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

Abstract

Background and purposeHydrocephalus is a frequent complication following subarachnoid hemorrhage. Few studies investigated the association between laboratory parameters and shunt-dependent hydrocephalus. This study aimed to investigate the variations of laboratory parameters after subarachnoid hemorrhage. We also attempted to identify predictive laboratory parameters for shunt-dependent hydrocephalus.MethodsMultiple imputation was performed to fill the missing laboratory data using Bayesian methods in SPSS. We used univariate and multivariate Cox regression analyses to calculate hazard ratios for shunt-dependent hydrocephalus based on clinical and laboratory factors. The area under the receiver operating characteristic curve was used to determine the laboratory risk values predicting shunt-dependent hydrocephalus.ResultsWe included 181 participants with a mean age of 54.4 years. Higher sodium (hazard ratio, 1.53; 95% confidence interval, 1.13–2.07; p = 0.005), lower potassium, and higher glucose levels were associated with higher shunt-dependent hydrocephalus. The receiver operating characteristic curve analysis showed that the areas under the curve of sodium, potassium, and glucose were 0.649 (cutoff value, 142.75 mEq/L), 0.609 (cutoff value, 3.04 mmol/L), and 0.664 (cutoff value, 140.51 mg/dL), respectively.ConclusionsDespite the exploratory nature of this study, we found that higher sodium, lower potassium, and higher glucose levels were predictive values for shunt-dependent hydrocephalus from postoperative day (POD) 1 to POD 12–16 after subarachnoid hemorrhage. Strict correction of electrolyte imbalance seems necessary to reduce shunt-dependent hydrocephalus. Further large studies are warranted to confirm our findings.

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

“…Continuous variables were given as means ± standard deviation (SD) and medians (interquartile range [IQR]) when normally and non-normally distributed, respectively, whereas categorical variables were given as frequencies (%). One-way ANOVAs were used to compare differences in CES-D scores among time points, with missing data being filled via multiple imputation using Bayesian methods [ 22 ]. Baseline predictors of different depressive symptom trajectories were identified via multinomial logistic analysis.…”

VPS dependency after aneurysmal subarachnoid haemorrhage and influence of admission hyperglycaemia

“…Incidence of post aSAH hydrocephalus has been reported to lie between 6% and 67%, up to 50% of patients end up needing a VPS. [6][7][8][9][10][11][12][13] Several risk factors such as increased age, female sex, rebleeding, intraventricular haemorrhage, higher Fisher and Hunt and Hess (HH) grades have been reported. [14][15][16][17][18] Only a few studies have looked at the association between hyperglycaemia and future VPS dependency and even less evaluated hyperglycaemia on admission.…”

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

“…Several studies have tried to identify potential predictors of shunt-dependency to estimate prognosis, to offer the best treatment strategy by preventing complications associated with unnecessary treatment or delayed surgical intervention, and to reduce hospitalization and rehabilitation length and costs [1, 5, 8, 9, 11-13, 16, 17, 21-23, 25, 27, 29, 31, 33, 35, 36, 39, 43, 46-48, 50]. Among these variables, some have been proposed, like the patient's age and gender [22,23,33,35,36,47,48], the neurological status at presentation (Hunt & Hess and WFNS scales) [12, 20-22, 25, 27, 47, 48], the amount of cisternal blood on the first CT scan (Fisher and BNI scales) [12, 16, 21-23, 25, 35, 47], the presence of acute hydrocephalus on the first CT scan and the need for external ventricular drain (EVD) [1, 12, 21-23, 25, 27, 33, 36, 43, 47, 48], the duration of EVD treatment [25,48], aneurysms location and size [9,22,25,33,36,47], the type of treatment for aneurysm exclusion (endovascular or surgical) [9,25,35,36,50], the onset and duration of posttreatment complications (i.e., fever and/or infections) [25,27,36,47,50], the duration of blood clearance detected on serial CT scans [29], and altered values of blood or cerebrospinal fluid (CSF) markers [27,31,46]. Some meta-analyses [11,45,47,50] have synthesized this information, and scores fo...…”

“…Several studies have tried to identify potential predictors of shunt-dependency to estimate prognosis, to offer the best treatment strategy by preventing complications associated with unnecessary treatment or delayed surgical intervention, and to reduce hospitalization and rehabilitation length and costs [ 1 , 5 , 8 , 9 , 11 – 13 , 16 , 17 , 21 – 23 , 25 , 27 , 29 , 31 , 33 , 35 , 36 , 39 , 43 , 46 – 48 , 50 ]. Among these variables, some have been proposed, like the patient’s age and gender [ 22 , 23 , 33 , 35 , 36 , 47 , 48 ], the neurological status at presentation (Hunt & Hess and WFNS scales) [ 12 , 20 – 22 , 25 , 27 , 47 , 48 ], the amount of cisternal blood on the first CT scan (Fisher and BNI scales) [ 12 , 16 , 21 – 23 , 25 , 35 , 47 ], the presence of acute hydrocephalus on the first CT scan and the need for external ventricular drain (EVD) [ 1 , 12 , 21 – 23 , 25 , 27 , 33 , 36 , 43 , 47 , 48 ], the duration of EVD treatment [ 25 , 48 ], aneurysms location and size [ 9 , 22 , 25 , 33 , 36 , 47 ], the type of treatment for aneurys...…”