Supplemental Material - Aged Patients With Severe Small Vessel Disease Exhibit Poor Bimanual Coordination During the Anti-Phase Horizontal Line Drawing Task

Supplemental Material for Aged Patients With Severe Small Vessel Disease Exhibit Poor Bimanual Coordination During the Anti-Phase Horizontal Line Drawing Task by Hóngyi Zhào, Hans-Leo Teulings, Cuiqiao Xia, and Yonghua Huang in Perceptual and Motor Skills</p

Data_Sheet_2_Detecting apathy in patients with cerebral small vessel disease.docx

BackgroundApathy is attracting more and more attention in clinical practice. As one of the most common features of cerebral small vessel disease (CSVD), the assessment of apathy still mainly relies on observers. With the development of Information and Communication Technologies (ICTs), new objective tools take part in the early detection of apathy.ObjectivesTo detect apathy in patients with CSVD and find out the relationship between apathy and actigraphic data sampled from the diurnal and nocturnal periods.MethodsA total of 56 patients with CSVD were recruited for a cross-sectional observational study. Apathy was diagnosed by the diagnostic criteria for apathy in neurocognitive disorders. The presence of lacunes, white matter hyperintensities, cerebral microbleeds (CMBs), and perivascular spaces (PVS) in magnetic resonance imaging (MRI) images were rated independently. Actigraph devices were worn in the non-dominant hands of each subject for 7 consecutive days to collect samples of raw data, and diurnal vector magnitude (VM) and a series of sleep quality variables were obtained.ResultsWe found that the frequency of apathy in Chinese patients with CSVD reached 37.50%. Patients in the Apathy+ group showed more lacunes and CMBs, and higher Fazekas scores in comparison to apathy-group individuals. Diurnal VM, instead of other sleep quality variables, was lower in CSVD patients with apathy relative to those without apathy. Lastly, we discovered that diurnal VM and total time in bed (TTB) correlated negatively with apathy severity in patients with CSVD.ConclusionActigraphy is a promising choice to evaluate apathy in patients with CSVD.</p

Data_Sheet_1_Detecting apathy in patients with cerebral small vessel disease.docx

BackgroundApathy is attracting more and more attention in clinical practice. As one of the most common features of cerebral small vessel disease (CSVD), the assessment of apathy still mainly relies on observers. With the development of Information and Communication Technologies (ICTs), new objective tools take part in the early detection of apathy.ObjectivesTo detect apathy in patients with CSVD and find out the relationship between apathy and actigraphic data sampled from the diurnal and nocturnal periods.MethodsA total of 56 patients with CSVD were recruited for a cross-sectional observational study. Apathy was diagnosed by the diagnostic criteria for apathy in neurocognitive disorders. The presence of lacunes, white matter hyperintensities, cerebral microbleeds (CMBs), and perivascular spaces (PVS) in magnetic resonance imaging (MRI) images were rated independently. Actigraph devices were worn in the non-dominant hands of each subject for 7 consecutive days to collect samples of raw data, and diurnal vector magnitude (VM) and a series of sleep quality variables were obtained.ResultsWe found that the frequency of apathy in Chinese patients with CSVD reached 37.50%. Patients in the Apathy+ group showed more lacunes and CMBs, and higher Fazekas scores in comparison to apathy-group individuals. Diurnal VM, instead of other sleep quality variables, was lower in CSVD patients with apathy relative to those without apathy. Lastly, we discovered that diurnal VM and total time in bed (TTB) correlated negatively with apathy severity in patients with CSVD.ConclusionActigraphy is a promising choice to evaluate apathy in patients with CSVD.</p

Data_Sheet_1_Spatial Navigation Is Impaired in Elderly Patients With Cerebral Small Vessel Disease.docx

Cerebral small vessel disease (SVD) refers to a heterogeneous group of pathological processes that result from damage to the small penetrating vessels in the brain. Spatial navigation, one of the most fundamental behaviors, has lately attracted considerable clinical interest. This study aimed to determine whether spatial navigation performance is impaired in elderly SVD patients. In total, 18 elderly patients with severe SVD, 40 elderly patients with non-severe SVD, and 41 age-matched healthy volunteers were classified according to the Fazekas scale. Spatial navigation was evaluated by Amunet (a computer-based analogy of Morris water maze software), and a mini-mental scale evaluation (MMSE), animal category verbal fluency test (VFT), clock drawing test (CDT), and trail making test (TMT) -B were also applied. Compared to healthy controls, severe SVD, rather than non-severe SVD patients, exhibited significantly worse performance on “allocentric + egocentric” (41.74 ± 29.10 vs. 31.50 ± 16.47 vs. 29.21 ± 19.03; p = 0.031). Furthermore, the different abilities of spatial navigation among groups reached a statistical level on allocentric subtests (46.93 ± 31.27 vs. 43.69 ± 23.95 vs. 28.56 ± 16.38; p = 0.003), but not on egocentric subtest (56.16 ± 39.85 vs. 56.00 ± 28.81 vs. 43.06 ± 25.07; p = 0.105). The linear regression analysis revealed that allocentric navigation deficit was significantly correlated with TMT-B (p = 0.000, standardized β = 0.342) and VFT (p = 0.016, standardized β = −0.873) performance in elderly SVD patients. These results elucidated that spatial navigation ability could be a manifestation of cognitive deficits in elderly patients with SVD.</p

The relationship between apathy and nonparametric variables of rest activity rhythm in older adults with cerebral small vessel disease

The goal of the current study was to demonstrate if the rest-activity rhythm (RAR) was altered in apathetic older adults with cerebral small vessel disease (CSVD) and find out the relationship between apathy/depression severity and RAR features in CSVD patients. This is a cross-sectional observational investigation including 53 CSVD cases (54.74% men), aged 70.70 ± 6.18 years old. The participants were assessed by neuropsychiatric inventory (NPI) subscale of apathy (NPI-apathy) and depression (NPI-depression) in succession, according to updated diagnostic criteria for apathy (DCA). Each subject wore an actigraph device (ActiGraph GT3X) in their nondominant hand for 7 days to collect raw data. Using a non-parametric methodological analysis, this study determined RAR variables such as interdaily stability (IS), intraday variability (IV) and relative amplitude (RA). Patients in the apathy-positive group had a higher Fazekas score than those in the apathy-negative group. IS, but not IV, RA, or objective sleep variables, differed between elderly patients with varying degrees of CSVD burden. Furthermore, apathy severity was statistically correlated with RA after adjusting for age, gender and education level, whereas depression severity was not associated with RAR variables. Finally, we discovered that the severity of apathy had no significant relationship with the severity of depression. All these findings indicated that the RAR altered in apathetic older adults with CSVD, and apathy was associated with decreased RAR amplitude.</p

Additional file 1 of EEG complexity correlates with residual consciousness level of disorders of consciousness

Additional file 1

Table_1_How to Best Convey Information About Intensive/Comfort Care to the Family Members of Premature Infants to Enable Unbiased Perinatal Decisions.DOCX

Background: As the infant's best interests are determined through the perinatal decisions of family members and physicians, it is important to understand the factors that affect such decisions. This paper investigated the separate and combined effects of various factors related to perinatal decision making and sought to determine the best way to convey information in an unbiased manner to family members.Methods: In total, 613 participants were consecutively recruited. Each participant completed a series of surveys. All responses to four items were examined via a latent class analysis (LCA) to identify subgroups of participants with similar preferences for intensive care (IC) and comfort care (CC) regarding their potentially premature infant. Multiple logistic regression analyses were applied to identify the sociodemographic predictors for the classification of participants into different subgroups.Results: χ2-tests indicated that perinatal decision making for Item 2 was influenced by framing information, whereas decision making wasn't affected by presentation modes. Furthermore, the endorsement rates of IC significantly decreased with the information increased from brief to detailed, regardless of framing or presentation mode. The LCA indicated that a 3-subgroup model, which included the IC, CC, and variation subgroups, was optimal. Logistic regression analyses demonstrated that, compared with the IC subgroup, negative framing, higher education, parenthood, and poor numeracy predicted participants' preferences for CC. Meanwhile, worrying about physical or mental disabilities predicted preferences for CC and sensitivity to the amount of information provided regarding treatment options (variation subgroup).Conclusions: Perinatal decision making is affected by many factors, suggesting that more detailed information, improved understandability of numerical data, and a neutral tone of voice regarding therapeutic outcomes would be helpful for the families of premature infants to make unbiased decisions. Our findings should be replicated in future research.</p

Data_Sheet_1_How to Best Convey Information About Intensive/Comfort Care to the Family Members of Premature Infants to Enable Unbiased Perinatal Decisions.DOCX

Background: As the infant's best interests are determined through the perinatal decisions of family members and physicians, it is important to understand the factors that affect such decisions. This paper investigated the separate and combined effects of various factors related to perinatal decision making and sought to determine the best way to convey information in an unbiased manner to family members.Methods: In total, 613 participants were consecutively recruited. Each participant completed a series of surveys. All responses to four items were examined via a latent class analysis (LCA) to identify subgroups of participants with similar preferences for intensive care (IC) and comfort care (CC) regarding their potentially premature infant. Multiple logistic regression analyses were applied to identify the sociodemographic predictors for the classification of participants into different subgroups.Results: χ2-tests indicated that perinatal decision making for Item 2 was influenced by framing information, whereas decision making wasn't affected by presentation modes. Furthermore, the endorsement rates of IC significantly decreased with the information increased from brief to detailed, regardless of framing or presentation mode. The LCA indicated that a 3-subgroup model, which included the IC, CC, and variation subgroups, was optimal. Logistic regression analyses demonstrated that, compared with the IC subgroup, negative framing, higher education, parenthood, and poor numeracy predicted participants' preferences for CC. Meanwhile, worrying about physical or mental disabilities predicted preferences for CC and sensitivity to the amount of information provided regarding treatment options (variation subgroup).Conclusions: Perinatal decision making is affected by many factors, suggesting that more detailed information, improved understandability of numerical data, and a neutral tone of voice regarding therapeutic outcomes would be helpful for the families of premature infants to make unbiased decisions. Our findings should be replicated in future research.</p

DataSheet1_Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing.docx

Background: The existence of maternal malignancy may cause false-positive results or failed tests of NIPT. Though recent studies have shown multiple chromosomal aneuploidies (MCA) are associated with malignancy, there is still no effective solution to identify maternal cancer patients from pregnant women with MCA results using NIPT. We aimed to develop a new method to effectively detect maternal cancer in pregnant women with MCA results using NIPT and a random forest classifier to identify the tissue origin of common maternal cancer types.Methods: For examination, 496 participants with MCA results via NIPT were enrolled from January 2016 to June 2019 at BGI. Cancer and non-cancer participants were confirmed through the clinical follow-up. The cohort comprising 42 maternal cancer cases and 294 non-cancer cases enrolled from January 2016 to December 2017 was utilized to develop a method named mean of the top five chromosome z scores (MTOP5Zscores). The remaining 160 participants enrolled from January 2018 to June 2019 were used to validate the performance of MTOP5Zscores. We established a random forest model to classify three common cancer types using normalized Pearson correlation coefficient (NPCC) values, z scores of 22 chromosomes, and seven plasma tumor markers (PTMs) as predictor variables.Results: 62 maternal cancer cases were confirmed with breast cancer, liver cancer, and lymphoma, the most common cancer types. MTOP5Zscores showed a sensitivity of 85% (95% confidence interval (CI), 62.11–96.79%) and specificity of 80% (95% CI, 72.41–88.28%) in the detection of maternal cancer among pregnant women with MCA results. The sensitivity of the classifier was 93.33, 66.67, and 50%, while specificity was 66.67, 90, and 97.06%, and positive predictive value (PPV) was 60.87, 72.73, and 80% for the prediction of breast cancer, liver cancer, and lymphoma, respectively.Conclusion: This study presents a solution to identify maternal cancer patients from pregnant women with MCA results using NIPT, indicating it as a value-added application of NIPT in the detection of maternal malignancies in addition to screening for fetal aneuploidies with no extra cost.</p