Falls are the leading cause of injury in stroke patients. However, the cause of a fall is complicated, and several types of risk factors are involved. Therefore, a comprehensive model to predict ...falls with high sensitivity and specificity is needed.
This study was a prospective study of 112 inpatients in a rehabilitation ward with follow-up interviews in patients' homes. Evaluations were performed 1 month after stroke and included the following factors: (1) status of cognition, depression, fear of fall and limb spasticity; (2) functional assessments walking velocity and the Functional Independence Measure (FIM); and (3) objective, computerized gait and balance analyses. The outcome variable was the number of accidental falls during the 6-month follow-up period after baseline measurements.
The non-faller group exhibited significantly better walking velocity and FIM scale compared to the faller group (P < .001). The faller group exhibited higher levels of spasticity in the affected limbs, asymmetry of gait parameters in single support (P < .001), double support (P = .027), and step time (P = .003), and lower stability of center of gravity in the medial-lateral direction (P = .008). Psychological assessments revealed that the faller group exhibited more severe depression and lower confidence without falling. A multivariate logistic regression model identified three independent predictors of falls with high sensitivity (82.6%) and specificity (86.5%): the asymmetry ratio of single support adjusted odds ratio, aOR = 2.2, 95% CI (1.2-3.8), the level of spasticity in the gastrocnemius aOR = 3.2 (1.4-7.3), and the degree of depression aOR = 1.4 (1.2-1.8).
This study revealed depression, in additional to gait asymmetry and spasticity, as another independent factor for predicting falls. These results suggest that appropriate gait training, reduction of ankle spasticity, and aggressive management of depression may be critical to prevent falls in stroke patients.
Electromyograms (EMG signals) may be contaminated by electrocardiographic (ECG) signals that cannot be easily separated with traditional filters, because both signals have some overlapping spectral ...components. Therefore, the first challenge encountered in signal processing is to extract the ECG noise from the EMG signal. In this study, the EMG, mixed with different degrees of noise (ECG), is simulated to investigate the variations of the EMG features. Simulated data were derived from the MIT-BIH Noise Stress Test (NSTD) Database. Two EMG and four ECG data were composed with four EMG/ECG SNR to 32 simulated signals. Following Pan-Tompkins R-peak detection, four ECG removal methods were used to remove ECG with different compensation algorithms to obtain the denoised EMG signal. A total of 13 time-domain and four frequency-domain EMG features were calculated from the denoised EMG. In addition, the similarity of denoised EMG features compared to clean EMG was also evaluated. Our results showed that with the ratio EMG/ECG SNR = 10 and 20, the ECG can be almost ignored, and the similarity of EMG features is close to 1. When EMG/ECG SNR = 1 and 2, there is a large variation of EMG features. The results of our simulation study would be beneficial for understanding the variations of EMG features upon the different EMG/ECG SNR.
In the context of behavior recognition, the emerging bed-exit monitoring system demands a rapid deployment in the ward to support mobility and personalization. Mobility means the system can be ...installed and removed as required without construction; personalization indicates human body tracking is limited to the bed region so that only the target is monitored. To satisfy the above-mentioned requirements, the behavior recognition system aims to: (1) operate in a small-size device, typically an embedded system; (2) process a series of images with narrow fields of view (NFV) to detect bed-related behaviors. In general, wide-range images are preferred to obtain a good recognition performance for diverse behaviors, while NFV images are used with abrupt activities and therefore fit single-purpose applications. This paper develops an NFV-based behavior recognition system with low complexity to realize a bed-exit monitoring application on embedded systems. To achieve effectiveness and low complexity, a queueing-based behavior classification is proposed to keep memories of object tracking information and a specific behavior can be identified from continuous object movement. The experimental results show that the developed system can recognize three bed behaviors, namely off bed, on bed and return, for NFV images with accuracy rates of 95~100%.
KDM4/JMJD2 Jumonji C-containing histone lysine demethylases (KDM4A-D) constitute an important class of epigenetic modulators in the transcriptional activation of cellular processes and genome ...stability. Interleukin-8 (IL-8) is overexpressed in gastric cancer, but the mechanisms and particularly the role of the epigenetic regulation of IL-8, are unclear. Here, we report that KDM4B, but not KDM4A/4C, upregulated IL-8 production in the absence or presence of Helicobacter pylori. Moreover, KDM4B physically interacts with c-Jun on IL-8, MMP1, and ITGAV promoters via its demethylation activity. The depletion of KDM4B leads to the decreased expression of integrin αV, which is exploited by H. pylori carrying the type IV secretion system, reducing IL-8 production and cell migration. Elevated KDM4B expression is significantly associated with the abundance of p-c-Jun in gastric cancer and is linked to a poor clinical outcome. Together, our results suggest that KDM4B is a key regulator of JNK/c-Jun-induced processes and is a valuable therapeutic target.
Intrahepatic cholangiocarcinoma (ICC) is a relatively rare subtype of cholangiocarcinoma. The study herein gathered experience of surgical treatment for ICC, and aimed to analyze the prognosis of ...patients who had received curative-intent liver resection.
A total of 216 patients who had undergone curative-intent liver resection for ICC between January 1977 and December 2014 was retrospectively reviewed.
Overall, the rates of 5-years recurrence-free survival (RFS) and overall survival (OS) were 26.1 and 33.9% respectively. Based on multivariate analysis, four independent adverse prognostic factors including morphology patterns, maximum tumor size > 5 cm, pathological lymph node involvement, and vascular invasion were identified as affecting RFS after curative-intent liver resection for ICC. Among patients with cholangiocarcinoma recurrence, only 27 (16.9%) were able to receive surgical resection for recurrent cholangiocarcinoma that had a significantly better outcome than the remaining patients.
Despite curative resection, the general outcome of patients with ICC is still unsatisfactory because of a high incidence of cholangiocarcinoma recurrence after operation. Tumor factors associated with cholangiocarcinoma remain crucial for the prognosis of patients with ICC after curative liver resection. Moreover, aggressive attitude toward repeat resection for the postoperative recurrent cholangiocarcinoma could provide a favorable outcome for patients.
This study aimed to investigate the feasibility of sonoelastography for determining echotexture in post-stroke patients. Moreover, the relationships of muscle echotexture features, muscle stiffness, ...and functional performance in spastic muscle were explored. The study population comprised 22 males with stroke. The echotexture features (entropy and energy) of the biceps brachii muscles (BBM) in both arms were extracted by local binary pattern (LBP) from ultrasound images, whereas the stiffness of BBM was assessed by shear wave velocity (SWV) in the transverse and longitudinal planes. The Fugl–Meyer assessment (FMA) was used to assess the functional performance of the upper arm. The results showed that echotexture was more inhomogeneous in the paretic BBM than in the non-paretic BBM. SWV was significantly faster in paretic BBM than in non-paretic BBM. Both echotexture features were significantly correlated with SWV in the longitudinal plane. The feature of energy was significantly negatively correlated with FMA in the longitudinal plane and was significantly positively correlated with the duration from stroke onset in the transverse plane. The echotexture extracted by LBP may be a promising approach for quantitative assessment of the spastic BBM in post-stroke patients.
Hepatocellular carcinoma (HCC) can be potentially discovered from abdominal computed tomography (CT) studies under varied clinical scenarios (e.g., fully dynamic contrast‐enhanced DCE studies, ...noncontrast NC plus venous phase VP abdominal studies, or NC‐only studies). Each scenario presents its own clinical challenges that could benefit from computer‐aided detection (CADe) tools. We investigate whether a single CADe model can be made flexible enough to handle different contrast protocols and whether this flexibility imparts performance gains. We developed a flexible three‐dimensional deep algorithm, called heterophase volumetric detection (HPVD), that can accept any combination of contrast‐phase inputs with adjustable sensitivity depending on the clinical purpose. We trained HPVD on 771 DCE CT scans to detect HCCs and evaluated it on 164 positives and 206 controls. We compared performance against six clinical readers, including two radiologists, two hepatopancreaticobiliary surgeons, and two hepatologists. The area under the curve of the localization receiver operating characteristic for NC‐only, NC plus VP, and full DCE CT yielded 0.71 (95% confidence interval CI, 0.64–0.77), 0.81 (95% CI, 0.75–0.87), and 0.89 (95% CI, 0.84–0.93), respectively. At a high‐sensitivity operating point of 80% on DCE CT, HPVD achieved 97% specificity, which is comparable to measured physician performance. We also demonstrated performance improvements over more typical and less flexible nonheterophase detectors. Conclusion: A single deep‐learning algorithm can be effectively applied to diverse HCC detection clinical scenarios, indicating that HPVD could serve as a useful clinical aid for at‐risk and opportunistic HCC surveillance.
This study presented a flexible three dimensional deep algorithm that can accepted any combination of contrast‐phase inputs with adjustable sensitivity to diverse hepatocellular carcinoma detection.
Correct placement of nasogastric tubes provide proper functionality and maximize benefit and minimize risk. The Nose-Ear-Xiphoid (NEX) body surface estimate method is a long-lasting technique, and ...this study was conducted to evaluate the correlation between NEX method and the secure insertion depth of nasogastric tube.
Thirty patients with nasogastric tube insertion who received whole body positron emission tomography with computerized tomography scan (PET-CT) were recruited. All data were gathered in the image center, which included Nose-Ear (NE), Ear-Xiphoid (EX), Nose-Ear-Xiphoid (NEX), glabella-xiphoid (GX) and glabella-umbilicus (GU) lengths. The distances of the inserted portion of the nasogastric tube between the cardiac and the nostril were measured by multiplanar reconstruction algorithm.
Only one patient successfully placed all side-holes into the stomach while using NEX method to estimate inserting depth. Twenty-nine patients (96.7%) failed to place correctly. Fourteen participants had one or more side-holes in both the esophagus and the stomach sides. Fifteen patients could not pass through any side-hole across the gastroesophageal junction. They had shorter EX distances (p = 0.02), but no difference among the NE distances. Body height had the highest statistical correlation with nasogastric tube length (adjusted R(2) = 0.459), as compared with the NEX, GX and GU body surface methods.
This study suggests that NEX method is inappropriate for adult patients to estimate the ideal inserting length of nasogastric tube. Physicians should realize these underinsertions with any side-hole above the gastroesophageal junctions may increase the potential risk of complications.
Numerous strategies for perioperative nutrition therapy for patients undergoing pancreaticoduodenectomy (PD) have been proposed. This systematic review aimed to summarize the current relevant ...published randomized controlled trials (RCTs) evaluating different nutritional interventions via a traditional network meta-analysis (NMA) and component network meta-analysis (cNMA). EMBASE, MEDLINE, the Cochrane Library, and ClinicalTrials.gov were searched to identify the RCTs. The evaluated nutritional interventions comprised standard postoperative enteral nutrition by feeding tube (Postop-SEN), preoperative enteral feeding (Preop-EN), postoperative immunonutrients (Postop-IM), preoperative oral immunonutrient supplement (Preop-IM), and postoperative total parenteral nutrition (TPN). The primary outcomes were general, infectious, and noninfectious complications; postoperative pancreatic fistula (POPF); and delayed gastric emptying (DGE). The secondary outcomes were mortality and length of hospital stay (LOS). The NMA and cNMA were conducted with a frequentist approach. The results are presented as odds ratios (ORs) and 95% confidence intervals (CIs). Two primary outcomes, infectious complications and POPF, were positively influenced by nutritional interventions. Preop-EN plus Postop-SEN (OR 0.11; 95% CI 0.02~0.72), Preop-IM (OR 0.22; 95% CI 0.08~0.62), and Preop-IM plus Postop-IM (OR 0.11; 95% CI 0.03~0.37) were all demonstrated to be associated with a decrease in infectious complications. Postop-TPN (OR 0.37; 95% CI 0.19~0.71) and Preop-IM plus Postop-IM (OR 0.21; 95% CI 0.06~0.77) were clinically beneficial for the prevention of POPF. While enteral feeding and TPN may decrease infectious complications and POPF, respectively, Preop-IM plus Postop-IM may provide the best clinical benefit for patients undergoing PD, as this approach decreases the incidence of both the aforementioned adverse effects.
Background
In the 8th edition of American Joint Committee on Cancer (AJCC) staging system for hepatocellular carcinoma (HCC), tumor size is not considered in T1 stage. The present study aimed to find ...out the optimal cutoff for tumor size to further stratify patients with T1 HCC.
Methods
Operated HCC patients were identified from the Chang Gung Research Database (CGRD), and the patients with T1bN0M0 tumors were further divided into two groups based on the tumor size. The resulting subgroups were denoted as T1b (≤ cutoff) and T1c (> cutoff). The survivals were compared between T1a/b and T1c as well as T1c and T2.
Results
From 2002 to 2018, a total of 2893 patients who underwent surgery for T1N0M0 HCC were identified from the CGRD. After excluding cases who died within 30 days of surgery, Kaplan–Meier survival analysis discovered that T1 tumors > 65 mm (T1c) had survivals similar to those of T2N0M0 tumors. Cox regression multivariate analysis further demonstrated that tumor size > 6.5 cm was an independent poor prognostic indicator for T1 HCC. Sensitivity tests also confirmed that tumors lager than 6.5 cm were significantly more likely to develop both tumor recurrence and liver-specific death after surgery.
Conclusions
Our study demonstrated that tumor size would significantly impact the survival outcome of T1 HCC after surgery. Due to significantly worse survival, we proposed a subclassification within T1 HCC, T1c: solitary tumor > 6.5 cm without vascular invasion, to further stratify those patients at risk. Further studies are mandatory to validate our findings.
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