Early variations of laboratory parameters predicting shunt-dependent hydrocephalus after subarachnoid hemorrhage

Risk factors of shunt-dependent hydrocephalus after subarachnoid hemorrhage: a systematic review and meta-analysis based on observational cohort studies

Shunt dependent hydrocephalus (SDHC) is a common sequel after aneurysmal subarachnoid hemorrhage (aSAH) and factors contributing to the development of SDHC remain obscure. The aim of this study was to identify predictors of SDHC following aSAH. We conducted a systematic review based on the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. We searched electronic databases including Pubmed, Embase, and Cochrane databases from 1980 through August 2019 for studies on the risk factors of SDHC after aSAH. Inclusion criteria were: (1) SAH and hydrocephalus confirmed by CT or magnetic resonance imaging findings; (2) the odds ratios (ORs) or the relative risk (RR) with 95% confidence interval (95%CI; or crude data that allowed their calculation) were reported; and (3) languages were restricted to English and Chinese. Two independent authors collected the data including study design, characteristics of patients and potential risk factors. Random-effects models were used to estimate weighted mean differences (WMD), relative risks (RR) with corresponding 95% confidence intervals (CI). For analysis with significant heterogeneity, subgroup analyses stratified by study design and geographic area were performed. In all, 37 cohort studies met inclusion criteria. Several factors were associated with SDHC. Infection, acute hydrocephalus, placement of external ventricular drainage, older age, higher Hunt and Hess grade, intraventricular hemorrhage, rebleeding, and mechanical ventilation were associated with greater 2-fold increased risk of SDHC. Vasospasm, female gender, high Fisher grade, preexisting hypertension, aneurysm in posterior location and intracerebral hemorrhage were associated with less than 2-fold increased risk. Treatment modality and diabetes mellitus were not associated with SDHC. SDHC is a multi-factorial disease that is associated with patient and treatment factors. Acknowledgement of these potential factors could help prevent SDHC.

Cytotoxic Lesions of the Corpus Callosum Associated with Aneurysmal Subarachnoid Hemorrhage May Influence Shunt-Dependent Chronic Hydrocephalus

BACKGROUND

Cytotoxic lesions of the corpus callosum (CLOCCs) are occasionally associated with aneurysmal subarachnoid hemorrhage (aSAH). The effects of aSAH on clinical outcomes in such cases are unclear. The present study aimed to investigate the frequency and characteristics of CLOCCs associated with aSAH to ascertain the predictors of shunt-dependent chronic hydrocephalus (SDCH) after aSAH.

METHODS

We retrospectively investigated cases of aSAH treated by coil embolization. Patients were divided into those with and without CLOCCs. Between-group differences were evaluated, including clinical outcomes and the characteristics of both the patients and the aneurysms. Patients were divided into those with and without SDCH to identify predictive factors of SDCH after aSAH focusing on CLOCCs.

RESULTS

This single-center study included 196 patients with aSAH. All patients received coil embolization between April 2013 and March 2020. CLOCCs were detected in 38 (19.4%) patients. In the group with CLOCCs, male sex, poor severity grade at onset, acute hydrocephalus, SDCH (all P < 0.01), and Fisher group 3 or 4 (P = 0.04) were significantly more common than in the group without CLOCCs. Diabetes and CLOCCs were significant predictors of SDCH after aSAH in multivariate analysis (diabetes: P < 0.01, odds ratio: 6.73, 95% confidence interval: 1.61-28.09; CLOCCs: P < 0.01, odds ratio: 6.86, 95% confidence interval: 2.87-16.38).

CONCLUSIONS

CLOCCs and SDCH were common in patients with poor-grade aSAH, and CLOCCs were independent predictors of SDCH after aSAH. Meticulous follow-up is necessary to detect SDCH after aSAH, especially in patients with poor-grade aSAH and CLOCCs.

Risk assessment and stratification of mild cognitive impairment among the Chinese elderly: attention to modifiable risk factors

BACKGROUND

The early identification of individuals at risk of mild cognitive impairment (MCI) has major public health implications for Alzheimer's disease prevention.

OBJECTIVE

This study aims to develop and validate a risk assessment tool for MCI with a focus on modifiable factors and a suggested risk stratification strategy.

METHODS

Modifiable risk factors were selected from recent reviews, and risk scores were obtained from the literature or calculated based on the Rothman-Keller model. Simulated data of 10 000 subjects with the exposure rates of the selected factors were generated, and the risk stratifications were determined by the theoretical incidences of MCI. The performance of the tool was verified using cross-sectional and longitudinal datasets from a population-based Chinese elderly cohort.

RESULTS

Nine modifiable risk factors (social isolation, less education, hypertension, hyperlipidaemia, diabetes, smoking, drinking, physical inactivity and depression) were selected for the predictive model. The area under the curve (AUC) was 0.71 in the training set and 0.72 in the validation set for the cross-sectional dataset. The AUCs were 0.70 and 0.64 in the training and validation sets, respectively, for the longitudinal dataset. A combined risk score of 0.95 and 1.86 was used as the threshold to categorise MCI risk as 'low', 'moderate' and 'high'.

CONCLUSION

A risk assessment tool for MCI with appropriate accuracy was developed in this study, and risk stratification thresholds were also suggested. The tool might have significant public health implications for the primary prevention of MCI in elderly individuals in China.

VPS dependency after aneurysmal subarachnoid haemorrhage and influence of admission hyperglycaemia

Introduction

Hydrocephalus after aneurysmal subarachnoid haemorrhage (aSAH) is a common complication which may lead to insertion of a ventriculoperitoneal shunt (VPS). Our aim is to evaluate a possible influence of specific clinical and biochemical factors on VPS dependency with special emphasis on hyperglycaemia on admission.

Patients and methods

Retrospective analysis of a monocentric database of aSAH patients. Using univariable and multivariable logistic regression analysis we evaluated factors influencing VPS dependency, with a special focus on hyperglycaemia on blood sample within 24 h of admission, dichotomised at 126 mg/dl. Factors evaluated in the univariable analysis were age, sex, known diabetes, Hunt and Hess grade, Barrow Neurological Institute scale, treatment modality, extra-ventricular drain (EVD) insertion, complications (rebleeding, vasospasm, infarction, decompressive craniectomy, ventriculitis), outcome variables and laboratory parameters (glucose, C-reactive protein, procalcitonin).

Results

We included 510 consecutive patients treated with acute aSAH requiring a VPS (mean age 58.2 years, 66% were female). An EVD was inserted in 387 (75.9%) patients. In the univariable analysis, VPS dependency was associated with hyperglycaemia on admission (OR 2.56, 95%CI 1.58-4.14, p < 0.001). In the multivariable regression analysis after stepwise backward regression, factors associated with VPS dependency were hyperglycaemia >126 mg/dl on admission (OR 1.93, 95%CI 1.13-3.30, p = 0.02), ventriculitis (OR 2.33, 95%CI 1.33-4.04, p = 0.003), Hunt and Hess grade (overall p-value 0.02) and decompressive craniectomy (OR 2.68, 95%CI 1.55-4.64, p < 0.001).

Conclusion

Hyperglycaemia on admission was associated with an increased probability of VPS placement. If confirmed, this finding might facilitate treatment of these patients by accelerating insertion of a permanent draining system.

Determinants of depressive symptom trajectories in self-reported chronic obstructive pulmonary disease patients

BACKGROUND

The depressive symptom trajectories of COPD individuals and its' predictors remain to be established. Therefore, this study aimed to explore the trajectories of depressive symptoms and predictors thereof in COPD patients.

METHODS

A total of 1286 individuals over 45 years of age with self-reported COPD were assessed. Depressive symptoms were evaluated using the Center for Epidemiological Studies Depression Scale short form, with depressive symptom trajectories being identified via latent class growth analysis. The predictors of depressive symptom trajectories were then identified through multinomial logistic regression.

RESULTS

Finally, three depressive symptom trajectories were identified: "steadily high", "consistently moderate", and "consistently low". Old age, longer night-time sleep duration, and high BMI were found to be associated with individuals being classified under the "consistently moderate" trajectory. Moreover, participants exhibiting more than two chronic conditions were more likely to be classified under the "consistently moderate" trajectory. Higher education and lower hand grip strength were important predictors of individuals classified in the "steadily high" trajectory.

CONCLUSIONS

To conclude, three depressive symptom trajectories were identified in self-reported COPD individuals. To ensure timely intervention aimed at preventing the worsening of depressive symptom progression among COPD individuals, health-care workers should regular analyze depressive symptoms and provide appropriate interventions when possible.

Invasive pulmonary aspergillosis caused by Aspergillus terreus diagnosed using virtual bronchoscopic navigation and endobronchial ultrasonography with guide sheath and successfully treated with liposomal amphotericin B

Invasive aspergillosis is a significant cause of mortality in patients with hematological malignancy. Early diagnosis of invasive pulmonary aspergillosis (IPA) by bronchoscopy is recommended but is often difficult to perform because of small lesion size and bleeding risk due to thrombocytopenia. A 71-year-old woman had received initial induction therapy for acute myeloid leukemia. On day 22 of chemotherapy, she had a high fever, and the chest computed tomography scan revealed a 20-mm-sized nodule with a halo sign. Bronchoscopy assisted by virtual bronchoscopic navigation (VBN) and endobronchial ultrasonography with a guide sheath (EBUS-GS) was performed, and Aspergillus terreus was identified from the culture of obtained specimens. A. terreus is often resistant to amphotericin B; thus, voriconazole is usually recommended for treatment. However, the obtained A. terreus isolate showed minimal inhibitory concentrations of 2 µg/mL for voriconazole and 0.5 µg/mL for amphotericin B. Therefore, the patient was successfully treated with liposomal amphotericin B. For patients suspected of having IPA, early diagnosis and drug susceptibility testing are very important. This case suggests that bronchoscopy using VBN and EBUS-GS is helpful for accurate diagnosis and successful treatment even if the lesion is small and the patient has a bleeding risk.

Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage

BACKGROUND

Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), and reliable prognosis methods have been sought in recent years to reduce morbidity and costs associated with delayed treatment or neglected onset. Machine learning (ML) defines modern data analysis techniques allowing accurate subject-based risk stratifications. We aimed at developing and testing different ML models to predict shunt-dependent hydrocephalus after aneurysmal SAH.

METHODS

We consulted electronic records of patients with aneurysmal SAH treated at our institution between January 2013 and March 2019. We selected variables for the models according to the results of the previous works on this topic. We trained and tested four ML algorithms on three datasets: one containing binary variables, one considering variables associated with shunt-dependency after an explorative analysis, and one including all variables. For each model, we calculated AUROC, specificity, sensitivity, accuracy, PPV, and also, on the validation set, the NPV and the Matthews correlation coefficient (ϕ).

RESULTS

Three hundred eighty-six patients were included. Fifty patients (12.9%) developed shunt-dependency after a mean follow-up of 19.7 (± 12.6) months. Complete information was retrieved for 32 variables, used to train the models. The best models were selected based on the performances on the validation set and were achieved with a distributed random forest model considering 21 variables, with a ϕ = 0.59, AUC = 0.88; sensitivity and specificity of 0.73 (C.I.: 0.39-0.94) and 0.92 (C.I.: 0.84-0.97), respectively; PPV = 0.59 (0.38-0.77); and NPV = 0.96 (0.90-0.98). Accuracy was 0.90 (0.82-0.95).

CONCLUSIONS

Machine learning prognostic models allow accurate predictions with a large number of variables and a more subject-oriented prognosis. We identified a single best distributed random forest model, with an excellent prognostic capacity (ϕ = 0.58), which could be especially helpful in identifying low-risk patients for shunt-dependency.

Hypernatremia is associated with poorer outcomes following aneurysmal subarachnoid hemorrhage: a nationwide inpatient sample analysis

BACKGROUND

Hypernatremia is one of the most common electrolyte disturbances following aneurysmal subarachnoid hemorrhage (aSAH) and has been correlated with increased mortality in single institution studies. We investigated this association using a large nationwide healthcare database.

METHODS

We performed a retrospective analysis of adults between 2002 and 2011 with a primary diagnosis of aSAH using the Nationwide Inpatient Sample (NIS). Patients were grouped according to whether or not an inpatient diagnosis of hypernatremia was present. The primary outcome was the NIS-SAH outcome measure. Secondary outcomes included in-hospital mortality, length of stay (LOS), and non-routine hospital discharge. Outcomes analyses adjusted for SAH severity using the NIS-SAH Severity Score, Charlson Comorbidity Index, and the presence of cerebral edema.

RESULTS

A total of 18,377 patients were included in the study. The incidence of a poor outcome as defined by the NIS-SAH outcome measure was 65.9% in the hypernatremia group and 33.4% in the normonatremia group (OR 1.96, 95% CI 1.68 - 2.27). There was higher mortality in the hypernatremia group (OR 1.60, 95% CI 1.37 - 1.87). Patients with hypernatremia had a significantly higher rate of non-routine hospital discharge and gastrostomy. The incidences of poor outcome, in-hospital mortality, and non-routine disposition were higher in the hypernatremia group regardless of treatment type (clipping vs. endovascular embolization). Pulmonary complications and acute kidney injury were more common in the hypernatremia group as well.

CONCLUSIONS

In patients with aSAH, hypernatremia is associated with poorer functional outcomes regardless of SAH severity.