METHODS: Literature databases were searched to June 2019. Observational studies were eligible if they measured short-term BPV, defined as variability in blood pressure measurements acquired either over a 24-hour period or several days. Data were extracted on method of BPV and reported association (or not) on future cardiovascular events, cardiovascular mortality and all-cause mortality. Methodological quality was assessed using the CASP observational study tool and data narratively synthesised.
RESULTS: Sixty-one studies including 3,333,801 individuals were eligible. BPV has been assessed by various methods including ambulatory and home-based BP monitors assessing 24-hour, "day-by-day" and "week-to-week" variability. There was moderate quality evidence of an association between BPV and cardiovascular events (43 studies analysed) or all-cause mortality (26 studies analysed) irrespective of the measurement method in the short- to longer-term. There was moderate quality evidence reporting inconsistent findings on the potential association between cardiovascular mortality, irrespective of methods of BPV assessment (17 studies analysed).
CONCLUSION: An association between BPV, cardiovascular mortality and cardiovascular events and/or all-cause mortality were reported by the majority of studies irrespective of method of measurement. Direct comparisons between studies and reporting of pooled effect sizes were not possible.
CASE REPORT: A 68-year-old lady with a history of multiple craniotomies and hemifacial resections for meningothelial meningioma currently underwent orbital exenteration, tumour debulking and cervical nodal excision for tumour recurrence. Histopathological examination of the tumour showed atypical meningioma, with cervical nodal metastasis.
DISCUSSION: This case report presents a rare finding of lymph node metastasis associated with atypical meningioma. The previous history of surgical resection is a known risk factor for metastasis for low to intermediate grade meningioma. Tumour biology and histology are predictors of metastasis. Haematogenous dissemination is the commonest route of metastasis. No standardised management protocol has been developed and the prognosis remains unknown.
METHODS: This retrospective study presents a total of 257 operations in 243 patients from 2 hospitals. A total of 130 cases were operated under LA sedation in hospital 1 and 127 cases under GA in hospital 2. Patient demographics and presenting features were similar at baseline.
RESULTS: Values are shown as LA sedation versus GA. Postoperatively, most patients recovered well in both groups with Glasgow Outcome Scale scores of 4-5 (96.2% vs. 88.2%, respectively). The postoperative morbidity was significantly increased by an odds ratio of 5.44 in the GA group compared with the LA sedation group (P = 0.005). The mortality was also significantly higher in the GA group (n = 5, 3.9%) than the LA sedation group (n = 0, 0.0%; P = 0.028). The CSDH recurrence rate was 4.6% in the LA sedation group versus 6.3% in the GA group. No intraoperative conversion from LA sedation to GA was reported.
CONCLUSIONS: This study demonstrates that CSDH drainage under LA sedation is safe and efficacious, with a significantly lower risk of postoperative mortality and morbidity when compared with GA.
METHODS: After 10 min of supine rest, the subject was tilted at a 70-degree angle on a tilt table for approximately a total of 35 min. 400 µg of glyceryl trinitrate (GTN) was administered sublingually after the first 20 min and monitoring continued for another 15 min. Mean imputation and K-nearest neighbors (KNN) imputation approaches to handle missing values. Next, feature selection techniques were implemented, including genetic algorithm, recursive feature elimination, and feature importance, to determine the crucial features. The Mann-Whitney U test was then performed to determine the statistical difference between two groups. Patients with VVS are categorized via machine learning models including Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), Multinomial Naïve Bayes (MNB), KNN, Logistic Regression (LR), and Random Forest (RF). The developed model is interpreted using an explainable artificial intelligence (XAI) model known as partial dependence plot.
RESULTS: A total of 137 subjects aged between 9 and 93 years were recruited for this study, 54 experienced clinical symptoms were considered positive tests, while the remaining 83 tested negative. Optimal results were obtained by combining the KNN imputation technique and three tilting features with SVM with 90.5% accuracy, 87.0% sensitivity, 92.7% specificity, 88.6% precision, 87.8% F1 score, and 95.4% ROC (receiver operating characteristics) AUC (area under curve).
CONCLUSIONS: The proposed algorithm effectively classifies VVS patients with over 90% accuracy. However, the study was confined to a small sample size. More clinical datasets are required to ensure that our approach is generalizable.
OBJECTIVE: Department of Neurosurgery Sarawak aimed to evaluate the surgical outcome of carpal tunnel release done over five years.
METHODS: The carpal tunnel surgeries were done under local anaesthesia (LA) given by neurosurgeons (Bupivacaine 0.5% or Lignocaine 2%). Monitored anaesthesia care (MAC) was later introduced by our hospital neuroanaesthetist in the beginning of 2018 (Target-controlled infusion propofol and boluses of fentanyl). We looked into our first 17 cases and compared these to the two anaesthesia techniques (LA versus MAC + LA) in terms of patient's pain score based on visual analogue scale (VAS).
RESULTS: Result showed MAC provided excellent pain control during and immediately after the surgery. None experienced anaesthesia complications. There was no difference in pain control at post-operation one month. Both techniques had equal good clinical outcome during patients' clinic follow up.
CONCLUSION: Neurosurgeons provide alternative route for CTS patients to receive surgical treatment. Being a designated pain free hospital, anaesthetist collaboration in carpal tunnel surgery is an added value and improves patients overall experience and satisfaction.
Objectives: Brain volume reduction occurs with age, especially in Parkinson plus syndrome or psychiatric disorders. We searched to define the degree of volume discrepancy in advanced IPD patients and correlate the anatomical volumetric changes to motor symptoms and cognitive function.
Methods: We determined the magnetic resonance imaging (MRI)-based volumetry of deep brain nuclei and brain structures of DBS-IPD group and matched controls.
Results: DBS-IPD group had significant deep nuclei atrophy and volume discrepancy, yet none had cognitive or psychobehavioural disturbances. Globus pallidus volume showed positive correlation to higher mental function.
Conclusion: The morphometric changes and clinical severity discrepancy in IPD may imply a more complex degenerative mechanism involving multiple neural pathways. Such alteration could be early changes before clinical manifestation.
METHODS: The MELoR study recruited community-dwelling adults aged 55 years and over, selected through stratified random sampling from three parliamentary constituencies. The baseline data collected during the first wave was obtained through face-to-face interviews in participants' homes using computer-assisted questionnaires. During their baseline assessments, participants were asked whether they had ever experienced a blackout in their lifetime and if they had experienced a blackout in the preceding 12 months.
RESULTS: Information on blackouts and ethnicity were available for 1530 participants. The weight-adjusted lifetime cumulative incidence of syncope for the overall population aged 55 years and above was 27.7%. The estimated lifetime cumulative incidence according to ethnic groups was 34.6% for Malays, 27.8% for Indians and 23.7% for Chinese. The estimated 12-month incidence of syncope was 6.1% overall, equating to 11.7% for Malays, 8.7 % for Indians and 2.3% for Chinese. Both Malay [odds ratio (OR) 1.46; 95% confidence interval (CI) 1.10-1.95 and OR 3.62, 95% CI 1.96-6.68] and Indian (OR 1.34; 95% CI 1.01-1.80 and OR 3.31, 1.78-6.15) ethnicities were independently associated with lifetime and 12-month cumulative incidence of syncope, respectively, together with falls, dizziness and myocardial infarction.
CONCLUSION: Ethnic differences exist for lifetime cumulative incidence of syncope in community-dwelling individuals aged 55 years and over in an urban area in Southeast Asia. Future studies should now seek to determine potential genetic, cultural and lifestyle differences which may predispose to syncope.
METHODS: A total of 69 patients with topographic corneal astigmatism of 1.0 Diopter (D) and above who underwent cataract surgery between June 2015 and December 2016 were included in this retrospective observational study. All preoperative toric IOL calculations were performed using immersion biometry. Appropriate formula to calculate toric IOL power was applied (SRK/T, Holladay 1 or Hoffer Q formula). All patients undergone similar uncomplicated phacoemulsification with implantation of AcrySoft IQ SN6AT toric IOL of different powers. Visual outcome, refractive status and axis of lens were evaluated at six weeks postoperatively. Ethical approval from the Ministry of Health Medical Research Ethics Committee was obtained prior to commencement of study.
RESULTS: The mean refractive astigmatism decreased from 1.69 D ±1.10 (SD) to 0.81 D ± 0.40 (SD) at six weeks postoperatively. The mean postoperative spherical equivalent was at -0.37 D ±0.64 (SD). Mean LogMAR for uncorrected and corrected distance visual acuity in six weeks postoperative patients was at 0.29 ±0.16 (SD) and 0.12 ±0.12 (SD) respectively. Intraoperative to 6 weeks of postoperative comparison of IOL axis alignment showed low levels of rotation (mean 3.21 ±2.52 degrees).
CONCLUSION: Cataract surgery with implantation of toric IOL was stable and effective in improving pre-existing regular corneal astigmatism.
METHODS: Data was obtained from the Malaysian Elders Longitudinal Research (MELoR) study, which employed random stratified sampling from three parliamentary constituencies within the Klang Valley. Beat-to-beat blood pressure (BP) was recorded using non-invasive BP monitoring (TaskforceTM, CNSystems). Low frequency (LF), high frequency (HF) and low-to-high frequency (LF:HF) ratio for BPV were derived using fast Fourier transformation. Cognition was evaluated using the Montreal Cognitive Assessment (MoCA) test, and categorized into normal aging, mild impairment and moderate-to-severe impairment.
RESULTS: Data from 1,140 individuals, mean age (SD) 68.48 (7.23) years, were included. Individuals with moderate-to-severe impairment had higher HF-BPV for systolic (SBP) and diastolic (DBP) blood pressure compared to individuals within the normal aging group [OR (95% CI) = 2.29 (1.62-3.24)] and [OR (95% CI) = 1.80 (1.32-2.45)], while HF-SBPV [OR (95% CI) = 1.41 (1.03-1.93)] but not HF-DBPV was significantly higher with mild impairment compared to normal aging after adjustments for potential confounders. Moderate-to-severe impairment was associated with significantly lower LF:HF-SBPV [OR (95% CI) = 0.29 (0.18-0.47)] and LF:HF-DBPV [OR (95% CI) = 0.49 (0.34-0.72)], while mild impairment was associated with significantly lower LF:HF-SBPV [OR (95% CI) = 0.52 (0.34-0.80)] but not LF:HF-DBPV [OR (95% CI) = 0.81 (0.57-1.17)], compared to normal aging with similar adjustments.
CONCLUSION: Higher HF-BPV, which indicates parasympathetic activation, and lower LF:HF-BPV, which addresses sympathovagal balance, were observed among individuals with moderate-to-severe cognitive impairment. Future studies should determine whether BPV could be a physiological marker or modifiable risk factor for cognitive decline.
METHODS: Diffusion-weighted imaging, perfusion-weighted imaging, and chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) data were acquired from five rats that underwent scans at 9.4 T after middle cerebral artery occlusion.
RESULTS: The apparent diffusion coefficient (ADC), cerebral blood flow (CBF), and apparent exchange-dependent relaxations (AREX) at 3.5 ppm and NOE(-1.6 ppm) were quantified. AREX(3.5 ppm) and NOE(-1.6 ppm) were found to be hypointense and exhibited different signal patterns within the ischemic tissue. The NOE(-1.6 ppm) deficit areas were equal to or larger than the ADC deficit areas, but smaller than the AREX(3.5 ppm) deficit areas. This suggested that NOE(-1.6 ppm) might further delineate the acidotic tissue estimated using AREX(3.5 ppm). Since NOE(-1.6 ppm) is closely related to membrane phospholipids, NOE(-1.6 ppm) potentially highlighted at-risk tissue affected by lipid peroxidation and membrane damage. Altogether, the ADC/NOE(-1.6 ppm)/AREX(3.5 ppm)/CBF mismatches revealed four zones of increasing sizes within the ischemic tissue, potentially reflecting different pathophysiological information.
CONCLUSIONS: Using CEST coupled with ADC and CBF, the ischemic tissue may thus potentially be separated into four zones to better understand the pathophysiology after stroke and improve ischemic tissue fate definition. Further verification of the potential utility of NOE(-1.6 ppm) may therefore lead to a more precise diagnosis.
METHODS: A cross-sectional observational study of hospitalized COVID-19 patients was conducted. The neurological manifestations were divided into the self-reported central nervous system (CNS) symptoms, stroke associated symptoms, symptoms of encephalitis or encephalopathy and specific neurological complications. Multiple logistic regression was performed using demographic and clinical variables to determine the factors associated with outcome.
RESULTS: Of 156 hospitalized COVID-19 patients with mean age of 55.88 ± 6.11 (SD) years, 23.7% developed neurological complications, which included stroke, encephalitis and encephalopathy. Patients with neurological complications were more likely to have diabetes mellitus (p = 0.033), symptoms of stroke [limb weakness (p
METHODS: In this work, we developed deep convolutional neural network (CNN) based heterogeneous ensemble models for automated analysis of renal histopathological images without detailed annotations. The proposed method would first segment the histopathological tissue into patches with different magnification factors, then classify the generated patches into normal and tumor tissues using the pre-trained CNNs and lastly perform the deep ensemble learning to determine the final classification. The heterogeneous ensemble models consisted of CNN models from five deep learning architectures, namely VGG, ResNet, DenseNet, MobileNet, and EfficientNet. These CNN models were fine-tuned and used as base learners, they exhibited different performances and had great diversity in histopathological image analysis. The CNN models with superior classification accuracy (Acc) were then selected to undergo ensemble learning for the final classification. The performance of the investigated ensemble approaches was evaluated against the state-of-the-art literature.
RESULTS: The performance evaluation demonstrated the superiority of the proposed best performing ensembled model: five-CNN based weighted averaging model, with an Acc (99%), specificity (Sp) (98%), F1-score (F1) (99%) and area under the receiver operating characteristic (ROC) curve (98%) but slightly inferior recall (Re) (99%) compared to the literature.
CONCLUSIONS: The outstanding robustness of the developed ensemble model with a superiorly high-performance scores in the evaluated metrics suggested its reliability as a diagnosis system for assisting the pathologists in analyzing the renal histopathological tissues. It is expected that the proposed ensemble deep CNN models can greatly improve the early detection of renal cancer by making the diagnosis process more efficient, and less misdetection and misdiagnosis; subsequently, leading to higher patients' survival rate.
METHODS: Four electronic databases were searched from inception to June 2022. Studies that investigated non-invasive parameters of arterial stiffness and autonomic function using beat-to-beat cardiovascular signals over a period of > 5min were included. Study quality was assessed using the STROBE criteria. Two authors screened the titles, abstracts, and full texts independently.
RESULTS: Nineteen studies met the inclusion criteria. A comprehensive overview of experimental design for assessing autonomic function in terms of baroreflex sensitivity and beat-to-beat cardiovascular variabilities, as well as arterial stiffness, was presented. Alterations in non-invasive indicators of autonomic function, which included baroreflex sensitivity, beat-to-beat cardiovascular variabilities and hemodynamic changes in response to autonomic challenges, as well as arterial stiffness, were identified in individuals with hypertension. A mixed result was found in terms of the association between non-invasive quantitative autonomic indices and arterial stiffness in hypertensive individuals. Nine out of 12 studies which quantified baroreflex sensitivity revealed a significant association with arterial stiffness parameters. Three studies estimated beat-to-beat heart rate variability and only one study reported a significant relationship with arterial stiffness indices. Three out of five studies which studied beat-to-beat blood pressure variability showed a significant association with arterial structural changes. One study revealed that hemodynamic changes in response to autonomic challenges were significantly correlated with arterial stiffness parameters.
CONCLUSIONS: The current review demonstrated alteration in autonomic function, which encompasses both the sympathetic and parasympathetic modulation of sinus node function and vasomotor tone (derived from beat-to-beat cardiovascular signals) in hypertension, and a significant association between some of these parameters with arterial stiffness. By employing non-invasive measurements to monitor changes in autonomic function and arterial remodeling in individuals with hypertension, we would be able to enhance our ability to identify individuals at high risk of cardiovascular disease. Understanding the intricate relationships among these cardiovascular variability measures and arterial stiffness could contribute toward better individualized treatment for hypertension in the future.
SYSTEMATIC REVIEW REGISTRATION: PROSPERO ID: CRD42022336703. Date of registration: 12/06/2022.
METHODS: Individuals aged ≥ 55 years were recruited through the Malaysian Elders Longitudinal Research (MELoR) study and continuous non-invasive BP was monitored over 5 min of supine rest and 3 min of standing. Physical performance was measured using the timed-up-and-go test, functional reach, handgrip and Lawton's functional ability scale. Cognition was measured with the Montreal Cognitive Assessment. Participants were categorized according to BP responses into four categories according to changes in SBP/DBP reductions from supine to standing:
METHODS: Continuous raw PPG waveforms were blindly allocated into segments with an equal length (5s) without leveraging any pulse location information and were normalized with Z-score normalization methods. A 1-D-CNN was designed to automatically learn the intrinsic features of the PPG waveform, and perform the required classification. Several training hyperparameters (initial learning rate and gradient threshold) were varied to investigate the effect of these parameters on the performance of the network. Subsequently, this proposed network was trained and validated with 30 subjects, and then tested with eight subjects, with our local dataset. Moreover, two independent datasets downloaded from the PhysioNet MIMIC II database were used to evaluate the robustness of the proposed network.
RESULTS: A 13 layer 1-D-CNN model was designed. Within our local study dataset evaluation, the proposed network achieved a testing accuracy of 94.9%. The classification accuracy of two independent datasets also achieved satisfactory accuracy of 93.8% and 86.7% respectively. Our model achieved a comparable performance with most reported works, with the potential to show good generalization as the proposed network was evaluated with multiple cohorts (overall accuracy of 94.5%).
CONCLUSION: This paper demonstrated the feasibility and effectiveness of applying blind signal processing and deep learning techniques to PPG motion artifact detection, whereby manual feature thresholding was avoided and yet a high generalization ability was achieved.