Early predictive value of scoring systems and routine laboratory tests in severity and prognosis of acute pancreatitis in pregnancy
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ABSTRACT: Background:
Currently, no guidelines specifically recommend scoring systems and
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PROVIDER: S-EPMC10126706 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundSevere acute pancreatitis (SAP) is a dangerous condition with a high mortality rate. Many studies have found an association between adipokines and the development of SAP, but the results are controversial. Therefore, we performed a meta-analysis of the association of inflammatory adipokines with SAP.MethodsWe screened PubMed, EMBASE, Web of Science and Cochrane Library for articles on adipokines and SAP published before July 20, 2023. The quality of the literature was assessed using QUADAS criteria. Standardized mean differences (SMD) with 95% confidence intervals (CI) were calculated to assess the combined effect. Subgroup analysis, sensitivity analysis and publication bias tests were also performed on the information obtained.ResultFifteen eligible studies included 1332 patients with acute pancreatitis (AP). Pooled analysis showed that patients with SAP had significantly higher serum levels of resistin (SMD = 0.78, 95% CI:0.37 to 1.19, z = 3.75, P = 0.000). The difference in leptin and adiponectin levels between SAP and mild acute pancreatitis (MAP) patients were not significant (SMD = 0.30, 95% CI: -0.08 to 0.68, z = 1.53, P = 0.127 and SMD = 0.11, 95% CI: -0.17 to 0.40, z = 0.80, P = 0.425, respectively). In patients with SAP, visfatin levels were not significantly different from that in patients with MAP (SMD = 1.20, 95% CI: -0.48 to 2.88, z = 1.40, P = 0.162).ConclusionElevated levels of resistin are associated with the development of SAP. Resistin may serve as biomarker for SAP and has promise as therapeutic target.
| S-EPMC10787974 | biostudies-literature
Project description:Psoriasis is a chronic inflammatory skin disease that affects approximately 125 million people worldwide. It has significant impacts on both physical and emotional health-related quality of life comparable to other major illnesses. Accurately prediction of psoriasis using biomarkers from routine laboratory tests has important practical values. Our goal is to derive a powerful predictive model for psoriasis disease based on only routine hospital tests. We collected a data set including 466 psoriasis patients and 520 healthy controls with 81 variables from only laboratory routine tests, such as age, total cholesterol, HDL cholesterol, blood pressure, albumin, and platelet distribution width. In this study, Boruta feature selection method was applied to select the most relevant features, with which a Random Forest model was constructed. The model was tested with 30 repetitions of 10-fold cross-validation. Our classification model yielded an average accuracy of 86.9%. 26 notable features were selected by Boruta, among which 15 features are confirmed from previous studies, and the rest are worth further investigations. The experimental results demonstrate that the machine learning approach has good potential in predictive modeling for the psoriasis disease given the information only from routine hospital tests.
| S-EPMC8525763 | biostudies-literature
Project description:BACKGROUND:Severity of AP is an important indicator of death rate, playing a crucial role in defining a correct dealing with a patient at his/her initial admission, in deciding on the need to transfer a patient to the intensive care unit. Many studies point out a direct relation between the death rate and the number of affected organs. In light of this, looking for the new criteria of multiple organ failure is still useful in clinical practice. Typically, assessment of multiple organ failure with patients undergoing treatment in the intensive care unit is carried out with the use of various integrated scores based both on clinical laboratory assessment of patient's condition and on data obtained by advanced imaging methods. However, many scientists point out that the facilities of diagnostic radiology, including in particularly computerised tomography, are not used to the full extent. AIM:We developed a CT score for assessment of pancreatitis severity that takes into consideration not only alterations of the pancreas but also enables evaluation of multiple organ failure with the examined patients. METHODS:We have examined 100 patients with suspected pancreatitis. Among them 30 patients had pancreatitis without alterations of the vital organs; 70 patients had alterations of the vital organs, suffered organ or multiple organ failure and received treatment in the surgery unit and intensive care unit of the Department of Surgical Conditions of Karaganda Medical University. RESULTS:Because of CT results, based on the proposed score, we assessed a degree of pancreas necrosis, analysed the relation between organ failure and degree of pancreas necrosis. Finally, we evaluated the connection between multiple organ failure and the specific failure of one organ and the presence of necrosis and death rate. CONCLUSION:The proposed score for CT-based assessment of pancreatitis severity can be used not only for identification but also for prediction of organ failure at the early stage of pancreatitis to a high accuracy as compared to conventional CT systems for assessment of the condition of patients affected by pancreatitis. It can also be used to differentiate the severity of organ failure and the number of affected organs.
| S-EPMC7061380 | biostudies-literature
Project description:ObjectivesThe present study aimed to develop a clinical decision support tool to assist coronavirus disease 2019 (COVID-19) diagnoses with machine learning (ML) models using routine laboratory test results.MethodsWe developed ML models using laboratory data (n = 1,391) composed of six clinical chemistry (CC) results, 14 CBC parameter results, and results of a severe acute respiratory syndrome coronavirus 2 real-time reverse transcription-polymerase chain reaction as a gold standard method. Four ML algorithms, including random forest (RF), gradient boosting (XGBoost), support vector machine (SVM), and logistic regression, were used to build eight ML models using CBC and a combination of CC and CBC parameters. Performance evaluation was conducted on the test data set and external validation data set from Brazil.ResultsThe accuracy values of all models ranged from 74% to 91%. The RF model trained from CC and CBC analytes showed the best performance on the present study's data set (accuracy, 85.3%; sensitivity, 79.6%; specificity, 91.2%). The RF model trained from only CBC parameters detected COVID-19 cases with 82.8% accuracy. The best performance on the external validation data set belonged to the SVM model trained from CC and CBC parameters (accuracy, 91.18%; sensitivity, 100%; specificity, 84.21%).ConclusionsML models presented in this study can be used as clinical decision support tools to contribute to physicians' clinical judgment for COVID-19 diagnoses.
| S-EPMC8690000 | biostudies-literature
Project description:BackgroundRecent studies suggest that routine laboratory tests are not required within 1 day after partial knee arthroplasty. In this study, we evaluated the utility of routine postoperative laboratory tests after initial unilateral total knee arthroplasty (TKA) in an Asian population. In addition, we explored risk factors associated with abnormal test results.MethodsClinical data of patients who underwent original unilateral TKA between 2015 and 2020 were retrospectively analyzed. Patient characteristics and laboratory test results were recorded. Multivariate binary logistic regression analysis was performed to identify risk factors associated with 3 abnormal laboratory results.ResultsA total of 713 patients, who underwent relevant laboratory tests within 3 days of TKA surgery, were enrolled. Among them, 8.1%, 9.9%, and 3.4% patients with anemia, hypoalbuminemia, and abnormal serum potassium levels required clinical intervention after surgery. Binary logistic regression analysis revealed that preoperative hemoglobin levels, estimated blood loss, and age were independent risk factors of postoperative blood transfusion in TKA patients. On the other hand, preoperative albumin levels, intraoperative blood loss, and operation time were risk factors associated with postoperative albumin supplementation. In addition, lower body mass index (BMI) and preoperative hypokalemia were potential risk factors of postoperative potassium supplementation.ConclusionConsidering that more than 90% of abnormal postoperative laboratory tests do not require clinical intervention, we believe that routine laboratory tests after surgery have little significance in patients with primary unilateral TKA. However, postoperative laboratory testing is necessary for patients with established risk factors.
| S-EPMC9188221 | biostudies-literature
Project description:Interleukin (IL)-6, IL-8, IL-10, and C-reactive protein (CRP) have been evaluated for predicting outcomes of acute pancreatitis. However, there is considerable variation in their performance among different studies. We evaluate their accuracy in predicting progression to severe pancreatitis.Serum IL-6, IL-8, IL-10, and CRP levels were measured within 24 h of admission in forty patients of clinically predicted severe acute pancreatitis (SAP). Persistent organ failure (>48 h) defined SAP. The performance of inflammatory markers was evaluated in predicting the progression of pancreatitis.IL-6 ≥28.90 pg/mL had a sensitivity of 62.86%, specificity of 80%, positive predictive value (PPV) of 95.65%, LR+ of 3.1429, LR- of 0.4643, and diagnostic odds ratio (DOR) of 6.7692; IL-8 ≥88.70 pg/mL had a sensitivity of 60%, specificity of 80%, PPV of 95.45%, LR+ of 3.000, LR- of 0.5000, and DOR of 6.000; IL-10 ≤5.70 pg/mL had DOR of 0.2647, sensitivity of 51.43%, specificity of 20%, PPV of 81.82%, LR+ of 0.6429, and LR- of 2.4286. CRP ≥110.00 mg/L had DOR of 2.3636, sensitivity of 37.14%, specificity of 80%, PPV of 92.86%, LR+ of 1.8571, and LR of 0.7857.IL-6 ≥28.90 pg/mL, measured within 48 h of onset is the best among the tested biomarkers in this study for predicting the progression to severe pancreatitis.
| S-EPMC5538089 | biostudies-other
Project description:BackgroundAneurysmal subarachnoid hemorrhage (aSAH) necessitating mechanical ventilation (MV) presents a serious challenge for intensivists. Laboratory blood tests reflect individual physiological and biochemical states, and provide a useful tool for identifying patients with critical condition and stratifying risk levels of death. This study aimed to determine the prognostic role of initial routine laboratory blood tests in these patients.MethodsThis retrospective cohort study included 190 aSAH patients requiring MV in the neurosurgical intensive care unit from December 2019 to March 2022. Follow-up evaluation was performed in May 2022 via routine outpatient appointment or telephone interview. The primary outcomes were death occurring within 7 days after discharge (short-term mortality) or reported at time of follow-up (long-term mortality). Clinico-demographic and radiological characteristics, initial routine laboratory blood tests (e.g., metabolic panels and arterial blood gas analysis), and treatment were analyzed and compared in relation to mortality. Multivariable logistic and Cox regression analyses, with adjustment of other clinical predictors, were performed to determine independent laboratory test predictors for short- and long-term mortality, respectively.ResultsThe patients had a median age of 62 years, with a median World Federation of Neurosurgical Societies grade (WFNS) score of 5 and a median modified Fisher grade (mFisher) score of 4. The short- and long-term mortality of this cohort were 60.5% and 65.3%, respectively. Compared with survivors, non-survivors had more severe disease upon admission based on neurological status and imaging features and a shorter disease course, and were more likely to receive conservative treatment. Initial ionized calcium was found to be independently associate with both short-term [adjusted odds ratio (OR): 0.92; 95% confidence interval (CI): 0.86 to 0.99; P=0.020] and long-term mortality [adjusted hazard ratio (HR): 0.95; 95% CI: 0.92 to 0.99; P=0.010], after adjusting for potential confounders. Moreover, the admission glucose level was found to be associated only with short-term mortality (adjusted OR: 1.19; 95% CI: 1.06 to 1.34; P=0.004).ConclusionsLaboratory screening may provide a useful tool for the management of aSAH patients requiring MV in stratifying risk levels for mortality and for better clinical decision-making. Further study is needed to validate the effects of calcium supplementation and glucose-lowering therapy on the outcomes in this disease.
| S-EPMC10482645 | biostudies-literature
Project description:Many injury severity scoring tools have been developed over the past few decades. These tools include the Injury Severity Score (ISS), New ISS (NISS), Trauma and Injury Severity Score (TRISS) and International Classification of Diseases (ICD)-based Injury Severity Score (ICISS). Although many studies have endeavored to determine the ability of these tools to predict the mortality of injured patients, their results have been inconsistent. We conducted a systematic review to summarize the predictive performances of these tools and explore the heterogeneity among studies. We defined a relevant article as any research article that reported the area under the Receiver Operating Characteristic curve as a measure of predictive performance. We conducted an online search using MEDLINE and Embase. We evaluated the quality of each relevant article using a quality assessment questionnaire consisting of 10 questions. The total number of positive answers was reported as the quality score of the study. Meta-analysis was not performed due to the heterogeneity among studies. We identified 64 relevant articles with 157 AUROCs of the tools. The median number of positive answers to the questionnaire was 5, ranging from 2 to 8. Less than half of the relevant studies reported the version of the Abbreviated Injury Scale (AIS) and/or ICD (37.5%). The heterogeneity among the studies could be observed in a broad distribution of crude mortality rates of study data, ranging from 1% to 38%. The NISS was mostly reported to perform better than the ISS when predicting the mortality of blunt trauma patients. The relative performance of the ICSS against the AIS-based tools was inconclusive because of the scarcity of studies. The performance of the ICISS appeared to be unstable because the performance could be altered by the type of formula and survival risk ratios used. In conclusion, high-quality studies were limited. The NISS might perform better in the mortality prediction of blunt injuries than the ISS. Additional studies are required to standardize the derivation of the ICISS and determine the relative performance of the ICISS against the AIS-based tools.
| S-EPMC3511252 | biostudies-literature
Project description:BackgroundThe Oxford Acute Severity of Illness Score (OASIS) has shown fair prognosis predictive value in critically ill patients, but its predictive value has not been assessed in septic patients.ObjectiveThe aim of this study was to evaluate the performance of the OASIS for the assessment of mortality in septic patients, especially when compared with the Sepsis-related Organ Failure Assessment (SOFA) score.MethodsA retrospective cohort study was conducted using data from a public database and septic patients were identified using the Sepsis-3 criteria. The primary outcome was hospital mortality. Data were mainly analyzed using multivariable logistic regression and receiver operating characteristic (ROC) curves. Sensitive analyses were performed in patients with an ICD-9-CM code for sepsis and ROC curves analyses were also conducted in septic patients stratified by the Simplified Acute Physiology Score (SAPS) II as subgroup analyses.ResultsA total of 10,305 septic patients were included. The OASIS was found to be significantly associated with hospital mortality (odds ratio 1.07 per one-point increase, 95% confidence interval [1.06-1.08]), while ROC curves analyses showed the discriminatory power of the OASIS for hospital mortality was statistically significantly lower than that of the SOFA score (area under the ROC curve: 0.652 vs 0.682, p < 0.001). Results of sensitive analyses were consistent, but the significant difference existed only when the SAPS II was higher than 50 according to results of the subgroup analyses.ConclusionsThe OASIS might serve as an initial predictor of clinical outcomes for septic patients, but one should be circumspect when it is applied to severer patients.
| S-EPMC6563807 | biostudies-literature
Project description:BackgroundDengue laboratory diagnosis is essentially based on detection of the virus, its components or antibodies directed against the virus in blood samples. Blood, however, may be difficult to draw in some patients, especially in children, and sampling during outbreak investigations or epidemiological studies may face logistical challenges or limited compliance to invasive procedures from subjects. The aim of this study was to assess the possibility of using saliva and urine samples instead of blood for dengue diagnosis.Methodology/principal findingsSerial plasma, urine and saliva samples were collected at several time-points between the day of admission to hospital until three months after the onset of fever in children with confirmed dengue disease. Quantitative RT-PCR, NS1 antigen capture and ELISA serology for anti-DENV antibody (IgG, IgM and IgA) detection were performed in parallel on the three body fluids. RT-PCR and NS1 tests demonstrated an overall sensitivity of 85.4%/63.4%, 41.6%/14.5% and 39%/28.3%, in plasma, urine and saliva specimens, respectively. When urine and saliva samples were collected at the same time-points and tested concurrently, the diagnostic sensitivity of RNA and NS1 detection assays was 69.1% and 34.4%, respectively. IgG/IgA detection assays had an overall sensitivity of 54.4%/37.4%, 38.5%/26.8% and 52.9%/28.6% in plasma, urine and saliva specimens, respectively. IgM were detected in 38.1% and 36% of the plasma and saliva samples but never in urine.ConclusionsAlthough the performances of the different diagnostic methods were not as good in saliva and urine as in plasma specimens, the results obtained by qRT-PCR and by anti-DENV antibody ELISA could well justify the use of these two body fluids to detect dengue infection in situations when the collection of blood specimens is not possible.
| S-EPMC4583371 | biostudies-literature