associated with the development of dementia.
| S-EPMC2943865 | biostudies-literature