Predictor Of Severity In Patients Research Articles

Lactic Acid Level as A Predictor of Severity in Patients with Acute Appendicitis

Lactic Acid Level as A Predictor of Severity in Patients with Acute Appendicitis

Systemic inflammatory response index as an independent predictor of severity in patients with obstructive sleep apnea

BackgroundChronic inflammation plays a crucial role in developing various cardiovascular and metabolic disorders. Obstructive sleep apnea (OSA) is a unique condition characterized by the coexistence of cardiovascular and metabolic disturbances, where chronic inflammation may exacerbate disease progression and severity. This study investigated how different hematological inflammatory cells and mediators can serve as predictive indicators of severe OSA.MethodsIn a retrospective cohort study, 150 patients suspected of having obstructive sleep apnea (OSA) underwent polysomnography (PSG) to confirm the diagnosis. Based on their apnea-hypopnea index (AHI), the patients were categorized into three groups: mild, moderate, and severe OSA. Blood samples were collected for the assessment of inflammatory blood cells and mediators at the time of diagnosis.ResultsAmong the 150 patients studied, 90 were diagnosed with OSA, and 43 had severe OSA, representing a prevalence rate of 47.7%. Patients with severe OSA were notably older and more likely to have diabetes mellitus and hypertension. After adjusting for age and sex, each one-unit increase in Systemic Inflammatory Response Index (SIRI), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) levels was associated with a doubling in the likelihood of having moderate and severe OSA (p < 0.05 for all). However, hypertension was linked to a 16-fold increase in the likelihood of moderate and severe OSA (p = 0.01).ConclusionOur research indicates that comorbidity and inflammatory cells and markers (SIRI, CRP, and ESR) are significantly related to the severity of OSA.

Role of Platelet to Lymphocyte Ratio (PLR) and its Correlation with NIHSS (National Institute of Health Stroke Scale) for Prediction of Severity in Patients of Acute Ischemic Stroke

Role of Platelet to Lymphocyte Ratio (PLR) and its Correlation with NIHSS (National Institute of Health Stroke Scale) for Prediction of Severity in Patients of Acute Ischemic Stroke

Urine Albumin/Creatinine Ratio and Serum Uric Acid as Predictors of Severity in Patients with Chronic Obstructive Pulmonary Disease

Background and Objective: As a global healthcare issue, Chronic Obstructive Pulmonary Disease (COPD) is mainly associated with smoking. Nonetheless, environmental and occupational issues are also linked to its development. The present study aimed to assess the urine albumin-to-creatinine ratio (ACR) and serum uric acid (SUA) levels as predictors of disease severity in COPD patients. Materials and Methods: This cross-sectional study was conducted on 67 patients diagnosed with COPD using the Global Initiative for Obstructive Lung Disease diagnostic criteria. The participants were patients who were either referred to the subspecialty clinic of the pulmonology and spirometry unit of Hamadan Shahid Beheshti Hospital or were hospitalized in the pulmonology ward. Blood and urine samples were taken from the COPD patients, and the serum uric acid, urine albumin, and urine creatinine levels were assessed and recorded in a checklist. The data were analyzed in SPSS software (version 23) at a significance level of 0.05. Results: In terms of gender, 5.7% of the participants were male and 34.3% were female. The mean age of patients was 61.77 years. The stages of disease severity in the patients were as follows: 20.89%, 22.38%, 5.73%, and 2.98% of cases had very severe, severe, moderate, and mild COPD, respectively. The regression analysis results demonstrated that SUA levels could significantly predict the FEV1 in COPD patients; nonetheless, urine ACR could not predict the FEV1 scores. Conclusion: As evidenced by the result of the present study, the FEV1 in COPD patients and disease severity could be predicted by the SUA levels. Therefore, it is recommended to consider monitoring and assessing non-pulmonary factors, especially SUA levels, in the treatment of COPD patients.

Role of Serum Procalcitonin in Prediction of Severity in Patients with Acute Cholangitis

Abstract Background Cholangitis is one of the commonest emergencies encountered by gastroenterologists that may warrant drainage of biliary system. Serum procalcitonin (PCT) is an important biomarker of cholangitis with a potential to guide early therapeutic decision. Materials and Methods We did a retrospective analysis of prospectively maintained data of patients admitted in the hospital from March 2018 to September 2020 with a diagnosis of acute cholangitis based on Tokyo 18 guidelines (TG-18). All the demographic parameters, biochemical and hematological parameters, and the result were recorded. Results One-hundred two patients were admitted to our hospital with a mean age of 51.07 ± 7.99 years, among which 58.5% (59/102) were females with most common etiology being choledocholithiasis (64%). Fever, jaundice, and abdominal pain were seen in 78% (80/102), 73.3% (74/102), and 76.9% (78/102) of patients, respectively. Organ failure was seen in 29.3% (29/102) of patients with most common organ failure being acute kidney injury. Mild, moderate, and severe cholangitis as per TG-13 was seen in 43.9, 26.8, and 29.3% of patients, respectively. Elevated PCT levels were associated with severe disease (76.7 vs. 26.5%, p &lt; 0.05). Forty-three percent (44/102) patients were managed with delayed biliary drainage, while the majority of remaining specifically with raised PCT levels needed early endoscopic intervention. Conclusion In this retrospective analysis, we showed that most common etiology of cholangitis in was choledocholithiasis. Raised serum PCT levels were significantly associated with increased severity of cholangitis.

The Prognostic Consequence of Red Cell Distribution Width in Acute Pancreatitis

INTRODUCTION&#x0D; Acute pancreatitis is commonly a self-limiting disease but, about 25% of patients consequently develop a severe pancreatitis which leads to increase mortality. The available Scoring system is use to predicate severity of the Acute Pancreatitis, which is used for early diagnosis and management. Aim of this study is to assess the association of red blood cell distribution width (RDW) with severity and mortality in patients of acute pancreatitis.&#x0D; MATERIAL AND METHODS&#x0D; This retrospective study was carried out in Department of Surgery of National Medical College and Teaching Hospital. A total of 50 patients with diagnosis as acute pancreatitis over period of March 2020 to February 2022 was included. History and detailed clinical examination was performed as per the working proforma. Blood investigation was done. Data analysis was done using SPSS (Statistical Package for social sciences), version 25.&#x0D; RESULTS&#x0D; Mean age was 39.03 years. 68% cases were female. Acute Biliary was the most common cause. Mean RDW was 12.461, 14.50 and 15.309 in mild, moderate and severe Pancreatitis respectively with a p value of &lt;0.001 showing significant association of RDW and severity of Pancreatitis. Mean RDW in alive was 13.046 and 16.625 in death with a p value of &lt;0.001 showing signifi- cant association between RDW and outcome of acute Pancreatitis.&#x0D; CONCLUSION&#x0D; RDW is a predictor of severity in patients with severe acute pancreatitis.

Prospective validation of a transcriptomic severity classifier among patients with suspected acute infection and sepsis in the emergency department.

Background and importancemRNA-based host response signatures have been reported to improve sepsis diagnostics. Meanwhile, prognostic markers for the rapid and accurate prediction of severity in patients with suspected acute infections and sepsis remain an unmet need. IMX-SEV-2 is a 29-host-mRNA classifier designed to predict disease severity in patients with acute infection or sepsis.ObjectiveValidation of the host-mRNA infection severity classifier IMX-SEV-2.Design, settings and participantsProspective, observational, convenience cohort of emergency department (ED) patients with suspected acute infections.Outcome measures and analysisWhole blood RNA tubes were analyzed using independently trained and validated composite target genes (IMX-SEV-2). IMX-SEV-2-generated risk scores for severity were compared to the patient outcomes in-hospital mortality and 72-h multiorgan failure.Main resultsOf the 312 eligible patients, 22 (7.1%) died in hospital and 58 (18.6%) experienced multiorgan failure within 72 h of presentation. For predicting in-hospital mortality, IMX-SEV-2 had a significantly higher area under the receiver operating characteristic (AUROC) of 0.84 [95% confidence intervals (CI), 0.76–0.93] compared to 0.76 (0.64–0.87) for lactate, 0.68 (0.57–0.79) for quick Sequential Organ Failure Assessment (qSOFA) and 0.75 (0.65–0.85) for National Early Warning Score 2 (NEWS2), (P = 0.015, 0.001 and 0.013, respectively). For identifying and predicting 72-h multiorgan failure, the AUROC of IMX-SEV-2 was 0.76 (0.68–0.83), not significantly different from lactate (0.73, 0.65–0.81), qSOFA (0.77, 0.70–0.83) or NEWS2 (0.81, 0.75–0.86).ConclusionThe IMX-SEV-2 classifier showed a superior prediction of in-hospital mortality compared to biomarkers and clinical scores among ED patients with suspected infections. No improvement for predicting multiorgan failure was found compared to established scores or biomarkers. Identifying patients with a high risk of mortality or multiorgan failure may improve patient outcomes, resource utilization and guide therapy decision-making.

Clinical frailty scale as a predictor of disease severity in patients hospitalised with COVID-19 – an observational cohort study

Background The coronavirus disease 2019 pandemic makes proper resource allocation and prioritisation important. Frailty increases the risk of adverse outcomes and can be quantified using the Clinical frailty scale. The aim of this study was to determine the role of the Clinical frailty scale, in patients ≥65 years of age with coronavirus disease 2019, as a risk factor either for critical coronavirus disease 2019 measured as intensive care unit admission or death or as a risk factor for death. Methods This was a retrospective observational study on patients ≥65 years hospitalised with coronavirus disease 2019 verified by polymerase chain reaction between 5 March 5 and 5 July 2020. The association between Clinical frailty scale and the composite primary outcome intensive care unit admission or death within 30 days post hospitalisation and the secondary outcome death within 30 days post hospitalisation was analysed using multivariable logistic regression models adjusting for gender, age, body mass index, hypertension, and diabetes. Clinical frailty scale was used as a categorical variable (fit score 1–4, frail score 5–6, and severely frail score 7–9). Results In total, 169 patients were included (47.3% women, mean age 79.2 ± 7.8 years). In the fully adjusted model, adjusted odds ratio for intensive care unit admission or death was 1.84 (95%-confidence interval 0.67–5.03, p = .234) for frail and 6.08 (1.70–21.81, p = .006) for severely frail compared to fit patients. For death, adjusted odds ratio was 2.81 (0.89–8.88, p = .079) for frail and 9.82 (2.53–38.10, p = .001) for severely frail compared to fit patients. Conclusions A high Clinical frailty scale score was an independent risk factor for the composite outcome intensive care unit admission or death and for the secondary outcome death.

Criteria and potential predictors of severity in patients with COVID-19

BackgroundThe challenge in treating severe COVID-19 in the absence of targeted medication is enforcing physicians to search carefully for clinical predictors of severity.AimTo define the profile of patients at risk of severe COVID-19 and to assess for certain predictors.MethodsConfirmed COVID-19 cases were classified into the following: group A: mild/moderate cases and group B: severe/critical cases according to the selected criteria. History, radiological assessment, complete blood count, lactate dehydrogenase (LDH), myocardial enzymes, serum ferritin, and D dimer were assessed. Patients were followed for the need of ICU and mechanical ventilation. Duration till conversion, length of stay, and mortality were recorded.ResultsA total of 202 patients were analyzed. Group B had higher age (53.2 ± 12.6 vs 40.3 ± 10.3, P < 0.001), more prevalence of DM (60.61% vs 16.57% P < 0.001), hypertension (51.52% vs 20.12%, P < 0.001), ischemic heart (27.27% vs 3.55%, P < 0.001), bronchial asthma (36.36% vs 3.55%, P < 0.001), COPD (9.09% vs 1.18%, P = 0.03), higher mean platelet volume (MPV) (12.76 ± 7.13 vs 10.51 ± 7.78 (fL), P < 0.001), higher serum ferritin (954 ± 138 vs 447 ± 166 ng/ml, P < 0.001), higher LDH (604 ± 220 vs 384 ± 183 U/L, P-value < 0.001), higher creatine phosphokinase (24.27 ± 5.82 vs 16.4 ± 4.87 IU/L, P < 0.001), and higher mortality (30.3% vs 0.6%, P < 0.001). Multivariate regression of predictors of severity identified three predictors; age, MPV, serum ferritin, and IHD.ConclusionsThe current study places of interest the characteristic host-related features of severe COVID-19 and draws attention to potential predictors.

The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity

BackgroundUsing a personality typing approach, we investigated the relationship between personality profiles and the prediction of longterm illness severity in patients with bipolar disorder (BD). While previous research suggests associations between BD and traits from the NEO-FFI profiles, the current study firstly aimed to identify latent classes of NEO-FFI profiles, and, secondly, to examine their impact on the longterm prognosis of BD.MethodsBased on the NEO-FFI profiles of 134 euthymic patients diagnosed with BD (64.2% female, mean age = 44.3 years), successive latent profile analyses were conducted. Subsequently, a subsample (n = 80) was examined prospectively by performing multiple regression analysis of the latent classes to evaluate the longitudinal course of the disease (mean: 54.7 weeks) measured using a modified Morbidity Index.ResultsThe latent profile analyses suggested a 3-class model typifying in a resilient (n = 68, 51%), vulnerable (n = 55, 41%) and highly vulnerable (n = 11, 8%) class. In the regression analysis, higher vulnerability predicted a higher longterm Morbidity Index (R2 = 0.28).ConclusionsSubgroups of patients with BD share a number of discrete personality features and their illness is characterized by a similar clinical course. This knowledge is valuable in a variety of clinical contexts including early detection, intervention planning and treatment process.

Fibrinolytic markers could be useful predictors of severity in patients with pulmonary arterial hypertension: a retrospective study

BackgroundThe severity of pulmonary arterial hypertension (PAH) is classified based on mean pulmonary artery pressure (mPAP) levels. However, other markers have not been elucidated. Fibrinolytic markers, such as total plasminogen activator inhibitor-1 (tPAI-1) and thrombomodulin (TM), are known to reflect arterial endothelial function. However, the relationship between serum tPAI-1, TM and pulmonary circulation has not been completely determined.MethodsThis study included 100 consecutive patients (38 men), with a mean age of 68.9 ± 12.0 years, with cardiac diseases who underwent right heart catheterization. Serum coagulation and fibrinolytic marker levels were measured.ResultsThe average mPAP value was 25.1 ± 13.1 mmHg for all patients. The mPAP levels revealed a significant positive correlation with serum tPAI-1 (ρ = 0.24, p = 0.042) and uric acid (ρ = 0.29, p = 0.0031) levels. In the group with mPAP levels less than 25 mmHg (n = 58, ave. 17.3 ± 4.3 mmHg), mPAP levels showed a significant positive correlation with serum tPA-1 (ρ = 0.34, p = 0.034) and TM (ρ = 0.34, p = 0.043) values. The mean tPAI-1 (29.8 ± 23.3 ng/ml, p = 0.047) and uric acid (5.7 ± 1.8 mg/dl, p = 0.026) levels were significantly less in those with lower mPAP levels. A multivariate analysis revealed that tPAI-1 alone was a significant independent characteristic marker of PAH (odds ratio 1.02, 95%CI 1.000–1.036, p = 0.034).ConclusionsThese results indicate that serum tPAI-1 and TM may be useful predictors of severity, similar to mPAP in patients with PAH. They could be beneficial in predicting PAH among patients in the early stage of the disease.

Vitamin D deficiency as a predictor of severity in patients with COVID-19 infection.

As an immune modulator, vitamin D has been implicated in the coronavirus disease 2019 (COVID-19) severity. This study aimed to investigate the association between vitamin D levels and the severity of COVID-19 infection. A cross-sectional study, which included 124 patients diagnosed with COVID-19 and were selected from Ain Shams University Hospitals and assigned to two groups; mild and severe COVID-19. All patients underwent detailed history taking, clinical data, and different laboratory investigations as complete blood count, blood urea nitrogen, serum creatinine, liver enzymes, C-reactive protein, D-dimer, ferritin and serum vitamin D concentration. In addition to findings of initial chest computed tomography (CT) were recorded. COVID-19 Reporting and Data System (CO-RADS) and CT chest severity scores (CT SS) were reported. In this study of 124 COVID-19-positive individuals, a high prevalence of hypovitaminosis D was found (97.6%). Lower vitamin D levels were significantly associated with more severe COVID-19 cases (p-value < 0.001), higher blood levels of inflammatory markers including (D-dimer, CRP, and ferritin), a higher CT SS and longer disease duration. Serum vitamin D can be used as a predictor for the severity of COVID-19 infection with a specificity of 96.6%, and sensitivity of 45.5%. The high frequency of hypovitaminosis D in severe COVID-19 patients provides further evidence of a potential link to poor prognosis and severity of the disease, so vitamin D deficiency may be a marker of poor prognosis in these patients.

Disease progression velocity as predictor of severity in Guillain-Barre syndrome.

To identify the velocity of disease progression as a predictor of severity in patients with Guillain-Barre syndrome (GBS). Prospective observational study of patients with confirmed diagnosis of GBS between May and August 2019 in four hospitals in Peru. The disease progression velocity (DPV) was defined as the time since the onset of neurological symptoms and the maximum peak of neurological severity. Of 94 cases with GBS, the average age was 42 years; 73 (77.8%) patients presented severe GBS, the average hospital stay was 19 days; 45 (47.8%) patients haddiarrheal symptoms previously, in 63 (67.1%) patients the onset of motor weakness was located in the upper limbs and in 31 (32.9%) it was located in the lower limbs, 9 (10.0%) patients presented some type of dysautonomy; admission to mechanical ventilation was needed in 8 (8.5%) patients, and the deceased were 2 (2.0%). The DPV≤ 1 day has a 79% probability of developing severe disease, the two and three day DPV have the probability of 61% and 38% respectively of progressing to severe forms. DPV is a predictor of poor prognosis when it is less than 2 days and with a possible requirement for mechanical ventilation. The speed of progression of neurological disease is a practical and accessible clinical evaluation method that should be evaluated in patients with GBS.

The Platelet-Lymphocyte Ratio As a Novel Predictor of Severity in Patients With Unstable Angina Pectoris: Randomized Control Double-Blind Study

The Platelet-Lymphocyte Ratio As a Novel Predictor of Severity in Patients With Unstable Angina Pectoris: Randomized Control Double-Blind Study

517. Association of the predictive risk scores of CALL points and COVID-GRAM with IL-6, duration of oxygen therapy, D-dimer among patients with COVID-19

BackgroundThe coronavirus disease 2019 (COVID-19) outbreak has caused a global pandemic. Critically ill patients with COVID-19 can develop acute respiratory distress syndrome (ARDS) and thrombosis. Angiotensin-converting enzyme 2 is a functional receptor for severe acute respiratory syndrome coronavirus 2 to gain entry in cells. This receptor is widely expressed in some hematopoietic cells, including monocytes and macrophages. Infection of these cells results in secretion of interleukin (IL)-6 and other inflammatory cytokines. IL-6 and other inflammatory cytokines can cause ARDS and thrombosis. Elevated IL-6 levels are expected to cause more severe cytokine release syndrome. In this study we investigated the association of the predictive risk scores with the IL-6 level, duration of oxygen therapy (DOT), and D-dimer level.MethodsWe enrolled 20 consecutive patients diagnosed with COVID-19 from April 3, 2020, to April 30, 2020, and determined the predictive risk scores of CALL points (Dong J et al. CID 2020) and COVID-GRAM (Liang W et al. JAMA Int. Med2020) on admission. We statically analyzed the regressions between these two scores and the values of IL-6 and D-dimer and DOT.ResultsThe regression lines between CALL points and the values of IL-6, D-dimer, DOT were Y=-2.09 + 0.618X (r=0.821), Y=-0.783 + 0.213X (r=0.510), and Y=-5.32 + 1.26X (r=0.744), respectively. The regression lines between COVID-GRAM and the values of IL-6, D-dimer, and DOT were Y=-0.820 + 0.0344X (r=0.935), Y=-2.70 + 0.0205X (r=0.774), and Y=-1.92 + 0.0491X (r=0.765), respectively. These correlation coefficients were statistically significant. The correlation coefficients of CALL points were in the descending order of IL-6, DOT, and D-dimer. The correlation coefficients of COVID-GRAM were in the descending order of IL-6, D-dimer, and DOT. The coefficient between COVID-GRAM and IL-6 was the highest.ConclusionThese predictive risk scores of CALL points and COVID-GRAM can be surrogate markers for the IL-6 level in patients with COVID-19. Further research is required to understand the prediction of severity in patients with COVID-19.Disclosures All Authors: No reported disclosures

Electrocardiogram Heart Rate as a Predictor of Severity in Acute Alcohol-Related Pancreatitis With Alcohol Withdrawal Syndrome.

BackgroundThe severity of acute alcohol-related pancreatitis (AAP) with alcohol withdrawal syndrome (AWS) has not been studied. Electrocardiogram (ECG) has not been used as a predictor of severity in patients with AWS and acute pancreatitis.ObjectivesThe study aimed to determine whether the ECG heart rate (HR) could predict the severity of AAP; secondarily, whether AWS influenced the severity of AAP based on Acute Physiology and Chronic Health Evaluation (APACHE) II and Bedside Index for Severity in Acute Pancreatitis (BISAP).MethodsDemographics, comorbid illnesses, AWS, biochemistry, ECG, arterial blood gases, and CT findings were noted in patients with AAP. The severity of pancreatitis was scored into mild, moderate, and severe based on CT. BISAP, APACHE II, and ECG heart rate-APACHE (E-APACHE) were compared in patients with and without AWS. A receiver operating characteristic curve was used to find the best predictor of severity.ResultsAmong 138 patients (M=128), 94 had AWS. ECG changes (≥1) were seen in 50%. Patients with AWS were younger, had consumed alcohol for a shorter duration, had higher systemic inflammatory response syndrome (SIRS), APACHE II, and E-APACHE II scores. APACHE II and E-APACHE II correlated significantly with severity grading, HR, alcohol duration, and AWS. HR was the best predictor of severe pancreatitis; E-APACHE was the best predictor for moderately severe pancreatitis.ConclusionsMostly, AAP appears to be mild; >2/3rds have AWS. ECG findings were seen in 50%. HR has not been previously studied in patients with both AAP and AWS and is an easy and inexpensive test to predict the severity of pancreatitis in this cohort.

Serum microRNAs as novel biomarkers for early prediction of disease severity in patients with acute pancreatitis

BackgroundDysregulated microRNAs (miRNAs) have been identified to be associated with various diseases. However, the relationship between serum miRNAs and the severity of acute pancreatitis (AP) remains unknown.MethodsOne hundred twenty-five patients were enrolled and classified into mild AP (MAP, n = 45), moderate severe AP (MSAP, n = 42) and severe AP (SAP, n = 38) groups according to Atlanta 2012. TaqMan low density array (TLDA) technology was initially used in three pooled serum samples from 10 MAP, 10SAP and 10 healthy controls (HCs). The selected miRNAs were subsequently measured individually using quantitative real-time polymerase chain reaction (qRT-PCR) assay.ResultsThe TLDA identified 395 miRNAs were differentially expressed between the AP patients and the HCs, among which 12 miRNAs were selected for further evaluation. qRT-PCR confirmed that miR-19a, miR-143 and miR-374-5p were significantly upregulated in AP patients (p < 0.001) and increased with disease severity (p < 0.05). Receiver operating characteristic (ROC) curve analysis revealed that three miRNAs could distinguish the SAP patients from the HCs (area under ROC, AUC 0.940–0.943), MAP (AUC 0.754–0.782), and moderate severe AP (MSAP, AUC 0.670–0.686). In addition, multivariate logistic regression revealed that increased serum miR-143 was an independent predictor of developing SAP among MSAP and SAP patients (OR = 6.8, 95% CI 2.0–22.7) and among all AP patients (OR = 4.5, 95% CI 1.8–10.9).ConclusionsThese data indicate that an expression signature of three serum miRNAs holds potential as a novel biomarker for the early prediction of SAP.

Soluble ST2 is a Useful Biomarker for Grading Cerebral–Cardiac Syndrome in Patients after Acute Ischemic Stroke

This study tested whether the soluble (s)ST2 is a superb biomarker predictive of moderate to severe cerebral–cardiac syndrome (CCS) (defined as coexisting National Institute of Health Stroke Scale (NIHSS) >8 and left-ventricular ejection fraction (LVEF) <60%) in patients after acute ischemic stroke (IS). Between November 2015 and October 2017, a total of 99 IS patients were prospectively enrolled and categorized into three groups based on NIHSS, i.e., group 1 (NIHSS ≤ 8, n = 66), group 2 (NIHSS = 9-15, n = 14) and group 3 (NIHSS ≥ 16, n = 19), respectively. Blood samples were collected immediately after hospitalization, followed by transthoracic echocardiographic examination. The results showed that the flow cytometric analysis for assessment of inflammatory biomarkers of TLR2+/CD14+cells, TLR4+/CD14+cells, Ly6g+/CD14+cells, and MPO+/CD14+cells, and ELISA assessment for circulatory level of sST2 were significantly higher in groups 2/3 than in group 1 (all p < 0.01). However, these parameters did not show significant differences between groups 2 and 3 (all p > 0.05). The LVEF was significantly lower in group 3 than in group 1 (p < 0.001), but it displayed no difference between groups 1/2 or between groups 2/3. These inflammatory biomarkers ((TLR2+/CD14+cells// TLR4+/CD14+cells// MPO+/CD14+cells) and sST2)) were significantly positively correlated to NIHSS and strongly negatively correlated to LVEF (all p < 0.05). Multivariate analysis demonstrated that both MPO/CD14+cells >20% (p = 0.027) and sST2 ≥ 17,600 (p = 0.004) were significantly and independently predictive of moderate-severe CCS after acute IS. Receiver operating characteristic curve analysis demonstrated that sST2 was the most powerful predictor of CCS with a sensitivity of 0.929 and a specificity of 0.731 (p < 0.001). In conclusion, sST2 is a useful biomarker for prediction of CCS severity in patients after acute IS.

A Novel Index for Prompt Prediction of Severity in Patients with Unstable Angina Pectoris.

Objectives Rapid risk stratification by emergency department (ED) physicians to evaluate patients with chest pain for predicting the short-term occurrence of major adverse cardiac event (MACE) is crucial. The aim of this study was to investigate the predictive value of platelet-lymphocyte ratio (PLR) levels and compare with the modified heart score (m-HS) and stress testing to predict the severity of high-risk patients with unstable angina pectoris (UAP) in the ED. Methods This study is prospective which included 316 patients with UAP and 316 control healthy subjects. The study took place from 01 April 2016, until 01 April 2017, in Medipol University. Result The mean PLR levels in the UAP group were higher than those in the control group (p < 0.001). The mean PLR of the m-HS ≥4 group was higher than that in the m-HS ≤3 group (p < 0.001). The mean levels of PLR in the subgroups based on the stress testing positivity were higher than those in the stress testing negative subgroup (p < 0.001). PLR levels were positively correlated with the m-HS, stress testing, and treatment decision in this study (r = 0.559; p < 0.001; r = 0.582; p < 0.001; r = 0.789; p < 0.001, respectively). Conclusion A positive correlation was determined with an increase in m-HS, treatment decision, and positive exercise testing as the PLR levels increased, indicating the severity of high risk of UAP in the ED.

Red Cell Distribution Width as a Predictor of Severity of Acute Pancreatitis

Introduction: Acute pancreatitis (AP) is a disorder featured by local and systemic inflammatory response, which manifests as mild, self-limited disorder to severe and sometimes fatal disease. Red cell distribution width (RDW) is reflective of systemic inflammation and has been shown to be effective at predicting severity. This study was aimed to investigate the association between Red cell distribution width as coefficient of variation (RDW -CV) on admission and severity of acute pancreatitis.&#x0D; Method: This was a hospital based prospective study conducted in the Department of Surgery, Nepalgunj Medical College Teaching Hospital for a period of 2 years from July 2017 to June 2019. The patients with acute pancreatitis were categorized into mild, moderate and severe acute pancreatitis. The value of RDW-CV on admission was correlated with the severity of acute pancreatitis.&#x0D; Results: RDW-CV on admission was significantly correlated with the severity of AP (p value &lt;0.001). Receiver Operating Characterstic (ROC) analysis showed that RDW has very good discriminative power for severe acute pancreatitis [AreaUnder curve (AUC) 0.963, 95% CI, 0.919 to 1.007, p-value &lt;0.001] but not useful to predict mild AP (AUC 0.157, 95% CI, 0.063 to 0.250, p value 0.14) and moderate AP (AUC 0.397, 95% CI, 0.252 to 0.541, p value 0.234). The maximum sensitivity and specificity of detecting severe AP was 95.7% and 91.5% respectively. The positive predictive value (PPV) and negative predictive value (NPV) was 84.6% and 97.7% respectively.&#x0D; Conclusion: RDW-CV width on admission is a predictor of severity in patients with severe acute pancreatitis.