Elevated Lactate Dehydrogenase Level Predicts Postoperative Pneumonia in Patients with Aneurysmal Subarachnoid Hemorrhage

Diagnostic model for spontaneous bacterial peritonitis in cirrhotic patients with ascites: a multicenter cohort study

INTRODUCTION

Spontaneous bacterial peritonitis (SBP) is a potentially life-threatening complication of cirrhotic ascites. Early diagnosis and treatment of SBP are essential to improve the survival rates and prognosis of patients. We aimed to identify the predictors of SBP to establish a new noninvasive early diagnostic tool.

METHODS

We screened 1618 patients who underwent paracentesis due to cirrhotic ascites between January 2017 and December 2018 in three hospitals. We evaluated the symptomatic, clinical, and laboratory parameters to identify the predictors of SBP. The primary diagnostic model was displayed as a nomogram.

RESULTS

The model included abdominal pain, diarrhea, white blood cell count, neutrophil percentage, procalcitonin, C-reactive protein, lactate dehydrogenase, glucose, and Model for End-stage Liver Disease score. The model's diagnostic performance was good, with an AUC of 0.84 [95% confidence interval (CI), 0.81-0.87] in the training cohort. In the validation cohort, the diagnostic ability was also good, with AUCs of 0.87 (95% CI, 0.83-0.91) and 0.90 (95% CI, 0.87-0.94) for inner and outer validation queues, respectively. Moreover, the decision curve analysis confirmed the clinical utility of the nomogram model. In addition, we developed a Microsoft Excel calculation model to allow convenient adoption of the model in clinical practice.

CONCLUSION

We developed good performing diagnostic models for SBP.

Development and validation of a machine-learning model for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage

Pneumonia is a common postoperative complication in patients with aneurysmal subarachnoid hemorrhage (aSAH), which is associated with poor prognosis and increased mortality. The aim of this study was to develop a predictive model for postoperative pneumonia (POP) in patients with aSAH. A retrospective analysis was conducted on 308 patients with aSAH who underwent surgery at the Neurosurgery Department of the First Affiliated Hospital of Soochow University. Univariate and multivariate logistic regression and lasso regression analysis were used to analyze the risk factors for POP. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the constructed model. Finally, the effectiveness of modeling these six variables in different machine learning methods was investigated. In our patient cohort, 23.4% (n = 72/308) of patients experienced POP. Univariate, multivariate logistic regression analysis and lasso regression analysis revealed age, Hunt-Hess grade, mechanical ventilation, leukocyte count, lymphocyte count, and platelet count as independent risk factors for POP. Subsequently, these six factors were used to build the final model. We found that age, Hunt-Hess grade, mechanical ventilation, leukocyte count, lymphocyte count, and platelet count were independent risk factors for POP in patients with aSAH. Through validation and comparison with other studies and machine learning models, our novel predictive model has demonstrated high efficacy in effectively predicting the likelihood of pneumonia during the hospitalization of aSAH patients.

A Novel Machine Learning Model for Predicting Stroke-Associated Pneumonia After Spontaneous Intracerebral Hemorrhage

BACKGROUND

Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there is no consensus on SAP prediction, and application of existing predictors is limited. The aim of this study was to develop a machine learning model to predict SAP after sICH.

METHODS

We retrospectively reviewed 748 patients diagnosed with sICH and collected data from 4 dimensions-demographic features, clinical features, medical history, and laboratory tests. Five machine learning algorithms-logistic regression, gradient boosting decision tree, random forest, extreme gradient boosting, and category boosting-were used to build and validate the predictive model. We also applied recursive feature elimination with cross-validation to obtain the best feature combination for each model. Predictive performance was evaluated by area under the receiver operating characteristic curve.

RESULTS

SAP was diagnosed in 237 patients. The model developed by category boosting yielded the most satisfactory outcomes overall with area under the receiver operating characteristic curves in the training set and test set of 0.8307 and 0.8178, respectively.

CONCLUSIONS

The incidence of SAP after sICH in our center was 31.68%. Machine learning could potentially provide assistance in the prediction of SAP after sICH.

Development and performance assessment of novel machine learning models for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage patients: external validation in MIMIC-IV

Background

Postoperative pneumonia (POP) is one of the primary complications after aneurysmal subarachnoid hemorrhage (aSAH) and is associated with postoperative mortality, extended hospital stay, and increased medical fee. Early identification of pneumonia and more aggressive treatment can improve patient outcomes. We aimed to develop a model to predict POP in aSAH patients using machine learning (ML) methods.

Methods

This internal cohort study included 706 patients with aSAH undergoing intracranial aneurysm embolization or aneurysm clipping. The cohort was randomly split into a train set (80%) and a testing set (20%). Perioperative information was collected from participants to establish 6 machine learning models for predicting POP after surgical treatment. The area under the receiver operating characteristic curve (AUC), precision-recall curve were used to assess the accuracy, discriminative power, and clinical validity of the predictions. The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database.

Results

In this study, 15.01% of patients in the training set and 12.06% in the testing set with POP after underwent surgery. Multivariate logistic regression analysis showed that mechanical ventilation time (MVT), Glasgow Coma Scale (GCS), Smoking history, albumin level, neutrophil-to-albumin Ratio (NAR), c-reactive protein (CRP)-to-albumin ratio (CAR) were independent predictors of POP. The logistic regression (LR) model presented significantly better predictive performance (AUC: 0.91) than other models and also performed well in the external validation set (AUC: 0.89).

Conclusion

A machine learning model for predicting POP in aSAH patients was successfully developed using a machine learning algorithm based on six perioperative variables, which could guide high-risk POP patients to take appropriate preventive measures.

Elevated lactate dehydrogenase predicts pneumonia in spontaneous intracerebral hemorrhage

Background

Although a variety of risk factors for pneumonia after spontaneous intracerebral hemorrhage have been established, an objective and easily obtainable predictor is still needed. Lactate dehydrogenase is a nonspecific inflammatory biomarker. In this study, we aimed to assess the association between lactate dehydrogenase and pneumonia in spontaneous intracerebral hemorrhage patients.

Methods

Our study was a retrospective, multicenter cohort study, undertaken in 7562 patients diagnosed with spontaneous intracerebral hemorrhage from 3 hospitals. All serum Lactate dehydrogenase was collected within 7 days from admission and divided into four groups as quartile(Q). We conducted a multivariable logistic regression analysis to assess the association of Lactate dehydrogenase with pneumonia.

Results

Among a total of 7562 patients, 2971 (39.3%) patients were diagnosed with pneumonia. All grades of elevated lactate dehydrogenase were associated with increased raw and risk-adjusted risk of pneumonia. Multiple logistic regression analysis showed odds ratios for Q2-Q4 compared with Q1 were 1.21 (95% CI, 1.04-1.42), 1.64(95% CI, 1.41-1.92), and 1.92 (95% CI, 1.63-2.25) respectively. The odds ratio after adjustment was 4.42 (95% CI, 2.94-6.64) when lactate dehydrogenase was a continuous variable after log-transformed.

Conclusions

Elevated lactate dehydrogenase is significantly associated with an increase in the odds of pneumonia and has a predictive value for severe pneumonia in patients with pneumonia. Lactate dehydrogenase may be used to predict pneumonia events in spontaneous intracerebral hemorrhage patients as a laboratory marker.

One-year mortality prediction for patients with sepsis: a nomogram integrating lactic dehydrogenase and clinical characteristics

BACKGROUND

To explore the association between myocardial enzymes and one-year mortality, and establish a nomogram integrating myocardial enzymes and clinical characteristics to predict one-year mortality among sepsis patients.

METHODS

Data of 1,983 sepsis patients were extracted from Medical Information Mart for Intensive Care III database in this retrospective cohort study. All participants were randomly split into the training set for the development of model and testing set for the internal validation at the ratio of 7:3. Univariate logistic regression was used to screen variables with statistical differences which were made for stepwise regression, obtaining the predictors associated with one-year mortality of sepsis patients. Adopted multivariate logistic regression to assess the relationship between myocardial enzymes and one-year mortality of sepsis patients. A nomogram was established in predicting the one-year survival status of sepsis patients, and the performance of developed model were compared with LDH alone, sequential organ failure assessment (SOFA), simplified acute physiology score II (SAPS II) by receiver operator characteristic, calibration, and decision curves analysis.

RESULTS

The result found that LDH was associated with one-year mortality of sepsis patients [odds ratio = 1.28, 95% confidence interval (CI): 1.18-1.52]. Independent predictors, including age, gender, ethnicity, potassium, calcium, albumin, hemoglobin, alkaline phosphatase, vasopressor, Elixhauser score, respiratory failure, and LDH were identified and used to establish the nomogram (LDH-model) for predicting one-year mortality for sepsis patients. The predicted performance [area under curve (AUC) = 0.773, 95%CI: 0.748-0.798] of this developed nomogram in the training and testing sets (AUC = 0.750, 95%CI: 0.711-0.789), which was superior to that of LDH alone, SOFA score, SAPS II score. Additionally, calibration curve indicated that LDH-model may have a good agreement between the predictive and actual outcomes, while decision curve analysis demonstrated clinical utility of the LDH-model.

CONCLUSION

LDH level was related to the risk of one-year mortality in sepsis patients. A prediction model based on LDH and clinical features was developed to predict one-year mortality risk of sepsis patients, surpassing the predictive ability of LDH alone as well as conventional SAPS II and SOFA scoring systems.

Development and external validation of a nomogram for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage

Background

Postoperative pneumonia (POP) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH) associated with increased mortality rates, prolonged hospitalization, and high medical costs. It is currently understood that identifying pneumonia early and implementing aggressive treatment can significantly improve patients' outcomes. The primary objective of this study was to explore risk factors and develop a logistic regression model that assesses the risks of POP.

Methods

An internal cohort of 613 inpatients with aSAH who underwent surgery at the Neurosurgical Department of First Affiliated Hospital of Wenzhou Medical University was retrospectively analyzed to develop a nomogram for predicting POP. We assessed the discriminative power, accuracy, and clinical validity of the predictions by using the area under the receiver operating characteristic curve (AUC), the calibration curve, and decision curve analysis (DCA). The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database.

Results

Among patients in our internal cohort, 15.66% (n = 96/613) of patients had POP. The least absolute shrinkage and selection operator (LASSO) regression analysis identified the Glasgow Coma Scale (GCS), mechanical ventilation time (MVT), albumin, C-reactive protein (CRP), smoking, and delayed cerebral ischemia (DCI) as potential predictors of POP. We then used multivariable logistic regression analysis to evaluate the effects of these predictors and create a final model. Eighty percentage of patients in the internal cohort were randomly assigned to the training set for model development, while the remaining 20% of patients were allocated to the internal validation set. The AUC values for the training, internal, and external validation sets were 0.914, 0.856, and 0.851, and the corresponding Brier scores were 0.084, 0.098, and 0.143, respectively.

Conclusion

We found that GCS, MVT, albumin, CRP, smoking, and DCI are independent predictors for the development of POP in patients with aSAH. Overall, our nomogram represents a reliable and convenient approach to predict POP in the patient population.

Platelet-to-white blood cell ratio: A feasible predictor for unfavorable functional outcome in patients with aneurysmal subarachnoid hemorrhage

This study aimed to identify the association between the platelet-to-white blood cell ratio (PWR) and outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH). Data for patients diagnosed with aSAH and admitted from January 2015 to December 2020 were retrospectively analyzed. Multivariate logistic regression analysis was performed to identify factors that correlated with unfavorable outcomes at 3 months. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off value for the PWR to discriminate favorable and unfavorable outcomes at 3 months. The patients were then divided into two groups based on this cut-off value. To reduce selection bias, propensity score matching (PSM) was performed to balance the baseline characteristics. In total, 800 patients were enrolled in this study. The multivariate logistic regression analysis showed that the PWR (odds ratio, 1.05; 95% confidence interval, 1.00-1.09; p = 0.034) at admission was independently associated with unfavorable 3-month outcomes. ROC curve analysis identified 15.69 as the best cut-off PWR value for predicting clinical outcomes. After PSM, patients with a PWR < 15.69 exhibited a higher incidence of postoperative pneumonia (POP) (37.2% vs. 25.6%, p = 0.011) and unfavorable 3-month outcomes (19.3% vs. 12.1%, p = 0.043). These findings suggest that patients with aSAH showing a PWR < 15.69 at admission have a higher probability of developing POP, which may be the main factor causing unfavorable outcomes at 3 months.

Predictors of rapidly progressive interstitial lung disease and prognosis in Chinese patients with anti-melanoma differentiation-associated gene 5-positive dermatomyositis

Background

Rapidly progressive interstitial lung disease (RP-ILD) is the most serious complication of anti-melanoma differentiation-associated gene 5-positive dermatomyositis (anti-MDA5+ DM). This study was performed to assess the prognostic factors of patients with anti-MDA5+ DM and the clinical characteristics and predictors of anti-MDA5+ DM in combination with RP-ILD.

Methods

In total, 73 MDA5+ DM patients were enrolled in this study from March 2017 to December 2021. They were divided into survival and non-survival subgroups and non-RP-ILD and RP-ILD subgroups.

Results

The lactate dehydrogenase (LDH) concentration and prognostic nutritional index (PNI) were independent prognostic factors in patients with anti-MDA5+ DM: the elevated LDH was associated with increased mortality (p = 0.01), whereas the elevated PNI was associated with reduced mortality (p < 0.001). The elevated LDH was independent risk prognostic factor for patients with anti-MDA5+ DM (HR 2.42, 95% CI: 1.02-4.83, p = 0.039), and the elevated PNI was independent protective prognostic factor (HR, 0.27; 95% CI, 0.08 - 0.94; p = 0.039). Patients who had anti-MDA5+ DM with RP-ILD had a significantly higher white blood cell count and LDH concentration than those without RP-ILD (p = 0.007 and p = 0.019, respectively). In contrast, PNI was significantly lower in patients with RP-ILD than those without RP-ILD (p < 0.001). The white blood cell count and elevated LDH were independent and significant risk factors for RP-ILD (OR 1.54, 95% CI: 1.12 - 2.13, p = 0.009 and OR 8.68, 95% CI: 1.28 - 58.83, p = 0.027, respectively), whereas the lymphocyte was an independent protective factor (OR, 0.11; 95% CI, 0.01 - 0.81; p = 0.03).

Conclusion

The elevated LDH and elevated PNI were independent prognostic factors for patients with anti-MDA5+ DM. The elevated LDH was independent risk factor for RP-ILD. Patients with anti-MDA5+ DM could benefit from the measurement of LDH and PNI, which are inexpensive and simple parameters that could be used for diagnosis as well as prediction of the extent of lung involvement and prognosis.

Blood inflammatory biomarkers predict in-hospital pneumonia after endovascular treatment of aneurysm in patients with aneurysmal subarachoid hemorrhage

The systemic inflammatory response index (SIRI) is a well-known marker of systemic inflammation reflecting the body's inflammatory/immune state. The study aimed to evaluate the relationship between the SIRI on admission and aneurysmal subarachnoid hemorrhage (aSAH)-associated pneumonia and compare with other currently used bio-markers. We reviewed 562 successive patients with aneurysmal SAH who underwent endovascular treatment between January 2019 and September 2021. ASAH-associated pneumonia was diagnosed using the modified Centers for Disease Control and Prevention criteria. The SIRI on admission was calculated as monocyte count × neutrophil count / lymphocyte count. Multiple logistic regression models were used for data analysis. A total of 158 (28.11%) patients developed aSAH-associated pneumonia. Using the Multiple logistic regression analysis, a notable dose-response association was found between the elevated SIRI (fourth quartile) and aSAH-associated pneumonia (adjusted odds ratio = 6.759; 95% confidence interval [CI], 3.280-13.930; p < 0.001 [p for trend < 0.001]). The SIRI (0.701, 95% CI: 0.653-0.749) presented a higher area under the curve (AUC) than systemic immune- inflammation index (SII) (0.669, 95% CI: 0.620-0.718) (p = 0.089); neutrophil-to-lymphocyte ratio (NLR) (0.665, 95% CI: 0.616-0.714) (p = 0.035) and platelet-lymphocyte ratio (PLR) (0.587, 95% CI: 0.534-0.641) (p < 0.001). A higher SIRI on admission was associated with aSAH-associated pneumonia, which may guide further clinical trials of prophylactic antibiotic therapy.

Procalcitonin as a biomarker of nosocomial pneumonia in aneurysmal subarachnoid hemorrhage patients treated in neuro-ICU

BACKGROUND

Nosocomial pneumonia commonly develops in aneurysmal subarachnoid hemorrhage (aSAH) patients and is associated with poor prognosis of these patients. This study is designed to verify the predictive value of procalcitonin (PCT) on nosocomial pneumonia in aSAH patients.

METHODS

298 aSAH patients received treatments in the neuro-intensive care unit (NICU) of West China hospital were included. Logistic regression was conducted to verify the association between PCT level and nosocomial pneumonia and to construct a model for predicting pneumonia. Area under the receiver operating characteristic curve (AUC) were calculated to evaluate the accuracy of the single PCT and the constructed model.

RESULTS

90 (30.2%) patients developed pneumonia during hospitalizations among included aSAH patients. Pneumonia group had higher procalcitonin level (p < 0.001) than non-pneumonia group. The mortality (p < 0.001), mRS (p < 0.001), length of ICU stay (p < 0.001), length of hospital stay (p < 0.001) were both higher or longer in pneumonia group. Multivariate logistic regression indicated WFNS (p = 0.001), acute hydrocephalus (p = 0.007), WBC (p = 0.021), PCT (p = 0.046) and C-reactive protein (CRP) (p = 0.031) were independently associated with the development of pneumonia in included patients. The AUC value of procalcitonin for predicting nosocomial pneumonia was 0.764. Composed of WFNS, acute hydrocephalus, WBC, PCT and CRP, the predictive model for pneumonia has higher AUC of 0.811.

CONCLUSIONS

PCT is an available and effective predictive marker of nosocomial pneumonia in aSAH patients. Composed of WFNS, acute hydrocephalus, WBC, PCT and CRP, our constructed predictive model is helpful for clinicians to evaluate the risk of nosocomial pneumonia and guide therapeutics in aSAH patients.

Serum LDH levels may predict poor neurological outcome after aneurysmal subarachnoid hemorrhage

INTRODUCTION

Serum lactate dehydrogenase (LDH) levels are often elevated in cardiovascular diseases. Their prognostic role after subarachnoid hemorrhage (SAH) remains poorly evaluated.

METHODS

This is a retrospective single-center study of patients with non-traumatic SAH admitted to the intensive care unit (ICU) of an University Hospital from 2007 to 2022. Exclusion criteria were pregnancy and incomplete medical records or follow-up data. Baseline information, clinical data, radiologic data, the occurrence of neurological complications as well as serum LDH levels during the first 14 days of ICU stay were collected. Unfavorable neurological outcome (UO) at 3 months was defined as a Glasgow Outcome Scale of 1-3.

RESULTS

Five hundred and forty-seven patients were included; median serum LDH values on admission and the highest LDH values during the ICU stay were 192 [160-230] IU/L and 263 [202-351] IU/L, respectively. The highest LDH value was recorded after a median of 4 [2-10] days after ICU admission. LDH levels on admission were significantly higher in patients with UO. When compared with patients with favorable outcome (FO), patients with UO had higher serum LDH values over time. In the multivariate logistic regression model, the highest LDH value over the ICU stay (OR 1.004 [95% CI 1.002 - 1.006]) was independently associated with the occurrence of UO; the area under the receiving operator (AUROC) curve for the highest LDH value over the ICU stay showed a moderate accuracy to predict UO (AUC 0.76 [95% CI 0.72-0.80]; p < 0.001), with an optimal threshold of > 272 IU/L (69% sensitivity and 74% specificity).

CONCLUSIONS

The results in this study suggest that high serum LDH levels are associated with the occurrence of UO in SAH patients. As a readily and available biomarker, serum LDH levels should be evaluated to help with the prognostication of SAH patients.

Pre-operative prognostic nutrition index and post-operative pneumonia in aneurysmal subarachnoid hemorrhage patients

Background and objective

Post-operative pneumonia (POP), a common complication, may be associated with prolonged hospitalization and long-term mortality in aneurysmal subarachnoid hemorrhage (aSAH) patients. This study aimed to explore the association between pre-operative prognostic nutrition index (PNI) and POP in aSAH patients.

Methods

A total of 280 aSAH patients were enrolled from Nanjing Drum Tower Hospital. PNI was calculated as follows: [10 × albumin(gr/dl)] + [0.005 × absolute pre-operative lymphocyte count (per mm³)]. We utilized multivariate analyses, restricted cubic spline, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to elucidate the role of PNI in POP.

Results

Pre-operative PNI levels in the POP group were higher, compared with the non-POP group (41.0 [39.0, 45.4] vs. 44.4 [40.5, 47.3], P = 0.001). When we included PNI as a categorical variable in the multivariate analysis, the levels of PNI were associated with POP (odds ratio, 0.433; 95% confidence interval, 0.253-0.743; P=0.002). In addition, when we included PNI as a continuous variable in the multivariate analysis, the PNI levels were also associated with POP (odds ratio, 0.942; 95% confidence interval, 0.892-0.994; P = 0.028). The level of albumin was also a predictor of the occurrence of POP, with a lower diagnostic power than PNI [AUC: 0.611 (95% confidence interval, 0.549-0.682; P = 0.001) for PNI vs. 0.584 (95% confidence interval, 0.517-0.650; P = 0.017) for albumin]. Multivariable-adjusted spline regression indicated a linear dose-response association between PNI and POP in aSAH participants (P for linearity = 0.027; P for non-linearity = 0.130). Reclassification assessed by IDI and NRI was significantly improved with the addition of PNI to the conventional model of POP in aSAH patients (NRI: 0.322 [0.089-0.555], P = 0.007; IDI: 0.016 [0.001-0.031], P = 0.040).

Conclusion

The lower levels of pre-operative PNI may be associated with the higher incidence of POP in aSAH patients. Neurosurgeons are supposed to pay more attention to pre-operative nutrition status in aSAH patients.

Predictive Values of White Blood Cell Count in Peripheral Blood at Admission on In-Hospital Complications and 90-Day Outcomes of Patients with Aneurysmal Subarachnoid Hemorrhage: Insights from the LongTEAM Registry

PURPOSE

This study aimed to explore the relationship between white blood cells (WBCs) at admission and clinical outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH).

PATIENTS AND METHODS

We analyzed data from patients with aSAH between January 2015 and September 2021 who were included in the LongTEAM (Long-term Prognosis of Emergency Aneurysmal Subarachnoid Hemorrhage) registry study. WBC is classified into four groups according to the quartile. We used the logistic model for in-hospital complications, mortality, modified Rankin scale (mRS) at discharge and 90 days to examine the relationship between WBC and clinical outcomes. We used WBC levels near odds ratio (OR) = 1 (Q1) in restricted cubic splines as the reference to evaluate whether there is a nonlinear relationship between WBC and clinical outcomes. Another Kaplan-Meier method was used to analyze the relationship between WBC levels and the risk of developing pneumonia.

RESULTS

Of the 988 patients included, the results showed that compared with patients in the Q1 group, patients in the highest quartile (Q4) had an increased incidence of 90-day unfavorable outcomes after adjusting the confounders (adjusted OR = 1.81, 95% CI = 1.02-3.20, p = 0.042), which may be caused by the increased incidence and risk of pneumonia (adjusted OR = 2.06, 95% CI = 1.30-3.29, p = 0.002; adjusted hazard ratio [HR]=1.63, 95% CI = 1.13-2.36, p < 0.001). The restricted cubic spline indicated that the incidence of developing pneumonia and 90-day unfavorable outcomes rises with increasing WBC levels (p for nonlinear = 0.135 and 0.113).

CONCLUSION

Patients with higher WBC at admission were associated with an increased incidence of 90-day unfavorable outcomes, which might be related to pneumonia.

Lactate dehydrogenase predicting mortality in patients with aneurysmal subarachnoid hemorrhage

Objective

Lactate dehydrogenase (LDH) has been reported to be associated with outcomes after surgery in patients with aneurysmal subarachnoid hemorrhage (aSAH), but it is unclear if this is independent from other biomarkers and across all aSAH treatments. This study aims to assess whether LDH is an independent predictor of mortality in patients with aSAH and test whether the inclusion of LDH in a well‐established prediction model can improve discrimination and reclassification.

Methods

This was a retrospective observational study at a tertiary academic medical center. This study measured baseline LDH levels taken at admission and longitudinal LDH levels (up to a month postadmission) to assess median, max, and trajectory LDH levels. The primary outcome was mortality at 90 days. Multivariable regression analyses were used to evaluate associations between LDH and outcomes. The full original Subarachnoid Hemorrhage International Trialists' (SAHIT) model was used as the reference model.

Results

In total, 3524 patients with aSAH were included. LDH at admission was independently associated with mortality at 90 days (quartile 4 vs. 1: odds ratio 1.60; 95% CI 1.08–2.37) and mortality at the longest follow‐up (quartile 4 vs. 1: hazard ratio1.72; 95% CI 1.34–2.20). Compared with the SAHIT model, the addition of three LDH (admission, max, and median) levels to the SAHIT model significantly improved the area under the curve and categorical net reclassification improvement for prediction mortality.

Interpretation

In patients with aSAH, LDH level is an independent predictor of all‐cause mortality. The incorporation of LDH into a well‐established prediction model improved the ability to predict the risk of death in patients with aSAH.

Pre-Operative Predictors for Post-Operative Pneumonia in Aneurysmal Subarachnoid Hemorrhage After Surgical Clipping and Endovascular Coiling: A Single-Center Retrospective Study

Objective

Postoperative pneumonia (POP) is one of the major complications after aneurysmal subarachnoid hemorrhage (aSAH) associated with postoperative mortality, prolonged hospitalization, and increased medical cost. Early recognition of pneumonia and more aggressive management may improve patient outcomes.

Methods

We retrospectively reviewed all patients with aSAH who were admitted to our institution between January 2015 and December 2020. Baseline clinical characteristics, imaging data, and inflammatory biomarkers were reviewed. The risk factors derived from multivariate logistic regression of surgical clipping (SC) and endovascular coiling (EC) were analyzed. The area under the receiver operating characteristic (ROC) curve (AUC) was used to calculate each independent predictor's prediction ability.

Results

A total of 843 patients were enrolled. Compared with patients in the EC group, the incidence of POP was higher in the SC group [143/414 (34.54%) vs. 114/429 (26.57%), p = 0.015]. In the EC group, multivariate analysis revealed that age [p = 0.001; odds ratio (OR) = 1.04, 95% CI = 1.02–1.07], posterior circulation aneurysms (p = 0.021; OR = 2.07, 95% CI = 1.14–3.83), higher neutrophil (NEUT; p < 0.001; OR = 1.13, 95% CI = 1.06–1.21), World Federation of Neurosurgical Societies (WFNS) grade 4 or 5 (p < 0.001; OR = 4.84, 95% CI = 2.67–8.79), modified Fisher Scale (mFS) grade 3 or 4 (p = 0.022; OR = 2.60, 95% CI = 1.15–5.89), and acute hydrocephalus (p = 0.048; OR = 1.74, 95% CI = 1.01–3.00) were independent risk factors for POP. In the SC group, multivariate analysis revealed that age (p = 0.015; OR = 1.03, 95% CI = 1.01–1.05), WFNS grade 4 or 5 (p = 0.037; OR = 1.76, 95% CI = 1.03–3.00), heart disease (p < 0.001; OR = 5.02, 95% CI = 2.03–12.45), higher white blood cell (WBC; p < 0.001; OR = 1.13, 95% CI = 1.07–1.20), and mFS grade 3 or 4 (p = 0.019; OR = 2.34, 95% CI = 1.15–4.77) were independent risk factors for POP.

Conclusion

Patients treated with SC are more likely to develop POP. Comprehensive preoperative evaluation of patients may help physicians to better predict POP and implement preventive measures to improve outcomes.

Antiviral Treatments Eliminate the Adverse Impacts of High Baseline HBV Loads on the Survival of HBV-Related HCC Patients

Background

In consideration of no standard exclusion criteria for hepatitis B virus (HBV) loads in hepatocellular carcinoma (HCC)-related clinical trials, this study aimed to investigate the prevalence of HBV-related exclusion criteria among current clinical trials and evaluate whether antiviral treatments could eliminate the adverse effects from high HBV loads for HCC patients.

Methods

This is a retrospective study including 772 HCC clinical trials on ClinicalTrials.gov and 1784 HCC patients receiving antiviral treatment. The Kaplan–Meier (K-M) method was used to compare the progression-free survival (PFS) and overall survival (OS) between different groups, and Cox regression analyses were performed to validate possible risk factors on PFS and overall survival OS.

Results

Among 772 clinical trials, 58.3% did not adopt baseline HBV loads as exclusion criteria, 18.0% was 2000 IU/mL, and 10.5% was receiving antiviral therapy. We observed baseline HBV loads had no significant impact on PFS (p = 0.491, 0.155, 0.119, 0.788, 0.280, 0.683 respectively) and OS (p = 0.478, 0.741, 0.263, 0.039, 0.999, 0.581 respectively) in all patients or each treatment group including hepatectomy, radiofrequency ablation, interventional therapy, targeted drugs and anti-programmed cell death immunotherapy, except for the OS of interventional therapy group, where patients with high HBV loads had higher BCLC stage, serum AFP level and ALBI grade (p = 0.009, 0.015 and 0.003, respectively).

Conclusion

Antiviral treatments could eliminate the adverse impacts of high HBV loads on the survival of HCC patients. Simplified eligibility criteria can be adopted for HCC patients with HBV infection where regular antiviral therapy should be enough.

Lactic Dehydrogenase to Albumin Ratio Is Associated With the Risk of Stroke-Associated Pneumonia in Patients With Acute Ischemic Stroke

Background: Stroke-associated pneumonia (SAP) is one of the common complications of stroke patients. Higher lactic dehydrogenase (LDH) and lower albumin levels were associated with SAP, but the contribution of the LDH to albumin ratio (LAR) to the risk of SAP in acute ischemic stroke (AIS) patients remained unclear. Methods: A total of 3173 AIS patients were included in this study, divided into SAP (n = 417) and non-SAP groups (n = 2756). Characteristics were compared between these two groups. The receiver operating characteristic curves (ROC) were used to evaluate the discrimination ability of the LAR, LDH, and albumin levels in predicting SAP. Logistic regression analysis was furtherly adopted to estimate the association between LAR and SAP. We also used the restricted cubic spline (RCS) to clarify the relationship between LAR and the risk of SAP. Results: LAR in the SAP group was significantly higher than that of the non-SAP group (8.75 ± 4.58 vs. 6.10 ± 2.55, P < 0.001). According to the results of ROC, LAR had the highest prognostic accuracy compared to LDH and albumin (P < 0.05). Besides, the logistic regression model showed that higher LAR (LAR > 6.75) were more vulnerable to SAP (OR, 2.80; 95% CI, 2.18-3.59, P < 0.001), controlling the confounders. The RCS model showed that there was a non-linear relationship between LAR and the risk of SAP. Conclusion: High LAR was associated with an increased risk of SAP in patients with AIS. LAR may be a potential predictor for the incidence of SAP. Appropriate prevention measures were needed in patients with high LAR (LAR > 6.75).

A Scoring System for Predicting the Prognosis of Late-Onset Severe Pneumonia after Allogeneic Hematopoietic Stem Cell Transplantation

Late-onset severe pneumonia (LOSP) is defined as severe pneumonia developing during the late phase of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Because of the high mortality in patients with LOSP, it is important to identify prognostic factors. In this study, we aimed to develop a risk score system with broad applicability that can help predict the risk of LOSP-associated mortality. We retrospectively analyzed 100 patients with LOSP after allo-HSCT between June 2009 and July 2017. The assessment variables included immune, nutritional, and metabolic parameters at the onset of LOSP. Of these 100 patients, 45 (45%) eventually died, and 55 (55%) were positive for organisms, most commonly viruses. In the multivariate analysis, higher monocyte count (≥0.20 × 10⁹/L versus <0.20 × 10⁹/L; P = .001), higher albumin level (≥30.5 g/L versus <30.5 g/L; P = .044), lower lactic dehydrogenase level (<250 U/L versus ≥250 U/L; P = .008) and lower blood urea nitrogen concentration (<7.2 mmol/L versus ≥7.2 mmol/L; P = .026) at the onset of LOSP were significantly associated with better 60-day survival. A risk score system based on the foregoing results showed that the probability of 60-day survival decreased with increasing risk factors, from 96.3% in the low-risk group to 49.1% in the intermediate-risk group and 12.5% in the high-risk group. Our results indicate that this scoring system using 4 variables can stratify patients with different probabilities of survival after LOSP, which suggests that patients' immune, nutritional, and metabolic status are crucial factors in determining outcome.

Nomogram based on albumin and neutrophil-to-lymphocyte ratio for predicting postoperative complications after pancreaticoduodenectomy

Background

The aim of this study was to identify a preoperative inflammatory marker with the most predictive value for postoperative complications after pancreaticoduodenectomy (PD). We then combined it with other perioperative variables to construct and validate a nomogram for complications after PD.

Methods

A total of 223 patients who received PD from January 2014 to July 2019 at a high-volume (>60 PDs/year) pancreatic centers in China were included in this retrospective study. All of the PDs were performed by the same surgeon who is beyond the learning curve with more than 100 PDs over the previous 3 years before 2014. 15 preoperative inflammatory markers were collected, including neutrophils, lymphocytes, high-sensitivity C-reactive protein and lactic dehydrogenase. The inflammatory markers' predicting abilities for complications were analyzed by calculating the values of an area under the curve (AUC). The complications included surgical complications (such as pancreatic fistula, delayed gastric emptying and bile leakage) and medical complications (such as sepsis, pneumonia, urinary tract infection, acute heart failure and acute liver failure) in this study. Univariable and multivariable logistic regression analyses were performed to investigate the perioperative features for independent risk factors for complications after PD. Nomograms with or without the most predictive inflammatory for complications were subsequently developed based on multivariable logistic regression using Akaike information criterion. Nomograms' performance was quantified and compared in terms of calibration and discrimination. We studied the utility of the nomograms using decision curve analysis.

Results

The albumin/ NLR score (ANS) exhibited the highest AUC value (0.616) for predicting postoperative complications. ANS and approach method were identified as independent risk factors for complications. The nomogram with ANS had higher C-index (0.725) and better calibration. The NRI compared between nomograms was 0.160 (95% CI: 0.023-0.296; P=0.022). By decision curve analysis, the model with ANS had higher clinical value.

Conclusions

The ANS is a useful predictor and an independent risk factor for postoperative complications after PD. The nomogram with ANS was constructed with better performance and more clinical benefit for predicting postoperative complications.

High serum lactate dehydrogenase and dyspnea: Positive predictors of adverse outcome in critical COVID-19 patients in Yichang

BACKGROUND

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in China, constitutes a Public Health Emergency of International Concern. It is well known that COVID-19 patients may have increased serum lactate dehydrogenase (LDH) levels in the early stage. The clinical changes in LDH may have predictive value in disease evolution and prognosis in critically ill COVID-19 patients.

AIM

To examine serum LDH and clinical characteristics in patients with COVID-19 and their predictive value for prognosis.

METHODS

This retrospective study analyzed the clinical data of forty-seven critical COVID-19 patients in the intensive care unit of the Third People's Hospital of Yichang City from January 27 to March 25, 2020 and divided them into survivors and non-survivors. The patients were diagnosed according to the World Health Organization interim guidance and critical cases met any one of the following criteria: Respiratory failure and required mechanical ventilation, the occurrence of shock, and the combined failure of other organs that required intensive care unit monitoring and treatments, according to the diagnostic criteria of critical COVID-19. Clinical data including symptoms, detection of SARS-CoV-2, chest computed tomography (CT) images, changes in serum LDH in different clinical phases, and prognosis were collected. Statistical analysis of the data was performed. Continuous variables were expressed as median (interquartile range) and compared with the Mann-Whitney U test. Categorical variables were compared with the Chi-square test. Survival data were analyzed using Kaplan-Meier survival curves and log-rank tests.

RESULTS

According to chest CT images, we observed the alveolitis and fibrosis stages in all critical patients in this study. Most non-survivors died in the fibrosis stage. Non-survivors had fewer days of hospitalization, shorter disease duration, shorter duration of alveolitis and fibrosis, and had dyspnea symptoms at disease onset (P = 0.05). Both first and lowest LDH values in the alveolitis stage were more pronounced in non-survivors than in survivors (449.0 U/L vs 288.0 U/L, P = 0.0243; 445.0 U/L vs 288.0 U/L, P = 0.0199, respectively), while the first, lowest and highest values of serum LDH in non-survivors were all significantly increased compared to survivors in the fibrosis phase (449.0 U/L vs 225.5 U/L, P = 0.0028; 432.0 U/L vs 191.0 U/L, P = 0.0007; 1303.0 U/L vs 263.5 U/L, P = 0.0001, respectively). The cut-off points of first LDH values in the alveolitis and fibrosis phase for distinction of non-survivors from survivors were 397.0 U/L and 263.0 U/L, respectively. In the fibrosis stage, non-survivors had more days with high LDH than survivors (7.0 d vs 0.0 d, P = 0.0002). Importantly, patients with high LDH had a significantly shorter median survival time than patients with low LDH in the alveolitis phase (22.0 d vs 36.5 d, P = 0.0002), while patients with high LDH also had a significantly shorter median survival time than patients with low LDH in the fibrosis phase (27.5 d vs 40.0 d, P = 0.0008). The proportion of non-survivors with detectable SARS-CoV-2 until death in the alveolitis stage was significantly increased compared with that in the fibrosis stage (100% vs 35.7%, P = 0.0220).

CONCLUSION

High LDH and dyspnea symptoms were positive predictors of an adverse outcome in critical COVID-19. The rapid progressive fibrosis stage was more perilous than the alveolitis stage, even if SARS-CoV-2 is undetectable.