Strong Predictor Of Severity Research Articles

Non-Thyroidal Illness Syndrome: A Pattern of Thyroid Dysfunction Seen in Intensive Care Unit Patients of a Tertiary Care Centre

Introduction: The response to the endocrine mechanism including thyroid gland hormones to critical illness is a complex phenomenon.1 There is a marked and distinct changes in the levels of thyroid hormones in critical illness.2 The magnitude of the decrease in circulating tri-iodothyronine (fT3) levels (also known as non-thyroidal illness) during the first 24 hour after the onset of acute illness reflects the severity of illness and correlates with mortality. The study aims to evaluate the thyroid function test (TFT) of critically ill patients. The results of the study will be helpful in determining the thyroid picture of the critically ill patients in our setting and definitely help in assessing the outcome of the patient admitted in ICU or ward.
 Materials and Methods: This is a hospital based cross sectional study. A total of 150 cases with the critical illness assessed as per Acute Physiology and Chronic Health Evaluation II (APACHE II) score were enrolled in the study from 12th December 2021 to 15th June, 2022. Informed written consent and ethical approval were taken.
 Results: The majority of the cases (52%) were of geriatric age group with the mean age of 57 years. Majority of the study participants (42%) in APACHE II were from 20–24 across all participants, and both sexes. Fifty‑one percent of the patients had reduced fT3 levels. There was an increase in percentage of patients with decreased fT3 levels with increasing APACHE II score, compared to normal fT3 levels at similar APACHE II score and the distribution was found to be statistically significant (p = 0.0233). Of the 68 patients expired, 52 of them had low fT3 levels whereas only 16 cases expired were with the normal fT3 level, making it a strong predictor of severity and outcome.
 Conclusion: Decrease in the levels of fT3, a condition of non-thyroidal illness, is a crucial prognostic indicator in critically ill patients which in coordination APACHE Score II can be helpful in clinical settings to predict the severity and outcome of such patients.

Electrophysiological biomarkers of brain function in CDKL5 deficiency disorder.

CDKL5 deficiency disorder is a debilitating developmental and epileptic encephalopathy for which no targeted treatment exists. A number of promising therapeutics are under development for CDKL5 deficiency disorder but a lack of validated biomarkers of brain function and clinical severity may limit the ability to objectively assess the efficacy of new treatments as they become available. To address this need, the current study quantified electrophysiological measures in individuals with CDKL5 deficiency disorder and the association between these parameters and clinical severity. Visual and auditory evoked potentials, as well as resting EEG, were acquired across 5 clinical sites from 26 individuals with CDKL5 deficiency disorder. Evoked potential and quantitative EEG features were calculated and compared with typically developing individuals in an age- and sex-matched cohort. Baseline and Year 1 data, when available, were analysed and the repeatability of the results was tested. Two clinician-completed severity scales were used for evaluating the clinical relevance of the electrophysiological parameters. Group-level comparisons revealed reduced visual evoked potential amplitude in CDKL5 deficiency disorder individuals versus typically developing individuals. There were no group differences in the latency of the visual evoked potentials or in the latency or amplitude of the auditory evoked potentials. Within the CDKL5 deficiency disorder group, auditory evoked potential amplitude correlated with disease severity at baseline as well as Year 1. Multiple quantitative EEG features differed between CDKL5 deficiency disorder and typically developing participants, including amplitude standard deviation, 1/f slope and global delta, theta, alpha and beta power. Several quantitative EEG features correlated with clinical severity, including amplitude skewness, theta/delta ratio and alpha/delta ratio. The theta/delta ratio was the overall strongest predictor of severity and also among the most repeatable qEEG measures from baseline to Year 1.Together, the present findings point to the utility of evoked potentials and quantitative EEG parameters as objective measures of brain function and disease severity in future clinical trials for CDKL5 deficiency disorder. The results also underscore the utility of the current methods, which could be similarly applied to the identification and validation of electrophysiological biomarkers of brain function for other developmental encephalopathies.

IL-6 and other biomarkers as predictors of severity in COVID-19

Objective Cytokine release syndrome is suggested to be the most important mechanism triggering acute respiratory distress syndrome and end organ damage in COVID-19. The severity of disease may be measured by different biomarkers. Methods We studied markers of inflammation and coagulation as recorded in 29 patients on admission to the hospital in order to identify markers of severe COVID-19 and need of ICU. Results Patients who were eventually admitted to ICU displayed significantly higher serum levels of interleukin-6 (IL-6), C-reactive protein (CRP), and procalcitonin. No statistical differences were found between the groups in median levels of lymphocytes, D-dimer or ferritin. Conclusions IL-6 and CRP were the strongest predictors of severity in hospitalized patients with COVID-19.

Lymphocyte Count is a Universal Predictor to the Health Status and Outcomes of Patients with Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-Regression Analysis

Background: This study aimed to evaluate the prediction capabilities of clinical laboratory biomarkers to the prognosis of COVID-19 patients. Methods: Observational studies reporting at least 30 cases of COVID-19 describing disease severity or mortality were included. Meta-data of demographics, clinical symptoms, vital signs, comorbidities, and 14 clinical laboratory biomarkers on initial hospital presentation were extracted. Taking the outcome group as the analysis unit, meta-regression analysis with the generalized estimating equations (GEE) method for clustered data was performed sequentially. The unadjusted effect of each potential predictor of the three binary outcome variables (i.e., severe vs. non-severe, critically severe vs. non-critically severe, and dead vs. alive) was examined one by one by fitting three series of simple GEE logistic regression models due to missing data. The worst one was dropped one at a time. Then, a final multiple GEE logistic regression model for each of the three outcome variables was obtained. Findings: Meta-data was extracted from 76 articles, reporting a total of 26,627 cases of COVID-19. Patients were recruited across 16 countries. The number of studies (patients) included in the final models of the analysis for severity, critical severity, and mortality was 38 studies (9,764 patients), 21 studies (4,792 patients), and 24 studies (14,825 patients), respectively. After adjusting for the effect of age, lymphocyte count mean or median ≤ 1.03 (estimated hazard ratio [HR] = 46.2594, p Interpretation: Lymphocyte count should be closely watched for COVID-19 patients in clinical practice.Funding: None to declare. Declaration of Interest: None to declare.

Vascular Endothelial Growth Factor as Predictive Biomarker for Stroke Severity and Outcome; An Evaluation of a New Clinical Module in Acute Ischemic Stroke.

The need to study prognosis after incidence of acute ischemic stroke (AIS) has fueled researchers to identify predictors apart from neurological, functional, or disability measures. The purpose of this study was to test and validate a newly developed clinico-biomarker assessment module in AIS and also to investigate the role of serum vascular endothelial growth factor (VEGF) after AIS. A randomized controlled study with sample size of 250 patients suffering from AIS within 2 weeks of the index event were conducted and followed up for a period of three months. Age, gender, stroke subtype, previous stroke history, dysarthria, stroke localization, wakeup strokes, and Glasgow Coma Scale (GCS) were dichotomized as present or absent using the National Institute of Health Stroke Scale (NIHSS) which consists of four subcategories. The additional serum VEGF was scored between 1 and 4 (0-200 = 1, 200-300 = 2, 300-400 = 3, and 400-500 = 4). All these were summed under a clinical biomarker (CB) module with highest score of 30. The mean VEGF in 125 patients was 378.4 + 98.9 pg/ml, indicating a moderately high increase with a score of 3 on CB module. Multiple regression analysis revealed that the CB model was fit to predict prognosis and severity [R2 = 0.86, F (23.4, 6);P = 0.001], with NIHSS subscore, prestroke status, and VEGF being very strong predictors. When only the clinical module was tested on all 250 patients, it was found that the NIHSS subscore, time to stroke onset and prestroke functional status were the most common [R2 = 0.79; F (45,9);P = 0.005]. This study demonstrates that VEGF is highly upregulated in AIS with severe disability as compared to healthy controls. This biomarker is a strong predictor of severity and functionality when combined with clinical variables three months post the ishemic event.

Predicting Severe Pneumonia Outcomes in Children

Substantial morbidity and excessive care variation are seen with pediatric pneumonia. Accurate risk-stratification tools to guide clinical decision-making are needed. We developed risk models to predict severe pneumonia outcomes in children (<18 years) by using data from the Etiology of Pneumonia in the Community Study, a prospective study of community-acquired pneumonia hospitalizations conducted in 3 US cities from January 2010 to June 2012. In-hospital outcomes were organized into an ordinal severity scale encompassing severe (mechanical ventilation, shock, or death), moderate (intensive care admission only), and mild (non-intensive care hospitalization) outcomes. Twenty predictors, including patient, laboratory, and radiographic characteristics at presentation, were evaluated in 3 models: a full model included all 20 predictors, a reduced model included 10 predictors based on expert consensus, and an electronic health record (EHR) model included 9 predictors typically available as structured data within comprehensive EHRs. Ordinal regression was used for model development. Predictive accuracy was estimated by using discrimination (concordance index). Among the 2319 included children, 21% had a moderate or severe outcome (14% moderate, 7% severe). Each of the models accurately identified risk for moderate or severe pneumonia (concordance index across models 0.78-0.81). Age, vital signs, chest indrawing, and radiologic infiltrate pattern were the strongest predictors of severity. The reduced and EHR models retained most of the strongest predictors and performed as well as the full model. We created 3 risk models that accurately estimate risk for severe pneumonia in children. Their use holds the potential to improve care and outcomes.

Role of bioelectric impedance phase angle in ovarian malignancy: A hospital-based study

Background: A woman's risk at birth of having ovarian cancer at some point in her lifetime is 1-1.5% and mortality due to the disease is almost 0.5%. It accounts for 3% of all cancers in females. Despite a low contributory percentage, it remains the fifth leading cause of cancer related death. This is because most ovarian cancers are detected when they have spread beyond the ovary. Bioelectric Impedance Analysis (BIA) affords an emerging opportunity to assess prognosis because of its ability to non invasively assess cell and plasma membrane structure and function by means of phase angle. Aims: To compare the Phase Angle between patients of Ovarian Cancer and their matched control with the help of BIA. Settings and Design: After taking clearance from ethical committee a total of 33 female cases of histological proven serous cyst adenocarcinoma were included from the surgery in Patient Department, Department of surgery. Equal numbers of matched controls were recruited from the friends and relatives of cases. Subjects and Methods: BIA BODY STAT QUAD SCAN 4000 was used to measure resistance (R) and reactance (Xc) by recording a voltage drop in applied current. Phase angle is the ratio of reactance to resistance and is a measure of cell vitality. Statistical Analysis Used: Unpaired t-test and One Way ANOVA were applied. Results: In control group Phase angle showed a mean ± SEM 5.073 (0.0698) while in test group it showed a mean value ± SEM 3.536 (0.0616). Mean of stage I was 3.800 (0.1154) while that of stage II was 3.620 (0.2588). Means of stage III and IV are 3.275 (0.158) and 2.90 (0.141) respectively. One Way ANOVA was applied to see any significant differences among the phase angle values of all stages. The results were statistically significant. The smaller the phase angle values higher was the Malignant Tumours (TNM) staging. Conclusions: The phase angles differed significantly from the healthy age matched control values and also among the stages. This study demonstrated that phase angle is a strong predictor of severity and prognosis of ovarian cancer and differed significantly between the groups. Further studies are required to validate its role as a screening and prognostic tool.

The role of citrullinated protein antibodies in predicting erosive disease in rheumatoid arthritis: a systematic literature review and meta-analysis.

Background. Autoantibodies to citrullinated peptides have been shown to be valuable in the diagnosis of rheumatoid arthritis (RA). The expanding repertoire of antibodies to citrullinated peptide antigens (ACPA) has been a topic of great interest in recent reviews and research studies, as has the ability of these autoantibodies to predict disease outcome. Objectives. The aim of this review was to provide an update on the relevance of ACPA as prognostic markers in RA. The ability to identify patients predisposed to an aggressive outcome at the time of initial diagnosis greatly facilitates the selection of appropriate and cost-effective treatment. Methods. A systematic review of the literature was carried out. Studies from 1967 up to June 2014 with data on prognostic value of ACPA were included. Quality assessment was done by using the modified Hayden list for prognostic studies. Meta-analysis was performed using BioStat software. Results. The results of 25 studies were selected for the final review. A total of 6421 patients with RA were included, mainly in inception cohorts, with follow-up duration ranging from one year to ten years. All studies carried prognostic data on all available isotypes of anticyclic citrullinated protein (CCP), while four had data on antimutated citrullinated vimentin (MCV). There was a single relevant study each on anticitrullinated enolase peptide 1 (CEP1) and antichimaeric fibrin/filaggrin citrullinated peptide 1 (CFFCP1). All studies showed ACPA to be strong predictors of joint erosions in RA. Other factors, particularly baseline erosions, showed an additive effect. Anti-MCV appeared to be a marker of a more aggressive form of disease. Ten studies had data on which a meta-analysis could be performed. This gave an overall odds ratio of 4.85 for ACPA (anti-CCP/MCV) positivity being predictive for the development of joint erosions. Two studies with data on anti-CEP1 and anti-CFFCP1 also showed this positive predictive role of ACPA for joint erosions. Conclusions. ACPA are strong predictors of severity in RA. Their use should be part of routine rheumatology practice.

Bioelectric impedance phase angle in breast carcinoma

Context: Worldwide breast cancer is the most frequently diagnosed life threatening cancer and the leading cause of death in women. Bioelectric impedance analysis (BIA) affords an emerging opportunity to assess prognosis because of its ability to non invasively assess cell and plasma membrane structure and function by means of phase angle. Aims: To compare the phase angle between patients of breast cancer and their matched control with the help of BIA. Settings and Design: After taking clearance from ethical committee, a total of 34 female cases of histologically proven infiltrating ductal breast carcinoma were included from the surgery IPD, department of surgery. Equal numbers of the matched controls were recruited from the friends and relatives of cases. Materials and Methods: Bio Electrical Impedance Analyzer (BIA) BODY STAT QUAD SCAN 4000 was used to measure resistance (R) and reactance (Xc) by recording a voltage drop in applied current. Phase angle is the ratio of reactance to resistance and is a measure of cell vitality. Statistical analysis used: Unpaired t test was applied. Results: In control group, the phase angle showed a mean of 5.479 whereas in test group, it showed a mean value of 4.726. The P value showed a significant difference (P < 0.0001). The smaller the phase angle values were higher was the tumor, nodes, metastases (TNM) staging. The phase angles differed significantly from the healthy age matched control values. Conclusions: This study demonstrated that phase angle is a strong predictor of severity of breast cancer and differed significantly between the two groups.