Alpha-hydroxybutyrate dehydrogenase as a biomarker for predicting systemic lupus erythematosus with liver injury

Serum α-hydroxybutyrate dehydrogenase as a biomarker for predicting survival outcomes in patients with UTUC after radical nephroureterectomy

PURPOSE

We aimed to determine the prognostic value of α-hydroxybutyrate dehydrogenase (α-HBDH) in upper tract urothelial carcinoma (UTUC) patients after radical nephroureterectomy (RNU).

MATERIALS AND METHODS

We retrospectively enrolled the data of 544 UTUC patients at West China Hospital from May 2003 to June 2019. Cancer-specific survival (CSS) was the endpoint of interest. The optimal cutoff value of α-HBDH was identified by X-Tile program. After propensity score matching (PSM), we utilized Kaplan‒Meier curves to estimate survival and Cox proportional hazard model for risk assessment. A nomogram was built based on the results of multivariate analysis, and calibration curve, time-dependent receiver operating characteristic (ROC) curves and decision curve analysis were also performed to evaluate the predictive accuracy.

RESULTS

Overall, 394 and 150 patients were divided into the α-HBDH-low group and α-HBDH -high group at the cutoff value of 158 U/L, respectively. After PSM, the two groups were well matched for all confounding factors. High α-HBDH was associated with inferior CSS (P = 0.006), and preoperative α-HBDH was an independent predictor for CSS (HR: 1.36; 95% CI:1.08, 1.80), especially in localized UTUC patients (HR: 2.04; 95% CI:1.11, 3.74). Furthermore, the nomogram based on α-HBDH achieved great predictive ability for CSS with areas under the curves of 0.800 and 0.778 for 3-year and 5-year CSS, respectively.

CONCLUSION

Serum α-HBDH was a novel and reliable biomarker for predicting survival outcomes in UTUC patients after RNU but should be further explored.

Clinical manifestations and prognostic factors analysis of patients hospitalised with acute exacerbation of idiopathic pulmonary fibrosis and other interstitial lung diseases

BACKGROUND

Acute exacerbation (AE) is a life-threatening condition taking place not only in idiopathic pulmonary fibrosis (IPF) but also in interstitial lung diseases (ILD) other than IPF (non-IPF ILD). This study aims to compare the clinical manifestations between patients hospitalised with AE-IPF and AE-non-IPF ILD, and further analyse the risk factors related to in-hospital mortality.

METHODS

Clinical data of 406 patients hospitalised with AE-IPF (93 cases) and AE-non-IPF ILD (313 cases) were retrospectively collected. Clinical features were compared between the two groups. Risk factors related to in-hospital mortality in patients with overall AE-ILD, AE-IPF and AE-non-IPF ILD were identified by multiple logistic regression analyses, respectively, and assessed by receiver operating characteristic curve.

RESULTS

In addition to having more smokers and males, the AE-IPF group also had more respiratory failure on admission, comorbidities of pulmonary hypertension (PAH) or coronary artery disease/heart failure, a longer history of pre-existing ILD. Comorbidity of coronary heart disease/heart failure, respiratory failure at admission, neutrophil (N)%, serum hydroxybutyrate dehydrogenase (HBDH), lactate dehydrogenase (LDH) and low cholesterol levels were independent risk factors for patients with AE-ILD, while respiratory failure on admission, N%, serum HBDH, urea nitrogen, LDH and low albumin levels were risk factors for the AE-non-IPF ILD group, and fever, N% and PAH were the AE-IPF group's. Among them, HBDH 0.758 (sensitivity 85.5%, specificity 56%, cut-off 237.5 U/L) for patients with AE-ILD; N% 0.838 (sensitivity 62.5%, specificity 91.18%, cut-off 83.55%) for the AE-IPF group and HBDH 0.779 (sensitivity 86.4%, specificity 55.1%, cut-off 243.5 U/L) for the AE-non-IPF ILD group were the risk factors with the highest area under the curve.

CONCLUSIONS

Clinical characteristics differ between patients with AE-IPF and AE-non-IPF ILD. HBDH outperformed LDH in predicting the prognosis for patients with AE-ILD and AE-non-IPF ILD. N% was an independent predictor of death in-hospital in all three groups, especially in the AE-IPF group.

Early diagnosis and clinical application of systemic lupus erythematosus based on a nomogram model

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease involving multi-system and multi-organ dysfunction, and is easily misdiagnosed early in the disease course. We aimed to accurately predict early SLE nomogram to provide a reference basis for the early clinical diagnosis of SLE. Methods: We retrospectively analyzed 167 patients who were first diagnosed with SLE at Fengxian District Central Hospital, Shanghai, between March 2017 and October 2022. Three groups of 129 physically healthy subjects, 67 patients with rheumatoid arthritis, and 40 patients with rashes were selected as controls during the same period. Patients with SLE and control group were randomly divided into training (n = 217) and validation (n = 141) group. Univariate and multivariate analyses were used to identify independent risk factors for early SLE diagnosis. The independent risk factors for diagnosis were used to construct a nomogram to predict early SLE. Results: Based on the training group, three variables were identified as independently influencing early SLE: platelets (odds ratio OR = 0.993, P = 0.047), albumin (OR = 0.833, P = 0.007), and complement component 1q (OR = 0.956, P = 0.000). The precision of the nomogram was assessed using C-index values and calibration plot diagrams. The C-index values were 0.929 for training group and 0.898 for validation group. Both the training group and validation group calibration curves showed good predicted outcomes. Conclusion: The construction of a nomogram can accurately predict the risk of early SLE. The model showed good discriminatory power and calibration for use in the diagnosis of SLE, providing a visual tool and reference basis for the early diagnosis of SLE.

The correlation between red cell distribution width to albumin ratio and all-cause mortality in critically ill patients with rheumatic diseases: a population-based retrospective study

Background

Patients with rheumatic diseases have an increased likelihood of being admitted to the intensive care unit (ICU), highlighting the importance of promptly identifying high-risk individuals to enhance prognosis. This study aimed to assess the correlation of red blood cell distribution width to albumin ratio (RAR) with the 90-days and 360-days survival rates among critically ill rheumatic patients.

Methods

Adult rheumatic patients admitted to the ICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were included. The participants were categorized into two groups, survivors (n = 436) and non-survivors (n = 192), based on their 90-days survival outcome. The population was further classified into tertiles using RAR values, with RAR < 4.63 (n = 208), 4.63-6.07 (n = 211), and > 6.07 (n = 209). Kaplan-Meier curves were utilized to evaluate the cumulative survival rates at 90-days and 360-days. The association between RAR and mortality was assessed using restricted cubic splines (RCS) and multivariate Cox regression analysis. Additional subgroup analyses and sensitivity analyses were conducted to further explore the findings. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive performance of RAR.

Results

This study involved 628 critically ill patients with rheumatic diseases, and they had an all-cause mortality of 30.57% at 90-days and 38.69% at 360-days. Kaplan-Meier analysis showed a gradual decrease in both 90-days and 360-days cumulative survival with increasing RAR (χ2 = 24.400, p < 0.001; χ2 = 35.360, p < 0.001). RCS revealed that RAR was linearly related to 90-days and 360-days all-cause mortality risk for critically ill patients with rheumatic diseases (χ2 = 4.360, p = 0.225; χ2 = 1.900, p = 0.594). Cox regression analysis indicated that elevated RAR (> 6.07) was significantly correlated with mortality. The ROC curves demonstrated that an optimal cut-off value of RAR for predicting 90-days mortality was determined to be 5.453, yielding a sensitivity of 61.5% and specificity of 60.3%.

Conclusion

Elevated RAR (> 6.07) was associated with all-cause mortality at 90-days and 360-days among critically ill patients with rheumatic diseases, serving as an independent risk factor for unfavorable prognosis.

Elevation of Metrnβ and Its Association with Disease Activity in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is an auto-immune disease, the pathogenesis of which remains to be fully addressed. Metrnβ is a novel cytokine involved in the pathogenesis of inflammatory disease, but its regulatory roles in SLE are unclear. We aimed to comprehensively investigate the clinical value of Metrnβ in SLE. A massive elevation of circulating Metrnβ levels was observed in SLE, and patients with an active phase displayed higher Metrnβ concentrations than those with inactive phases. Additionally, we found that Metrnβ expression was positively correlated with clinical indicators of SLE. Longitudinal cytokine and chemokine profiles revealed a disturbed immune response in SLE, with high activity profiles displayed severe pathogenic inflammation, and a positive correlation of the serum Metrnβ with CXCL9, IL10, IL18 and IL1RA was observed as well. Moreover, Metrnβ expressions exhibited an inverse correlation with Treg and B10. Of note, a significant decrease of ILC2 was found in SLE, and there was a negative correlation of Metrnβ with ILC2 as well. Further ROC analysis showed that the area under the curve (AUC) for Metrnβ was 0.8250 (95% CI: 0.7379-0.9121), with a cutoff value of 1131 pg/mL to effectively distinguish SLE patients from healthy controls. Our study herein demonstrated for the first time that Metrnβ values were increased and were immunologically correlated with SLE activity, which could be utilized as an alternative biomarker for the early identification and predicting of the immuno-response of SLE.

Prognostic value of serum α-HBDH levels in patients with lung cancer

BACKGROUND

The purpose of our study is to investigate the expression level and prognostic value of serum α-hydroxybutyrate dehydrogenase (α-HBDH) in lung cancer (LC) patients.

METHOD

LC patients treated in the Department of Oncology, Shaanxi Provincial Cancer Hospital from January 2014 to December 2016 were included in this study, all of whom underwent serological detection of α-HBDH prior to admission, and were enrolled in follow-up 5-year survival. Comparing the differences between high group and normal groups based on α-HBDH and LDH expression via clinicopathological parameters and laboratory data. Univariate and multivariate regression and overall survival (OS) were analyzed to explore whether elevated α-HBDH was an independent risk factor for LC, compared to LDH.

RESULTS

Multivariate regression analysis showed that age (P = 0.018), liver metastasis (P = 0.011), α-HBDH (P = 0.015), and neutrophil-to-lymphocyte ratio (NLR) (P = 0.031) were independent prognostic factors affecting OS in LC patients. The overall diagnostic efficacy of α-HBDH (AUC = 0.887) was higher than that of LDH (AUC = 0.709) in the ROC curve. The sensitivity was significantly higher of α-HBDH (sensitivity: 76.06%, specificity: 94.87%) compared with LDH (sensitivity: 49.30%, specificity: 94.87%). The median of OS was more significant in the high-α-HBDH group (6.4 months) than in the normal-α-HBDH group (12.7 months) (P = 0.023). The median of OS was significant in the high-LDH (> 245 U/L) group at 5.8 months and 12.0 months in the normal-LDH (≤ 245 U/L) group (P = 0.068).

CONCLUSIONS

Elevated expression of α-HBDH may indicate a poor prognosis of LC patients. It has a higher sensitivity than LDH and can be used as a potential early biomarker and an independent risk factor predicting the prognosis of LC survival.

The relationship of α-hydroxybutyrate dehydrogenase with 1-year outcomes in patients with intracerebral hemorrhage: A retrospective study

Background and aims

Cardiac enzymes are recognized as a valuable tool for predicting the prognosis of various cardiovascular diseases. The prognostic value of alpha-hydroxybutyrate dehydrogenase (α-HBDH) in patients with intracerebral hemorrhage (ICH) was ambiguous and not evaluated.

Methods

Two hundred and thirteen Chinese patients with ICH participated in the study from December 2018 to December 2019. Laboratory routine tests and cardiac enzymes, including α-HBDH level, were examined and analyzed. All the patients were classified into two groups by the median value of α-HBDH: B1 <175.90 and B2 ≥175.90 U/L. The clinical outcomes included functional outcome (according to modified Rankin Scale (mRS) score ≥3), all-cause death, and recurrent cerebro-cardiovascular events 1 year after discharge. Associations between the α-HBDH and the outcomes were evaluated using logistic regression analysis. Univariate survival analysis was performed by the Kaplan-Meier method and log-rank test.

Results

Of the 213 patients, 117 had α-HBDH ≥175.90 U/L. Eighty-two patients had poor functional outcomes (mRS≥3). During the 1-year follow-up, a total of 20 patients died, and 15 of them had α-HBDH ≥175.90 U/L during the follow-up time. Moreover, 24 recurrent events were recorded. After adjusting confounding factors, α-HBDH (≥175.90) remained an indicator of poor outcome (mRS 3-6), all-cause death, and recurrent cerebro-cardiovascular events. The ORs for B2 vs. B1 were 4.78 (95% CI: 2.60 to 8.78, P = 0.001), 2.63 (95% CI: 0.80 to 8.59, P = 0.11), and 2.40 (95% CI: 0.82 to 7.02, P = 0.11) for poor functional outcomes with mRS ≥ 3, all-cause death, and recurrent cerebro-cardiovascular events, respectively.

Conclusion

Increased α-HBDH at admission was independently related to poor functional outcome and all-cause mortality in patients with ICH at 1-year follow-up.

Triglycerides as Biomarker for Predicting Systemic Lupus Erythematosus Related Kidney Injury of Negative Proteinuria

Fewer biomarkers can be used to predict systemic lupus erythematosus (SLE) related kidney injury. This paper presents an apriori algorithm of association rules to mine the predictive biomarkers for SLE-related kidney injury of negative proteinuria. An apriori algorithm of association rules was employed to identify biomarkers, and logistic regression analysis and spearman correlation analysis were used to evaluate the correlation between triglycerides and SLE-related kidney injury of negative proteinuria. Triglycerides were mined out by the apriori algorithm of association rules. The level of triglycerides was significantly higher, and it was an independent risk factor for SLE-related kidney injury. In the high-triglycerides group, the number of patients with SLE-related kidney injury, SLEDAI-2K, urine P-CAST, the level of blood urea nitrogen, serum creatinine, and proteinuria were increased. Triglycerides level was positively correlated with proteinuria and P-CAST and negatively correlated with albumin and IgG. The area under the ROC curve of triglycerides and triglycerides combined proteinuria was 0.72 and 0.82, respectively. Significantly, 50% of SLE-related kidney injuries of negative proteinuria could be identified by high triglycerides levels. High triglycerides level was found at the time of onset of kidney injury, and it was opposite to glomerular filtration rate. Triglycerides may be a potential marker for predicting SLE-related kidney injury, especially in SLE-related kidney injury of negative proteinuria. Triglycerides combined proteinuria could predict SLE-related kidney injury effectively.

Hollow Cobalt Oxide/Carbon Hybrids Aid Metabolic Encoding for Active Systemic Lupus Erythematosus during Pregnancy

A noninvasive, easy operation, and accurate diagnostic protocol is highly demanded to assess systemic lupus erythematosus (SLE) activity during pregnancy, promising real-time activity monitoring during the whole gestational period to reduce adverse pregnancy outcomes. Here, machine learning of serum metabolic fingerprints (SMFs) is developed to assess the SLE activity for pregnant women. The SMFs are directly extracted through a hollow-cobalt oxide/carbon (Co₃ O₄ /C)-composite-assisted laser desorption/ionization mass spectrometer (LDI MS) platform. The Co₃ O₄ /C composite owns enhanced light absorption, size-selective trapping, and better charge-hole separation, enabling improved ionization efficiency and selectivity for LDI MS detection toward small molecules. Metabolic fingerprints are collected from ≈0.1 µL serum within 1 s without enrichment and encoded by the optimized elastic net algorithm. The averaged area under the curve (AUC) value in the differentiation of active SLE from inactive SLE and healthy controls reaches 0.985 and 0.990, respectively. Further, a simplified panel based on four identified metabolites is built to distinguish SLE flares in pregnant women with the highest AUC value of 0.875 for the blind test. This work sets an accurate and practical protocol for SLE activity assessment during pregnancy, promoting precision diagnosis of disease status transitions in clinics.

Serum amyloid A-to-albumin ratio as a potential biomarker to predict the activity, severity, and poor prognosis of systemic lupus erythematosus

Objectives

To evaluate the predictive value of serum amyloid A‐to‐albumin ratio (SAR) for active systemic lupus erythematosus (SLE), severe active SLE, and poor prognosis of SLE.

Methods

One hundred and eighty‐six patients with SLE undergoing treatment in our hospital were selected. The demographic characteristics, clinical data, and disease prognosis of all patients were collected and analyzed.

Results

There were significant differences in SLEDAI, total glyceride (TG), serum amyloid A (SAA), SAR, urinary microalbumin‐to‐creatinine ratio (ACR), erythrocyte sedimentation rate (ESR), albumin (ALB), complement 3 (C3), anti‐dsDNA, anti‐Sm positive rate, and anti‐dsDNA positive rate between active SLE and stable SLE patients. TG, SAR, C3, ACR, and positive anti‐dsDNA were independent influencing factors of active SLE, and the odds ratio (OR) values were 2.342, 10.921, 0.832, 1.451, and 2.476, respectively. The area under curves (AUCs) of SAA, ALB, and SAR for predicting active SLE and severe active SLE were 0.743, 0.724, 0.787, 0.711, 0.686, and 0.733, respectively. The AUC of SAR for predicting the poor prognosis of active SLE was 0.719. High SAR, high ACR, low C3, and positive anti‐dsDNA were high risk factors for poor prognosis. Kaplan–Meier (K‐M) survival analysis showed that patients with high SAR, high ACR, low C3, and positive anti‐dsDNA had shorter continuous remission time than that with low SAR, low ACR, high C3, and negative anti‐dsDNA.

Conclusion

SAR had high predictive value for active SLE, severe active SLE, and poor prognosis of SLE. High SAR may be a potential marker for predicting the activity and prognosis of Chinese patients with SLE.

Abnormal myocardial enzymes are important indicators of poor prognosis in COVID-19 patients

Objective: Researching the prognostic value of myocardial enzymes in COVID-19 patients. Materials & methods: We collected 113 confirmed COVID-19 patients. The dynamic changes of CK, LDH and α-HBDH in patients were studied retrospectively, the correlation between myocardial enzyme index, clinical classification and outcome of patients and its significance to prognosis. Results: There are significant statistical differences between LDH, α-HBDH, CK and the clinical classification, and patient’s outcome. In the receiver operating characteristic curve analysis, LDH, α-HBDH and CK have a good diagnostic value for the death outcome of patients. Conclusion: LDH, α-HBDH and CK were the components of myocardial enzyme profiles, and our results found that they were significantly positively correlated with clinical classification and prognosis of COVID-19 patients. The values of LDH, α-HBDH and CK increased with the increase of the severity of admission clinical classification and the deterioration of outcome. Therefore, we propose that continuous monitoring of LDH, α-HBDH and CK indicators can warn the deterioration of COVID-19 to a certain extent, regardless of whether patients with cardiovascular diseases are combined or not, and prompt early intervention.

Serum hydroxybutyrate dehydrogenase as an early predictive marker of the severity of acute pancreatitis: a retrospective study

BACKGROUND

To investigate the value of serum hydroxybutyrate dehydrogenase (HBDH) level, an isozyme of lactate dehydrogenase, in evaluating the severity of acute pancreatitis (AP).

METHODS

Patients diagnosed with AP from January 2013 to December 2018 were included in this retrospective study. Patients were divided into the normal serum HBDH levels group (n-HBDH group) and the high serum HBDH levels group (h-HBDH group) according to the criteria HBDH ≥ 182 U/L after admission. The demographic parameters, laboratory data and the severity of AP in the two groups were compared. The receiver operating curve (ROC) was used to evaluate the efficacy of serum HBDH in predicting persistent organ failure and systemic inflammatory response syndrome (SIRS).

RESULTS

A total of 260 AP patients were enrolled, including 176 cases in the n-HBDH group and 84 cases in the h-HBDH group. The incidence of SIRS and organ failure in the h-HBDH group were significantly higher than those in n-HBDH group (both P < 0.001). In addition, the HBDH level was significantly decreased in 110 patients who were re-measured after AP treatment. The serum HBDH levels were positively correlated with Atlanta classification, Ranson score, and BISAP score (all P < 0.05). ROC analysis showed that a serum HBDH cut-off point of 195.0 U/L had optimal predictive value for the development of persistent organ failure (AUC = 0.778) and 166.5 U/L for the development of SIRS (AUC = 0.724).

CONCLUSION

The elevated serum HBDH in early stage of AP is closely related to the adverse prognosis of AP patients, which can be used as a potential early biomarker for predicting the severity of AP.

Clinical features, laboratory findings and persistence of virus in 10 children with coronavirus disease 2019 (COVID-19)

Background

A pandemic caused by SARS-CoV-2 infection (COVID-19) has rapidly spread across the globe. Although many articles have established the clinical characteristics of adult COVID-19 patients so far, limited data are available for children. The aim of this study was to reveal the clinical features, laboratory findings and nucleic acid test results of ten pediatric cases.

Methods

In this retrospective single-center cohort study, pediatric cases with COVID-19 infection were consecutively enrolled in one hospital in Huangshi, China from January 1 to March 11, 2020.

Results

A total of 10 children with COVID-19 were recruited. Of them, four were the asymptomatic type, one was the mild type, and five were the moderate type (including two subclinical ones). All patients were from family clusters. Only fever, nasal discharge and nasal congestion were observed. Lymphopenia and leukopenia were uncommon in our sample but elevated levels of lactate dehydrogenase (LDH) and alpha-hydroxybutyrate dehydrogenase (α-HBDH) were observed frequently. Of these laboratory test variables, no statistical difference was identified between asymptomatic and symptomatic patients. Abnormalities in radiological data were detected in five patients, and representative findings of chest CT images were patchy shadows and ground-glass opacities. There were two cases whose oropharyngeal nucleic acid tests reversed to positive after one negative result, and two patients whose oropharyngeal swabs tested negative but rectal swabs showed positive.

Conclusions

Clinical symptoms were mild in children with COVID-19. Increased levels of LDH and α-HBDH were potential clinical biomarkers for pediatric cases. More attention should be paid to the SARS-CoV-2 viral assessment of rectal swabs before patients are discharged.