Dbl (B-cell lymphoma)-related guanine nucleotide exchange factors (GEFs), the largest family of GEFs, are directly responsible for the activation of Rho family GTPases and essential for a number of cellular events such as proliferation, differentiation and movement. The members of the Ephexin (Eph-interacting exchange protein) family, a subgroup of Dbl GEFs, initially were named for their interaction with Eph receptors and sequence homology with Ephexin1. Although the first Ephexin was identified about two decades ago, their functions in physiological and pathological contexts and regulatory mechanisms remained elusive until recently. Ephexins are now considered as GEFs that can activate Rho GTPases such as RhoA, Rac, Cdc42, and RhoG. Moreover, Ephexins have been shown to have pivotal roles in neural development, tumorigenesis, and efferocytosis. In this review, we discuss the known and proposed functions of Ephexins in physiological and pathological contexts, as well as their regulatory mechanisms. The Rho family of GTPases is a subgroup of the Ras superfamily. Like other small GTPases, the members of the Rho family function as molecular switches ,2,3,4. RThe overall activity of a Rho GTPase in cells depends on its ratio of the GTP-bound to GDP-bound form. Importantly, this ratio is controlled by its direct binding to GEFs, GAPs, or GDIs. GEFs activate Rho GTPases by catalyzing the exchange of bound GDP for GTP, which results in activated Rho GTPases to interact with their downstream effectors. On the other hand, GAPs antagonize the function of GEFs by stimulating Rho GTPases to hydrolyze bound GTP to GDP. Additionally, inactive GDP-bound Rho GTPases are sequestered in the cytosol by RhoGDIs  1,2,8,9,98,9,10.Dbl, the first GEF of the Dbl family, was originally identified as an oncogene but its function as a GEF for Cdc42 was revealed later ,12. SincAmong the members of the Dbl family, five proteins from Ephexin1 to 5 belong to the Ephexin subfamily ,17. TheiIn particular, the Ephexin family plays essential roles in normal function of neurons and their development. It regulates the axon guidance of developing neurons ,28,29,30Since the first Ephexin, Ephexin1, was identified as an EphA4-interacting RhoGEF, Ephexin was named for Eph-interacting exchange protein . Since tEphexins function as GEFs for Rac, Cdc42, Rho and RhoG, and interact with Eph receptors to transduce signals from the receptors although an Eph receptor interacting with Ephexin2 has not been identified. Accordingly, they are engaged in a variety of Eph receptor-mediated cellular processes  18,19,2,21,22. IEphexin1 was originally isolated from an adult mouse brain cDNA library in 2000 as Ngef. Ephexin1 is predominately expressed in the central nervous system, the brain and spinal cord, and its expression is developmentally regulated, that is, its mRNA levels gradually increase throughout embryonic development and peak at the P10 postnatal stage. In particular, Ephexin1 is highly expressed in the caudate nucleus associated with motor processes ,54. ThisDuring development, the axon pathfinding is regulated by various molecules existing in the extracellular matrix or on the surrounding cell surfaces. These guidance cues determine the attraction and/or repulsion of the growth cone by regulating the actin cytoskeleton. Eph receptors and Ephrins are involved and their roles are well established in these processes . In partIn addition, the importance of Ephexin1 in the nervous systems is also highlighted in various contexts. Optimal neuron innervation by axon guidance during embryonic development is one of the most well-characterized processes regulated by Ephexin1. Tissues from various model organisms like mice, chickens, and fruit flies have been used to confirm the roles of Ephexin1 in those developmental stages. Afferent innervation from spiral ganglion neurons (SGNs) is important for development of the proper auditory system during mouse embryogenesis and also regulated by the ephrin-EphA4-Ephexin1 axis . Medial The GEF activity of Ephexin1 is modulated by the activation state of EphA4: using cultured Ephexin1-/- neurons and RNA interference in the chick, it was found that Ephexin1 could function as a GEF for Rac1, Cdc42, and RhoA under the basal condition. However, when EphA4 is activated by Ephrins, the phosphorylation of Ephexin1 by Src provides the specificity of Ephexin1 towards RhoA ,24. AheaIt has been reported that Ephexin1 is positively correlated to pathophysiologic conditions like depression or recovery after CNS  injury, due to its roles in neuronal development and synaptic homeostasis, ,62,63,64Ephexin2 was identified in 2004 from a mouse liver cDNA library and initially was termed as Wgef, an abbreviation of weakly similar to Rho GEF 5 . StudiesEphexin2 is involved in convergent extension, a developmental step of anterior-posterior axis extension in Xenopus gastrulation through RhoA activation . In addiEphexin3, also called Tim , is ubiquitously expressed in many tissues, such as colon, kidney, trachea, prostate, liver, and pancreas, with tendency to be highly expressed in tissues containing epithelial cells . EphexinThe roles of Ephexin3 in physiological and pathological contexts are quite various. Genetic deletion of Ephexin3 causes defects in immature dendritic cell migration in vivo. In terms of cell migration, Ephexin3 is also involved in Src-induced podosome formation which is related to cell migration and adhesion. RNAi-mediated knockdown of Ephexin3 inhibits Src-dependent podosome formation whereas its overexpression increases the podosome formation through RhoA activation ,67. In aThe activity of Ephexin3 is also auto-inhibited by intramolecular interaction caused by the N-terminal inhibitory helix and the DH domain, which is similar to that of Ephexin1. Therefore, the regulatory mechanism for the activity of Ephexin3 is also comparable to that of Ephexin1. The inhibitory helix of Ephexin3 binds to the DH domain, which prevents RhoA access to the DH domain of Ephexin3 and results in the auto-inhibition. Tyrosine phosphorylation at Y1097 and Y1100 by Src leads to disruption of the intramolecular interaction between the inhibitory helix and the DH domain, which results in RhoA activation ,69,70.Most studies on Ephexin4, also known as Arhgef16, have focused on its role as a GEF for RhoG. However, the potential activity of Ephexin4 to regulate Cdc42 was also reported in a specific context. Tax-interacting-protein 1 (Tip-1) is a protein that interacts with HPV16 E6 oncoprotein to regulate E6-dependent cell motility. Intriguingly, Ephexin4 was identified as a novel binding partner of Tip-1 via a yeast two-hybrid screen. The interaction of Ephexin4 with Tip-1 alters its GEF activity toward Cdc42 ,57.The biological significance of Ephexin4 in various physiological and pathological conditions has been addressed. The potential involvement of Ephexin4 in preventing carcinogenesis was suggested from its down-regulation in kojic acid-stimulated A375 malignant melanoma cells . In addiA novel role of Ephexin4 in clearance of apoptotic cells was recently reported . InteracAnother name for Ephexin5 is Vsm-RhoGEF, standing for vascular smooth muscle-specific RhoGEF. As its name implies, it was identified as a RhoGEF expressed in vascular smooth muscle cells from different tissues including the heart, liver, kidney, aorta, and spleen. Along with the identification of its expression pattern, its roles as a key downstream regulator of EphA4 signaling have been revealed. Ephexin5 interacts with EphA4 through its DH-PH domain, and Ephrin-A-stimulated EphA4 phosphorylates Ephexin5, which activates RhoA and induces the formation of stress fibers related to the vascular smooth muscle contractility .Ephexin5 is highly expressed in the brain, especially in the hippocampus, and its functions in the brain have been well established . It is kAngiogenesis occurs through a series of complicated processes including sprouting, migration, tubulogenesis, and stabilization . To accoAll members of the Ephexin family function as GEFs for RhoA, Rac, Cdc42 and RhoG, which is closely related to cell proliferation and cell migration. Due to their pivotal roles in cell proliferation and migration, dysregulation of their activity or expression could be associated with tumorigenesis and metastasis. Indeed, the increased expression levels of Eph receptors or Ephexins have been observed in many cancer types. Moreover, mutations or transcript variants of Ephexins are also closely related to cancer ,49,68. TA few studies tried to modulate the activity of Ephexin3 using peptides mimicking the inhibitory helix or the most highly conserved surface of the DH domain interacting the inhibitory helix. However, modulating their activity is only tested in in silico or in vitro systems ,69,70. TFurthermore, Ephexin1 and Ephexin5 are associated with neuronal disorders such as depression, epilepsy, and Alzheimer’s disease ,61,79,80In this review, the biological significance of Ephexins in various physiological and pathological contexts and molecular mechanisms by which their GEF activity is regulated have been discussed. Starting from studies in the 2000s, their roles not only in neurogenesis but also in other cellular events have been reported. In particular, recent studies have provided the relevance of Ephexins to tumorigenesis and efferocytosis, suggesting that the unappreciated roles of Ephexins still remain and need to be explored. Accordingly, extensive and in-depth studies of them would provide a better understanding of the diverse processes, including neuronal development and cancer.


The aim of this study is to verify if the Insertion Torque Value (ITV) of 32 Ncm for immediate loading protocol (ILP), as indicated by literature, is still, with the advance in implant research, a real significant cut-off for long-term implant survival.In this retrospective study, data from 224 patients that during three years of clinical practice, were submitted to the insertion of 322 implants with immediate loading protocol, have been recorded, pooled and analyzed. Data were organized based on Insertion Torque Value (ITV): > 32 Ncm (CG) and < 32 Ncm (LTG) and two different groups of equal sample size, 161 implants each, were distinguished.Crestal bone reabsorption, and the implant failure rate were evaluated after 2-years of follow-up.p<0.001. However, the survival rate after 2-years of follow-up was quite high and similar for both groups: 96.89% for LTG and 97.52% for CG and no statistically significant differences have been found among the two groups for the implant failure rate (p=0.455). The Odds Ratio (OR) of implant failure was of 1.258 , but results were not statistical significant, p=0.740.The bone reabsorption in LTG (0.49 ± 0.11 mm) was significantly greater than CG (0.22 ± 0.04 mm), The present study showed that although implants with ITV> 32 Ncm are still characterized by a lower crestal bone resorption, there are no statistically significant differences among the two groups for what concerning the failure rate during the 2 years of follow-up and OR. These results permit us to suppose that the cut-off of ITV >32 Ncm for immediate loading implants, could be reduced to inferior values. However further studies are necessary to indicate precise clinical guidelines. Key words:Immediate loading, insertion torque, primary stability, dental implants, implant survival. A good primary stability and a direct interface between the implant surface and the alveolar bone during the healing process is fundamental for osteointegration .Traditionally, it was assumed that to achieve osseointegration, implants needed to be submerged under the mucosa and left without any loads for a period of 3–6 months . Then, pWith the advent of the immediate loading protocol (ILP), it is no longer necessary to wait this time and inconveniences; the implant can be loaded immediately after the surgical phase or within 48h . CompareP = 0.01)  .In order to use ILP, a high degree of implant primary stability measured by ITV must be verified intraoperative, as shown by Testori and coworkers .ITV is a biometric parameter that can be influenced by several conditions, such as the size of the recipient site, the morphology and quality of the bone, the macro and micro design of implants, and the surgical technique ,11. Undeet al. indicated a minimum ITV of 60 Ncm for single teeth, 45 Ncm for implants supporting partial-arch restorations, and 32 Ncm for implants supporting full-arch restorations , were selected, pooled and analyzed.A different Arabic number (code) was assigned to each implant, in order to distinguish from each other. Data were organized in two groups, basing on the Insertion Torque Value (ITV): conventional group, CG, with ITV >32 Ncm, and lower torque group, LTG, with ITV <32 Ncm.-Inclusion and Exclusion Criteria Inclusion criteria were: dental implants placed in the healed bone or in fresh extraction sockets, with ITV recorded and loaded with ILP with at least two years of follow-up.Other inclusion criteria were: bone volume enough to insert implants of suitable diameter without interventions of bone regeneration, the absence of disease that could affect bone healing, good general health, controlled oral hygiene, age between 18 and 75 years.Exclusion criteria were: severe parafunctions, severe intermaxillary discrepancy, drugs or alcohol addiction, poor oral hygiene, gestation or lactation, previous radiation therapy, periodontal disease untreated or unresolved.-Surgical and Prosthetic ProceduresDiagnostic models, endoral and panoramic radiographs, and computed tomography have been examined, before surgery, for each case.Before the surgery, all patients were informed about the procedures, and then they signed the informed consent; then they assumed a prophylactic antibiotic therapy  and rinsed for 1 minute with chlorhexidine mouthwash 0.2%.Local Anesthesia was performed with mepivacaine with adrenaline 1:100,000. Implants of various diameters and lengths  were positioned according to the manufacturer’s instructions.The ITV was measured intraoperative, through an implant micromotor (up to 80 Ncm) or the torque wrench (greater than 80 Ncm) and recorded.The electronic resonance frequency analysis, RFA , was used to measure the fixture implant stability during the insertion and at the time of the final impression  D1/D2 and D3/D4, respectively). Immediately after surgery, a provisional restoration was connected to the fixtures; only rehabilitations greater than three elements were loaded with functional occlusion.A postoperative antibiotic therapy 6 or 8 hours after surgery (1g of amoxicillin or 500 mg of clarithromycin) was prescribed for all patients.The time of definitive load varied according to the bone quality scale ; for bon-Follow-UpAll patients were seen 7 days after surgery. Survival rate was evaluated at 2-years of follow-up in which patients were observed once a month until definitive load, and then, once every 6 months. Criteria used for the survival rate were those proposed by Albrektsonn  and wereBone reabsorption was evaluated on digital endoral radiographs, by the use of a digital ruler , that measured the distance from implant’s shoulder to first bone-to-implant contact (BIC). The evaluation of bone reabsorption started since the fixtures were connected with definitive prostheses.-Statistical analysisAll medical data were recorded in data sheet and then the statistical analysis was performed using SPSS for Windows version 21 . The mean values ± standard deviation of ITV, average bone reabsorption and survival rate were calculated. The statistical analysis was performed through the Student’s T-Test with two tails for independent variables. The significance threshold was set at 0.05.The Odds Ratio for implant failure was also calculated through the free online software MedCalc Software .The implants analyzed in this study were of variable measures, diameters and lengths , were poOverall healing was optimal, the swelling was minimal, and patients reported no lingering pain in the 7 days after surgery.The connection of definitive prosthesis was screwed in 22% of cases and cemented in 78% of cases. Materials used for definitive crowns were metal-ceramic (87%) and integral ceramic (13%).p=0.455).The survival rate after 2-years of follow-up was of 97.52% for CG and 96.89% for the LTG. The failure rate was low for both groups and there were not statistically significant differences: 3.11% (5/161) and 2.48% (4/161) for LTG and CG, respectively  than single-tooth restorations 2 implants), , Fig. 2; implantsp=0.170), (Also the average timing of implant failure was very different among the two groups: 137.50+103.40 (CG) and 53.40+71.40 (LTG) days after the insertion, however, results were not statistically significative (=0.170), , Table 4p=0.740 for LTG.The calculated Odds Ratio for implant failure was 1.258 , The average ITV was 61.30 ± 12.84 Ncm and 24.03 ± 4.07 Ncm, for CG and LTG, respectively.Average bone reabsorption, calculated from the time of definitive load until the end of 2-years of follow-up was 0.22 ± 0.04 mm and 0.49 ± 0.11 mm for CG and LTG, respectively.p<0.01).Although the failed implants were not included for the calculation of the average bone reabsorption, the statistical analysis has shown significant differences between test and CG  shown by Gallucci itations .Contrarily, a study of Ottoni and coworkers showed a severe failure rate: 9 implants on 10 inserted with an ITV of 20 Ncm and immediately loaded, as part of a larger group test, failed . AnotherIt is important to highlight that the technological improvement of implant surfaces and the surgical tools and the refinements of the surgical protocols could have positively influenced our results, respect literature of the past 10 years.p=0.740). The peri-implant crestal bone reabsorption appears to be lower for CG than implants of the LTG. Statistical analysis shows a significant difference between control and LTGs. This might be explained by the fact that the implants screwed with a greater ITV, CG, were more stable than implants of the LTG and therefore less free to carry out micro-movements in order of microns; hence, around them, it was possible an healing without excessive remodeling of peri-implant bone tissue. This finding is in agreement with an animal study performed by Rea and coworkers that demonstrates how the peri-implant bone reabsorption is greater for implants placed with a lower ITV during the surgical phase(The Odds ratio was 1.258 for implant failure but the results were not statistically significant (cal phase. Anothercal phase. MoreoveIt is important to highlight that the Albrektsson criteria adopted in this study to evaluate the implant failures, considered only survival parameters, not the successful ones . This coThe results obtained in this study suggests that the cut-off for ITV of 32 Ncm, for ILP, could be reduced to inferior values making possible the extension of this loading protocol to cases that until now was not possible to obtain long-time success.Considering the number of patients included in this study and the missing of RFA data, the findings should be interpreted with care.Further studies and a greater number of patients are needed to ensure that these new values of insertion torque proposed for immediate loading implants are entirely based on evidence.


Background: Alzheimer's disease (AD) is characterized by progressive cognitive decline, often associated with Behavioral and Psychological Symptoms of Dementia (BPSD). Acetylcholinesterase inhibitors (ChEi) may attenuate cognitive decline and mitigate BPSD. The EVOLUTION group found that the switch from oral ChEi to transdermal rivastigmine patch formulation resulted in improvement/stabilization in the frequency of clinically relevant BPSD, but gender-specific subgroup analyses were not reported.Methods: Participants underwent Neuropsychiatric Inventory to assess the frequency and severity of neuropsychiatric symptoms at baseline and 3 and 6 months after the switch from oral ChEi to transdermal rivastigmine patch. A descriptive post hoc analysis was conducted to assess whether there were gender-based differences in BPSD profile during the 6 months after the switch.Results: The entire sample consisted of 475 patients, 274 women and 201 men. Women were on average slightly older and with poorer cognitive performance . In mild-AD patients (MMSE score 18–26), the frequency of BPSD did not change significantly over time and an association was found between gender and depression , anxiety (2.42 [1.23–4.79]), apathy (2.25 [1.07–4.70]), nighttime behavior disturbances (3.97 [1.66–9.49]), and appetite/eating abnormalities (2.39 [1.10–5.18]). Moderate-AD female patients had euphoria more frequently than male patients . The frequency of delusions, anxiety, and irritability decreased during the first 3 months after the switch, independently of gender.Conclusion: Mild-AD women tended to suffer more frequently from BPSD than men; in the 3 months after treatment switch, moderate-AD patients showed a decrease in delusions, anxiety, and irritability, with no significant differences between genders. Ad hoc studies to investigate this potential gender effect in AD could be well worthwhile. In one 6-month study, changes in Neuropsychiatric Inventory (NPI) scores were no different between the rivastigmine and placebo groups.16 In a different, 12-month study, agitation/aggression and anxiety/phobias improved significantly among AD patients treated with rivastigmine.17Appropriate, tailored interventions are essential to provide quality care. Such interventions include both nonpharmacological strategies and psychotropic agents. The etiology of BPSD has not been clearly delineated, but studies assessing the benefits of acetylcholinesterase inhibitors (ChEi) on BPSD suggest that some of these symptoms, such as agitation, apathy, and psychosis, may reflect a specific central cholinergic deficiency syndrome.18Norton et al. have suggested that caregiver interventions may become an important complement to pharmacological and other approaches to slowing the progression of dementia; they showed that for adult caregivers who are children of the patient, the personality traits of the caregivers are associated with the rate of cognitive decline in the receivers (CRs) with AD, regardless of coresidency.19Furthermore, closeness and loss of closeness in the caregiver-CR dyad may be associated with either positive or adverse outcomes for caregivers.20 While men and women are known to differ in the risk, pathogenesis, clinical manifestations, and prognosis of AD,21–23 the EVOLUTION study Group did not report gender-specific subgroup analyses, and current clinical guidelines do not differentiate between men and women in the use of ChEi. Accordingly, for the sample of patients in the EVOLUTION study, we conducted a post hoc analysis to assess whether there were gender-based differences in BPSD profile during 6 months after the switch from oral ChEi to transdermal rivastigmine patch.The EVOLUTION observational study evaluated the switch in ChEi in a sample of 635 AD patients who were no longer responsive to the initial treatment, with reduced tolerance and/or compliance and the loss of at least two points on their Mini-Mental State Examination (MMSE) score in the last 6 months. In analysis of a subsample of 423 patients in the EVOLUTION study, the study group found that the switch from oral ChEi to transdermal rivastigmine patch formulation not only slowed the progression of global cognitive impairment but also resulted in improvement/stabilization in the frequency of clinically relevant BPSD.post hoc analysis is part of the gender medicine project MetaGeM, designed to describe and analyze clinical outcomes, therapeutic approaches and safety data according to gender, based on nine observational studies; the MetaGeM methodology has been described extensively elsewhere.24This 25; (2) mild to moderate severity of dementia, defined as MMSE26 score of 26 to 10; (3) onset of symptoms at least 6 months before inclusion in the sample; (4) treatment with ChEi for at least 6 months, and first switch to another type of ChEi therapy due to lack of response and/or reduced compliance  and/or reduced tolerance ; (5) vision and hearing sufficient for compliance with testing procedures; and (6) presence of caregiver able to understand all testing procedures. Hospitalized patients were excluded.The EVOLUTION study was conducted in 38 outpatient memory clinics across Italy, on subjects who satisfied the following criteria: (1) diagnosis of probable AD according to the criteria of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA)20 This post hoc analysis used a subsample of EVOLUTION patients: patients without psychiatric disorders, who switched from oral ChEi to rivastigmine transdermal patch at baseline and who underwent 3- and 6-month follow-up visits. The switch followed treatment guidelines for AD; in particular, the practice for switching called for an immediate switch from other ChEi to patch 4.6 mg/24 hours, and 1 month after the switch the dose was increased to 9.5 mg/24 hours. Patients were then kept on this dosage unless they experienced adverse events; in this case, the rivastigmine patch dosage was reduced to 4.6 mg/24 hours.The EVOLUTION study design and methodology are described elsewhere.Women and men were described and compared at baseline according to sociodemographic variables  and clinical features . Caregivers (who remained the same for the entire length of the study) were described at baseline  and their characteristics compared between male and female patients.27) and NPI for the assessment of BPSD, carried out at baseline and at 3- and 6-month follow-up.Clinical data collection included MMSE  to 4 (very frequent) and severity from 1 (mild) to 3 (severe). If the symptom was absent, the score was 0. A composite score for each symptom was calculated, namely the product of the frequency and severity scores, with range accordingly from 0 to 12.The NPI is a useful instrument for characterizing the psychopathology of dementia syndromes, investigating the neurobiology of brain disorders with neuropsychiatric manifestations, distinguishing among different syndromes and assessing the efficacy of treatment.31 For homogeneous gender comparison, the sample was stratified according to severity of dementia: mild-AD patients  and moderate-AD patients (MMSE score of 17–10).A first exploratory analysis was conducted, considering for each domain patients with available NPI scores at baseline and 3- and 6-month follow-up and comparing women and men at each study visit with regard to the presence of neuropsychiatric symptoms. BPSD were considered present for composite scores ≥1. A composite score ≥4 indicated the presence of a clinically relevant symptom typically associated with therapeutic intervention; a score of 1–3, mild symptoms usually not requiring specific treatment; and a score of 0, no symptom.t-test (for continuous variables) and χ2 or Fisher's exact test . For the post hoc analyses, the significance threshold was set at 0.05 .Comparisons by gender were performed by Student's i.e., a NPI composite score ≥1)/absence of each specific BPSD at time x  was considered and gender was introduced in the models as constant effect over time (no interaction between time and gender was hypothesized).Confirmatory logistic regressions for repeated measures were then run to get a further evaluation of the association between gender and BPSD. A model for each BPSD domain was estimated. As binary dependent variable, the presence , marital status , education , smoking , alcohol consumption , concomitant ischemic heart disease, hypertension, dyslipidemia, diabetes, cerebrovascular disease (yes or no), caregiver's gender, caregiver's relationship to patient , ongoing antipsychotic and antidepressant therapy (yes or no), and previous treatment with oral rivastigmine (yes or no). The ongoing antipsychotic and antidepressant therapies were considered time-dependent variables and so evaluated at each time point. All the other covariates were assessed at baseline visit and considered constant over time. The results of the multivariate regressions provided an estimate of the association between gender and the presence of BPSD, adjusted for potential confounding factors.We were also interested in estimating the effect of time on the presence of BPSD in mild- and moderate-AD patients, holding gender and all the other variables of each model constant. For this reason, the visit  was also included as covariate in the model.To control for MMSE that differed significantly between genders, the models were estimated in two different subpopulations, mild- and moderate-AD patients.i.e., symptoms present at baseline and absent at follow-up) was calculated and compared by gender.Finally, we compared the results of these models with those of an exploratory analysis in which the proportion of patients with NPI remission , less likely to be married/cohabiting , and less well educated . Men were more likely to be past smokers (43.5% vs. 8.1% of women) or current smokers  and to be frequent alcohol consumers . No gender differences were found in employment status or concomitant diseases .The sample analyzed consisted of a total of 475 patients: 274 women (57.7%) and 201 men (42.3%); baseline demographic data are provided in t-test p-values, male vs. female = 0.275 and 0.159, respectively).There was no significant difference between men and women in time to onset of symptoms and to diagnosis: the means (±SD) for these variables were 1.3 (±1.1) and 2.4 (±1.7) years for men and ±1.4 (±2.2) and 2.7 (±2.0) years for women . The daily dosage of ChEi treatment before baseline did not differ between males and females.In the 6 months before baseline, 162, 14, and 25 men  were treated with donepezil, galantamine, and rivastigmine  and 235, 24, and 15 women  were treated with donepezil, galantamine, and rivastigmine , respectively . Women more frequently took antidepressants  , while no substantial gender differences were found at baseline in antipsychotic treatment —5.1% of women versus 8.5% of men; χ2 test p = 0.144.Among women, 5.5% were treated at baseline with memantine versus 3.6% of men . At each point of measurement, women's MMSE score was significantly lower than men's ; for 131 male patients (65.8%), the caregiver was the wife, while 165 female patients (61.6%) had a son or daughter as caregiver and 46 (17.2%) had other caregivers  . Other caregiver characteristics are shown in Men had a female caregiver in 89.6% of the cases versus 60.9% for female patients .The NPI assessment showed a higher frequency of delusions, hallucinations, depression, anxiety, apathy, and aberrant motor behavior at baseline in women than in men see  and 4. Np-value = 0.021), depression , anxiety , apathy , nighttime behavior disturbances , and appetite/eating abnormalities   see  and 4.p-value = 0.028); differently from mild-AD patients, in moderate-AD patients nighttime behavior disturbances were more frequent at baseline in men than in women . No gender differences were observed for the other symptoms  than in men , anxiety , apathy , nighttime behavior disturbances , and appetite/eating abnormalities .Moderate-AD female patients displayed euphoria more frequently than male patients .In mild-AD patients, no significant effect of time emerged in any of the NPI domains; in this group of patients, the frequency of BPSD did not change significantly.In moderate-AD patients, an association was found between time and delusions (OR [95% CI] at 3-month follow-up vs. baseline = 0.79 [0.64–0.98]), anxiety (OR [95% CI] visit at 3 months vs. baseline = 0.73 [0.57–0.93]), and irritability (OR [95% CI] visit at 3 months vs. baseline = 0.70 [0.53–0.93]). The frequency of delusions, anxiety, and irritability decreased during the first 3 months after the switch, independently of gender .No significant associations emerged between time and other BPSD.www.liebertpub.com/jwh).These results (thanks to control of confounding factors through multivariate estimation) actually overcome those of our exploratory analysis about the frequency of patients with remitted NPI symptoms during follow-up  and the frequency of delusions, anxiety, and irritability decreased during the first 3 months after the switch, independently of gender.Our 34 and gender was found to be a strong predictor of behavioral differences among AD patients.12 Women with AD were shown to suffer delusions and hallucinations more often9 and earlier10 than men. Furthermore, depression was associated with twice as great a risk of AD in women but not in men,35 and depression itself was found to be more prevalent in women with AD.11The female predominance in behavior disturbances was also reflected in the use of psychoactive medications, as women were more likely than men to be taking antidepressants, but not antipsychotics. Our data are in line with previous studies that found women with AD more often displaying a broader spectrum of BPSD,12 aggression,13 and vegetative changes such as overeating and oversleeping.12 Other studies of AD have found a higher, but not statistically significant, incidence of aggressive behavior in men.37 Our own data confirm these findings only in part, probably owing to differences in the samples and in the tools used to assess BPSD.In other studies, men have been reported as more commonly suffering apathy,p values) supported by confirmatory multivariate models.Our study has a number of strengths. The sample was larger than in most previous gender studies on AD, as subjects were recruited from a number of memory clinics across Italy. Sociodemographic and clinical data were collected using uniform structured evaluations. We used a descriptive statistical analysis (with exploratory Our project assesses gender differences in BPSD profile after the switch from oral ChEi to transdermal rivastigmine patch. However, our work also has limitations. Our pooled data lack a control population. To reduce possible bias, the study considered only patients who had been switched from oral ChEi to rivastigmine patch therapy.Our study, like most previous research on AD patient populations, indicates that the prevalence of various BPSD differs between women and men. Mild-AD women tend to experience BPSD more often than men; but where cognitive dysfunction is more severe, that is, among the moderate-AD patients, the prevalence of BPSD tends to be comparable between genders. Our data also suggest that in the 3 months after the switch, moderate-AD patients experienced a decrease in delusions, anxiety, and irritability, again with no substantial gender difference. The need is for substantially increased gender-specific data on treatment response, which could carry major prognostic and therapeutic implications in clinical practice.


What is the association of hearing loss with future incident dementia in the general population of Taiwan?In this population-based matched cohort study of 16 270 participants, hearing loss was positively associated with incident dementia, especially in patients aged 45 to 64 years.Hearing loss is associated with a higher risk of dementia, and findings suggest that hearing protection, screening, and treatment may be used as strategies to mitigate this potential risk factor. This population-based cohort study investigates the association of hearing loss with incident dementia among Taiwanese adults in the general population. Hearing loss (HL) may be a modifiable risk factor for dementia, and longitudinal studies are needed to examine the association of HL and dementia.To investigate the association of HL with incident dementia in Taiwanese adults in the general population.This population-based cohort study collected data from the National Health Insurance Research Database of Taiwan. Patients newly diagnosed with HL from January 1, 2000, through December 31, 2011 (n = 8135), constituted the exposed (HL) group. The HL group patients were matched by sex, age, residence, and insurance premium to individuals without HL (non-HL group) (n = 8135). Data were analyzed from January 1, 2000, to December 31, 2013.International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes.Hearing loss defined according to ICD-9-CM codes.Dementia classified according to P = .003). Subgroup analysis revealed that, among 3 age groups , the group aged 45 to 64 years was associated with a risk of dementia . In sensitivity analysis, the presence of HL among those aged 45 to 64 years  was associated with a risk of dementia.Of a total of 16 270 participants , 1868 developed dementia. The dementia incidence rate in the HL group was higher than that in the non-HL group  during the follow-up period. In the fully adjusted multivariate Cox proportional hazards regression model applied for risk analysis, patients with HL had a significant risk of dementia (hazard ratio [HR], 1.17; 95% CI, 1.07-1.29; false discovery rate [FDR] In this study, hearing loss was positively associated with a risk of dementia, especially in patients aged 45 to 64 years. Hearing protection, screening, and treatment may be used as strategies for mitigating this potential risk factor. Dementia is associated with a higher risk of mortality, higher health care costs, and disability. Current treatment strategies only ameliorate symptoms and do not change the disease course. Identification of patients at risk of dementia is critical for preventing an impending dementia epidemic. Hearing loss (HL) has recently been recognized as a risk factor for dementia. The risk of HL increases with age and is associated with lower scores on tests of memory and a higher risk of incident all-cause dementia.3 Hearing loss includes peripheral hearing impairment and central auditory dysfunction; both are associated with accelerated cognitive decline, cognitive impairment, and incident dementia.6 Evidence suggests that even mild levels of HL increase the long-term risks of cognitive decline and dementia.9 Hearing loss in older adults may play a role in social isolation, depression, disability, lower quality of life, and risk of dementia10; however, HL is a possible biomarker of and modifiable risk factor for cognitive decline, cognitive impairment, and dementia.11 A meta-analysis12 stated that 65% of the risk factors for dementia are hereditary or genetic, which means they are not modifiable; however, 35% of the factors can be modified. Moreover, the adjusted population-attributable fraction of HL was calculated to be 9.1%; HL had the highest population-attributable fraction compared with other identified risk factors such as hypertension, obesity, depression, types 1 and 2 diabetes, and smoking. Thus, this longitudinal cohort study aimed to examine the association between HL and dementia.The prevalence of dementia has increased,STROBE) reporting guideline.The institutional review board of National Taiwan Normal University approved this study. Written informed consent from the study patients was waived by the institutional review board because data were collected from the National Health Insurance Research Database (NHIRD), which consists of deidentified secondary data released for research purposes. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology  program of Taiwan was established in 1995; it is a single-payer insurance system operated by the government that ensures the health of the entire nation and prevents social problems caused by poverty and disease. As of 2014, 99.9% of Taiwan’s population was enrolled in the NHI program.This cohort study was conducted using data from the NHIRD.International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) were used for disease diagnosis. Hearing loss was defined according to the ICD-9-CM codes 389 and A241 and included conductive, sensorineural, and mixed conductive, sensorineural, and unspecified HL. All medical claims between 1997 and 2013 containing these codes were obtained from the NHIRD for further analysis. Hearing loss with a duration of more than 1 year was considered, and at least 2 outpatient visits or any inpatient diagnosis was required. Patients newly diagnosed with HL from January 1, 2000, through December 31, 2011, were included in the exposed group (HL group); persons who were diagnosed with HL from 1997 through 1999 were excluded. Thus, 8135 patients newly diagnosed with HL without a dementia diagnosis before the index date were included. These exposed patients were compared with 8135 sex-, age-, residence-, and insurance premium–matched unexposed individuals (non-HL group) by exact matching. The index date was calculated by adding 365 days to the HL diagnosis date, and this date was assigned to the respective matched unexposed individuals, who were NHI enrollees without any HL or dementia diagnosis before the index date. Dementia  constituted the study outcome , cerebrovascular disease (ICD-9-CM codes 362.34 and 430-438), chronic obstructive pulmonary disease , types 1 and 2 diabetes (ICD-9-CM codes 250 and 251), chronic kidney disease (ICD-9-CM codes 580-589), hypertension (ICD-9-CM codes 401-405), hyperlipidemia (ICD-9-CM code 272), anxiety , depression , alcohol-related illness , head injury , rheumatoid arthritis (ICD-9-CM code 714), and asthma (ICD-9-CM code 493). The comorbidities included were required to be more than 1 year in duration and to have at least 2 outpatient visits or any inpatient diagnosis. Finally, the hospitalization length was included.To better understand the association between HL and dementia, several potential confounders were included in this study. We defined potential confounders based on medical claims data from the NHIRD from January 1, 1997, to the index date. Demographic data included age, sex, residence, and insurance premium. The following general physical health data related to dementia were also collected: coronary artery disease . P < .05 indicated significance.Data were analyzed from January 1, 2000, to December 31, 2013. The first dementia diagnosis of each person within the study period was used to calculate the risk of dementia during specific time intervals. The risk of dementia during the follow-up period was calculated using survival analysis. Follow-up was conducted from the index date to withdrawal from the NHI program or December 31, 2013, whichever occurred first. This study included incident dementia diagnosed from the index date (HL diagnosis date plus 365 days) to December 31, 2013. Multivariate Cox proportional hazards regression models adjusted for covariates were used to determine the associations of HL with dementia. The false discovery rate (FDR) and hazard ratios (HRs) with 95% CIs were calculated. False discovery–adjusted 14To validate the robustness of the main study findings, we performed sensitivity analyses. Through subgroup analysis, the association of HL subgroups with dementia risk was evaluated. Furthermore, we used propensity score matching to control for sampling bias. Propensity scores represent patients’ probability of dementia incidence, and the scores were determined using a multivariate logistic regression model. The potential confounders used to calculate propensity scores included sex, age, residence, insurance premium, coronary artery disease, cerebrovascular disease, chronic obstructive pulmonary disease, diabetes, chronic kidney disease, severe liver disease, hyperlipidemia, anxiety, depression, alcohol-related illness, head injury, rheumatoid arthritis, asthma, and hospitalization length. The index year was defined as the year of the first HL diagnosis, and the index year was randomly selected for patients without HL. Using the estimated propensity scores, the HL and non-HL groups were matched at a ratio of 1:1 as closely as possible within each matched index year. Thus, the index year was the same between patients with HL and propensity score–matched individuals without HL. For balance diagnostics, the standardized difference was used to compare the mean of the binary variable between the HL and non-HL groups in propensity score–matched and nonmatched samples. A standardized difference of less than 0.1 indicated a negligible difference in the prevalence of a covariate between the HL and non-HL groups.P < .001). The mean number of hospital admission days was higher in the HL group than in the non-HL group .A total of 16 270 participants were included, of whom 9286 (57.1%) were men and 6984 (42.9%) were women . The exposed and unexposed groups included, respectively, 8135 patients with newly diagnosed HL (aged ≥45 years) and 8135 sex-, age-, residence-, and insurance premium–matched individuals without HL. Descriptions and a comparison of the groups’ characteristics are presented in P < .001 according to the log-rank test).Of a total of 16 270 participants, 1868 developed dementia during the follow-up period. Among them, 1094 (58.6%) were from the HL group and 774 (41.4%) were from the non-HL group, as shown in the P = .003). Advanced age  was significantly and positively associated with dementia; however, a high insurance premium  was significantly and negatively associated with dementia. Moreover, cerebrovascular disease , diabetes , anxiety , depression , alcohol-related illnesses , and head injury  were significantly and positively associated with dementia  according to the fully adjusted multivariate Cox proportional hazards regression model for risk analysis. Subgroup analysis by sex and age groups (eTable in the P = .008) and that the group aged 45 to 64 years was positively associated with dementia .As shown in P = .051). Advanced age , cerebrovascular disease , diabetes , anxiety , depression , and head injury  were significantly and positively associated with dementia , and the highest insurance premium was significantly and negatively associated with dementia . These findings were similar to the results of our main analysis. Subgroup analyses revealed that, among the 3 age groups (eTable in the P = .01). Male sex was not associated with a significant risk of dementia. Segment-adjusted analysis showed that HL was not significantly associated with dementia 1 to 4 years after the index date . The association was significant 5 to 12 years after the index date  in exact matching analysis; the association between HL and dementia 1 to 4 years after the index date  and the association 5 to 12 years after the index date  in propensity score matching analysis were not significant.The distributions of potential confounders were similar between the HL and non-HL groups after propensity score matching  . The res21 test, 2.19; P = .14) or between alcohol-related illness and HL  were not significant. In the group aged 65 to 74 years, the interaction between head injury and HL was significant , and the interaction between alcohol-related illness and HL was not significant . In the group aged 75 years or older, the interactions between head injury and HL  or between alcohol-related illness and HL  were not significant.In the group aged 45 to 64 years, the interactions between head injury and HL . However, scant evidence suggests an increased risk of dementia or AD in middle-aged patients with HL, and this research topic has received little attention previously. Recently, Livingston et al12 observed that preventing HL in midlife may modify the 9.1% risk of incident dementia. A recent cohort study16 reported that midlife HL is associated with an increased rate of dementia at younger than 60 years, and the association between HL and cognition may be due to shared etiology or because HL causes cognitive reduction through impaired speech perception in younger individuals and increased use of executive function and working memory in older people, resulting in the constant effort. These findings support the association between midlife HL and dementia.The main analysis results demonstrated that in the HL group, patients aged 45 to 64 years showed significantly stronger and more positive associations with dementia occurrence than patients aged 65 to 74 years or 75 years or older compared with their counterparts in the non-HL group. Patients with HL aged 45 to 64 years were characterized by a higher HR, whereas similar findings were not obtained for patients aged 65 to 74 years or 75 years or older. Previous studies17 To compensate for decreased auditory input owing to HL, increased listening effort is required through the additional recruitment of frontal areas.18 An increase in cognitive load occurs in patients who are hard of hearing; consequently, cognitive processes such as memory and executive function are adversely affected.20 Hearing loss, defined as sensory deprivation, may alter the usual pattern of resource allocation in the brain, thereby affecting neural reserves and cognitive performance.21 Hearing loss leads to altered auditory processing, and research has shown that cross-modal neuroplasticity changes in the auditory cortex and altered visual and audiovisual information processing affect functional connectivity between the sensory cortices.22 Hence, early HL development may causally accelerate atrophy in the entire brain, which could lead to cognitive reserve depletion in the brain.23Several neural changes have been described in people with hearing impairment. Age-related HL may result in the acceleration of aging because the peripheral and central nervous systems can alter synapses and neural anatomy with aging.24 and patients with HL may experience long-term disturbances in life, such as difficulties in communication, social isolation, and bad mood, which further suggests that HL may be associated with dementia.25 Intervention studies have indicated that hearing aids are associated with higher cognitive performance, and this association is mediated through social isolation or depression. Higher levels of HL are associated with an increased risk of social isolation,27 and social isolation and depression have been found to exacerbate cognitive impairment.28Hearing loss is associated with difficulties in understanding speech, especially under adverse listening conditions,29 Studies31 have demonstrated that hearing aids and cochlear implants impede cognitive decline. Hence, the early identification of HL in patients and successful hearing rehabilitation can mitigate the negative effects of HL.12 However, the ideal time to perform HL screening to reduce the risk of dementia remains unclear. The findings of the present study suggest that screening for HL should be performed when people are middle aged.Hearing loss is a potential reversible risk factor for dementia and AD.P < .01) in fully adjusted analysis, namely, cerebrovascular disease, diabetes, anxiety, depression, alcohol-related illnesses, and head injury. This finding implies a strong association between these comorbidities and dementia risk. An increasing number of studies have reported that cerebrovascular disease, diabetes, anxiety, depression, and head injury are risk factors for dementia, and these conditions might interrupt cognitive reserve function (as discussed previously)12; however, alcohol-related illnesses did not show such an association. Chronic alcoholism adversely affects the brain, causing cognitive impairment.33 A study indicated that alcohol use–related disorders are associated with a significantly higher risk of dementia.34 Other studies have shown that frequent alcohol consumption is associated with an increased risk of dementia compared with infrequent alcohol consumption.35 However, a systematic review36 indicated that light to moderate alcohol consumption may protect against AD and dementia. This discrepancy may be due to the case definition. That study included patients with confirmed diagnoses related to alcoholism, and previous studies have included patients based on self-report drinking behavior questionnaires.In the present study, 6 comorbidities were significantly associated with an increased risk of dementia (FDR 12This cohort study was based on nationwide representative data, and potential confounders such as social and demographic factors and the general health status were controlled for in the adjusted multivariate Cox proportional hazards regression models in the main analysis and through propensity score matching in the sensitivity analysis. However, the principal limitation with any study of this nature is that causality is difficult to infer, and we can only state that findings support a given hypothesis. In addition, the main limitation of studies based on the insurance database is the lack of precision in dementia diagnosis. Moreover, the database contains limited or no information on other potential confounders such as educational level, body mass index, physical activities, diet pattern, blood pressure, blood glucose levels, smoking, and use of hearing aids. Information on dementia subtype and HL severity is also lacking in the study database. Disease onset and diagnosis may differ according to the economic status and residence of patients because these variables affect access to neurologists. The comorbidity rate in patients with HL was higher than that in the non-HL group; patients with HL are possibly diagnosed with dementia earlier due to frequent outpatient visits. The HL group might have more opportunities for dementia diagnoses than the non-HL group. We used propensity score matching in sensitivity analysis to address this potential bias. Our segment analysis showed that the association of HL with dementia was significant at 5 to 12 years and not at 1 to 4 years after the index date of HL. Therefore, this bias was weak in our study. Despite the limitations of this study, the association between HL and dementia was consistent with many other investigations in the literature.In this cohort study, HL was associated with a significant increase in the risk of dementia, especially in patients aged 45 to 64 years. This finding suggests that the implementation of early hearing protection, HL screening, and the use of hearing aids may help to mitigate this potential risk factor for dementia.


Data from weather stations at airports, far away locations or predictions using macro-level data may not be accurate enough to disseminate visibility related information to motorists in advance. Therefore, the objective of this research is to investigate the influence of contributing factors and develop visibility prediction models, at road link-level, by considering data from weather stations located within 1.6 km of state routes, US routes and interstates in the state of North Carolina (NC). Four years of meteorological data, from January 2011 to December 2014, were collected within NC. Ordinary least squares (OLS) and weighted least squares (WLS) regression models were developed for different visibility and elevation ranges. The results indicate that elevation and cloud cover are negatively associated with low visibility. The chances of low visibility are higher between six to twelve hours after rainfall when compared to the first six hours after rainfall. A visibility sensor was installed at four different locations in NC to compare hourly visibility from the selected regression model, High-Resolution Rapid Refresh (HRRR) data, and the nearest weather station. The results indicate that the number of samples with zero error range was higher for the selected regression model compared with the HRRR and weather station observations. Each year, on average, 5,376 people are killed and over 418,000 people are injured in weather-related road crashes . Wet pavFog and low visibility are localized phenomena. However, it is expensive to install visibility sensors every few kilometers along a road. Therefore, predicting fog events, disseminating that information to motorists beforehand, and exploring technologies to dynamically adjust speed limits is vital to avoid fog-related crashes.Past researchers have adopted statistical or numerical modeling techniques to predict fog events. Motorists are often caught unaware by sudden reductions in visibility . Low visApplying fog prediction models to predict low visibility events could help to inform motorists in advance. Additionally, accurate meteorological data are essential for collision analyses to establish contributing factors associated with these collisions. However, crash investigations at many locations rely on observational data from distant weather stations that may have recorded very different meteorological conditions. It is possible to improve the reliability of predicted low visibility conditions through models developed using nearby weather station data or via technologies for reducing crashes or identifying weather-related contributing factors in collision analyses.Past studies have investigated the contribution of several meteorological predictors on visibility. However, the influence of rainfall in past hours, the time-of-the-day, and the presence of water bodies within the vicinity were not explored in the past. Also, the influence of meteorological factors on visibility could vary with the elevation and was not explored in the past. Considering all visibility records may reduce the applicability of models for road link-level prediction. These factors were accounted for by modeling low visibility conditions in this research.1.to investigate the influence of contributing factors,2.to develop visibility prediction models for different visibility and elevation ranges, and,3.to compare visibility from different data sources.Numerical weather prediction models such as the North American Regional Reanalysis (NARR) and High-Resolution Rapid Refresh (HRRR) forecasts can help to analyze weather conditions to some extent. However, the applicability of these models at road link-level is unclear. Using low visibility meteorological data at weather stations near traffic links may help improve the accuracy of the visibility prediction models and assist with the dissemination of such information to motorists or dynamically adjust speed limits in a timely manner. Therefore, the objectives of this research study are:This research focuses on considering data from only weather stations located within 1.6 km of highways and developing regression models to predict visibility. Collecting meteorological data within the vicinity of road links and then developing statistical models will help to identify the factors influencing low visibility conditions at road link-level in addition to improving the accuracy of the predictions.21.Select weather stations close to the road network and collect meteorological data2.Process data3.Develop regression models to predict visibility4.Compare visibility from the developed model and other data sourcesThe methodology adopted in this research includes the following steps.Each step is explained next in detail.2.1The Integrated Surface Database (ISD) comprises hourly meteorological data from over 35,000 locations worldwide. This dataset is maintained by the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environmental Information (NCEI) . The datTypically, the source of the meteorological dataset is weather stations located at airports. Before distribution/sharing, the ISD database undergoes a meticulous quality control process . In spitFor predicting fog events for motorists, 42 ISD locations were selected in NC. These locations are within 1.6 km from state routes, US routes, and interstates . Four ye2.2In this step, the missing values were deleted from the database. The elevation (m), cloud cover (%), wind speed at 10-m above ground level (AGL) (m/s), and amount of precipitation (mm) were considered as the predictor variables.According to NOAA, fog consists of a collection of suspended water droplets or ice crystals near Earth's surface that leads to a reduction of horizontal visibility below 1 km . TherefoDew point depression (‘tair_dew’ in Kelvin) was computed as a continuous variable by computing the difference between air temperature and dew point temperature for every hour.2.3Elevation plays an important role in low visibility events. Further, only 9% of recorded visibility values at the selected 42 ISD locations are less than 2,000 m. Considering all recorded visibility values for modeling may result in skewed/biased predictions. Therefore, linear regression models were developed to predict visibility using data for different visibility and elevation ranges.1.Dense fog <40 m2.Thick fog 40 m to 200 m3.Fog 200 m to 1,000 m4.Mist/haze 1,000 m to 2,000 m5.Poor visibility 2,000 m to 4,000 m6.Moderate visibility 4,000 m to 10,000 m7.Good visibility 10,000 m to 40,000 m8.Excellent visibility >40,000 mPer the International standard, visibility range is classified into eight different classes . They arIn this research, both fog and non-fog events were considered to eliminate bias and investigate the influence of contributing factors. To ensure that the sample is adequate and to attain statistically meaningful results, the visibility range was classified into four groups: less than 15,000 m, less than 10,000 m, less than 5,000 m, and less than 2,000 m. Visibility less than 15,000 m includes visibility values ranging from dense fog to good visibility while visibility less than 10,000 m includes visibility values ranging from dense fog to moderate visibility. Visibility less than 5,000 m includes visibility values ranging from dense fog to poor visibility and visibility less than 2,000 m includes visibility values ranging from dense fog to mist/haze conditions. Further, for each visibility range, elevation was further classified into five groups: less than 50 m, 50 m to 250 m, 250 m to 750 m, and greater than 750 m.weighti = 1/variancei (Ordinary least squares (OLS) and weighted least squares (WLS) regression models were developed using STATA to examine the influence of predictor variables on visibility. OLS regression is the simplest form of regression and tries to minimize the residual sum of squares (RSS). In OLS regression, each observation receives equal weight (irrespective of the distance between the observation and population mean) so as to minimize the RSS. Contrarily, weights are used to minimize the RSS in the case of WLS regression. The observations closer to the population mean receive more weight. For example, ariancei , where “Based on the visibility and elevation ranges, data were used for the development of regression models. The predictor variables such as elevation, cloud cover, wind speed at 10-m, dewpoint depression, the time-of-the-day, rainfall in past hours, and the presence of water bodies within 1.6 km of the weather stations were considered for the model development. All the predictor variables were initially considered in the model development and the predictor variables with p-value greater than 0.05 were removed one at a time . This method is also known as the backward elimination method. The visibility value is considered as the dependent variable.Altogether, twenty OLS and twenty WLS regression models were developed in this research. Predictor variables were identified as a significant variable if the p-value is less than 0.05 . The performance of the developed models was assessed using statistical measures such as R-square, adjusted R-square, Akaike information criterion (AIC), and root mean square error (RMSE) in addition to the sign of the computed coefficient for each significant predictor variable. The best-fitted regression model was selected based on the statistical measures and their applicability for predicting visibility at link-level.2.4A visibility sensor was installed at four different locations across NC. In addition, visibility values from the HRRR model were compared with the visibility values from the visibility sensor. HRRR is a NOAA real-time 3 km resolution model that assimilates radar data. Along with visibility, the model forecasts meteorological parameters such as 2-m air temperature, 2-m dewpoint temperature, 2-m relative humidity, 10-m zonal and meridional wind speeds, accumulated precipitation, total cloud cover, surface ceiling height, skin temperature, moisture availability, and downward shortwave radiation.To check the predictability of the best-fitted regression model, the meteorological data (predictor variables) such as 2-m air temperature, 2-m dew point temperature, cloud cover, wind speed at 10-m AGL, precipitation, and elevation were collected from the nearest weather stations  and added to the developed regression model. The estimated visibility from the regression model was also compared with the visibility sensor.The nearest HRRR grid point and the nearest weather station from the visibility sensor are presented in 1.Dense fog (visibility less than 40 m) represented as 12.Thick fog (visibility between 40 m to 200 m) represented as 23.Fog  represented as 34.Mist/haze  represented as 4For comparison purposes, the hourly visibility from each data source was classified as per the international standards .1.Dense The errors were computed by computing the difference between the visibility categories .(1)Error3Over the span of 11 years, from the year 2005 to the year 2014, the average annual frequency of visibility less than 2,000 m was reported at 73 weather stations in NC . The topSeveral sets of regression models (OLS and WLS) were developed based on the visibility and elevation range, by considering the weather stations close to the road network. The developed models are discussed next.3.1Similar trends were observed in the case of the WLS regression models. The coefficients of predictor variables in the OLS and WLS models are approximately consistent. In terms of statistical measures, both the OLS and WLS models are acceptable, but the developed WLS models have slightly higher R-squared and adjusted R-squared values. Also, AIC and RMSE are found to be lower for WLS models compared to OLS models. Similar results were observed in the case of models developed for different elevations.3.2The developed OLS and WLS regression models for visibility less than 10,000 m are summarized in 3.3The developed OLS and WLS regression models for visibility less than 5,000 m are summarized in 3.4The developed OLS and WLS regression models for visibility less than 2,000 m are summarized in Comparing the high visibility  with low visibility  regression models, the amount of precipitation is negatively associated with visibility less than 15,000 m, while the amount of precipitation is positively associated with visibility less than 2,000 m. In other words, the chance of visibility less than 2,000 m due to fog is lower in the event of heavy rainfall compared to a light rainfall, if all the other factors are kept constant.Considering all the models, the WLS regression model for visibility less than 2,000 m that considers all the samples is observed to best fit the data with higher R-square and adjusted R-square values, lower AIC, and lower RMSE values. In addition, this regression model would help to understand the effect of meteorological predictor variables on low visibility conditions at link-level. It is mathematically represented as 3.5The hourly visibility values from the visibility sensor were compared with the nearest HRRR grid point, the WLS regression model based on visibility less than 2,000 m, and the nearest weather station data. In approximately four months of data collection, 25 hourly events were recorded with visibility less than 2,000 m. The selected hourly visibility values were classified as per the international standards and errors were computed by computing the difference between the visibility sensor data and respective data source as represented in The error histogram between the visibility classification from HRRR, regression model and weather station compared with the visibility sensor is shown in The results indicate that the number of samples with zero error range was higher for the selected regression model compared to HRRR and the weather station observations. Also, the majority of the samples for HRRR and the weather station have an error of -1 . This indicates that the HRRR model predicts visibility one classification higher than the visibility sensor. This could be due to the distance between the HRRR grid point and the visibility sensor. The same reason applies to the error histogram associated with the weather stations data. For some locations, the nearest weather station is located at >21 km away from the visibility sensor. However, the HRRR model directly considers the real-time data from radar data and can provide two-hour forecasted weather information in real time. Therefore, this could be a possible data source for practitioners to disseminate information to motorists.4This paper focuses on investigating the influence and identifying factors associated with different visibility and elevation ranges at link-level. The descriptive analysis showed that the frequency of low visibility events is higher in the mountainous region when compared to other parts of NC. The WLS regression model for visibility less than 2,000 m, by considering all the samples irrespective of elevation, was considered as the best-fitted model to predict low-visibility events. In general, elevation and cloud cover are negatively associated with visibility less than 2,000 m. In addition, the chances of low visibility events are higher between six to twelve hours after rainfall when compared to the first six hours after rainfall.The predicted air temperature, wind speed, precipitation, dew point temperature, and cloud cover are required for predicting the visibility less than 2,000 m using the developed regression model. These data elements must be captured for application purposes.The HRRR model is a numerical weather prediction model that produces new hourly forecasts every hour and could be a solution for informing motorits of low visibility conditions. The HRRR model can help to predict visibility dynamically for the next two hours. Also, it can provide visibility information for future timestamps at a link-level. This resource could be very useful for practitioners to provide dynamic forecasts of visibility information to motorists through radio/mobile application-/dynamic signs.In this research, most of the nearest HRRR grid points and the nearest weather stations were located within a range of 0.5 km to ∼2.0 km from the visibility sensor. Since fog is a highly localized phenomenon, the distance between each HRRR grid point, visibility sensor, and weather station would definitely play an important role when comparing visibility values from different data sources. Therefore, other approaches such as interpolating the visibility values obtained from the HRRR model and then comparing these with a significantly larger number of visibility values from the installed sensor could be considered as a possible improvement and explored in the future.This research study focuses only on visibility related to fog events, but not reductions to visibility during heavy rainfall, dust, smoke, and wind-blown snow events. Integrating all of the aforementioned contributing factors to model low visibility under adverse weather conditions also merits an investigation.Srinivas Pulugurtha: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper.Ajinkya Mane: Performed the experiments; Analyzed and interpreted the data; Wrote the paper.Venkata Ramana Duddu: Analyzed and interpreted the data; Wrote the paper.Christopher Godfrey: Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.North Carolina Department of Transportation (NCDOT).This work was supported by the The authors declare no conflict of interest.No additional information is available for this paper.


The use of residential eating disorder (ED) treatment has grown dramatically in the United States, yet there has been minimal evaluation of treatment outcomes. Thus, outcome data on weight restoration, purging behaviors, and/or Global Assessment of Functioning (GAF) for 1,421 patients treated over an 8-year period in residential ED programs are described. Results suggest that, (1) for patients who needed weight restoration upon admission, adolescent and adult patients gained 2.0 and 2.1 lb/week, respectively; (2) of patients who reported purge behavior the month before admission, 89.1% were able to completely cease purging while in treatment; (3) although improvement of approximately 10 mean GAF points was made during treatment, patients were still quite impaired at discharge; and (4) mean length of stay was 12 days longer for adolescents than adults, and 10–15 days longer for patients diagnosed with anorexia compared to bulimia or ED Not Otherwise Specified (EDNOS), respectively. Other demographic statistics and additional analyses are presented. Limitations include the high variance of purging data and reliance on self- and parent-report for admission data. The data on the 1,421 patients, which represents 96% of all patients treated during the study period, more than doubles the number of residential ED patients with outcome in the literature. With decreases in insurance reimbursement in the 1990s for inpatient hospital treatment for patients with eating disorders (EDs), alternative levels-of-care, including that of residential treatment, were developed for management of the medical, nutritional, and mental health care needs of the ED patient population in the United States. Today in the United States, although around-the-clock-care is provided at both residential ED treatment and inpatient hospitalization, residential care provides primarily psychological treatment  to medically-stabilized patients, whereas inpatient hospitalization usually provides only short-term medical stabilization, often without ED-specific psychological treatment and often at a significantly greater daily cost than residential treatment. However, in the 30 years since its inception, residential ED treatment has received relatively little study. To date, there have been a total of eight studies examining admission-to-discharge outcomes in residential ED treatment. A review by While there is a dearth of outcome data, residential ED treatment centers are increasing. In a 10-year period, the number of ED residential treatment centers in the United States grew from 22 in 2006  to at leThis study corresponds to that need and describes outcome data for over 1,400 patients treated for EDs in 12 residential facilities operated by one large treatment program in the United States over an 8-year period. The data were analyzed and are being presented by the Divisions of Adolescent Medicine and Child and Adolescent Psychiatry, along with the Biostatistics Unit, of Northwell Health, an academic medical center in New York. The data demonstrate differences between admission and discharge for patients with the DSM-IV-TR  diagnoseCenter For Discovery, which opened in 1997, operates residential ED treatment facilities, each with a maximum census of six or eight patients. Patients who are admitted to a Center For Discovery residential facility live at the treatment facility, generally for more than 1 month. Some of the (gender-inclusive) facilities treat only adolescent patients, aged 10–19, while others treat only female-identifying adults. Between 2006 and 2013, Center For Discovery operated as many as 12 residential facilities in California, Washington, Illinois, and Connecticut.Center For Discovery is like other ED residential treatment in many ways. Weekly programming includes two to three individual sessions; one to two family sessions; dietary, medical, and psychiatric sessions; and between 35 and 40 therapeutic groups. Modalities such as Exposure Response Prevention, Dialectical Behavioral Therapy, Cognitive Behavioral Therapy, Acceptance and Commitment Therapy, and a Family Systems Approach are utilized. However, according to their outreach material, there are several factors that make Center For Discovery unique: (a) Treatment takes place in actual homes in residential neighborhoods, rather than in large, institutional settings. (b) Patients with EDs are not mixed with patients with other primary mental health disorders—that is, although it is common for patients to present with co-occurring diagnoses , all patients admitted into the program have a primary ED diagnosis and all treatment provided is specialized for patients diagnosed with an ED. (c) Because Center For Discovery treats such small groups of patients in each, the patient to staff ratio is very high, with typically only one to three patients for every one staff during waking hours  . All staBetween 2006 and 2013, patient data were collected at the time of admission and discharge via standardized measures, and post-discharge via a retrospective chart review. This study utilizes the data that were collected retrospectively from paper charts, and includes age; gender; race and ethnicity; DSM-IV-TR  ED diagnGlobal Assessment of Functioning scores were established by the treating, licensed (or supervised by a licensed) therapist for each patient on admission and discharge, as described in the DSM-IV-TR . DiagnosAs what constitutes a “healthy” body mass index  is not standardized for children/adolescents , BMI is only provided for adult patients in this study (though BMI change is noted for both adolescents and adults). In presenting the BMI data, the authors acknowledge the research indicating that BMI is often a poor indicator of health both in children and adolescents, as summarized in a review by For both adult and adolescent patients, percent of minimum target body weight (%TBW) is used as a standardized marker of health in this study and was calculated per Center For Discovery protocol: For patients diagnosed with AN and treated at the adolescent facilities, historical growth charts were utilized, often targeting the 50th percentile for height and age, to identify a minimum TBW; current weight was divided by TBW to identify %TBW. For patients  diagnosed with AN treated at the adult facilities, the HAMWI method was utilized to calculate TBW—that is, 100 pounds (lb) for 60 inches and 5 lb for every inch above 60 inches. Current weight was then divided by the TBW to identify %TBW for adult patients. Per protocol, if the treating physician or dietitian felt that this minimum TBW was too low to provide physical and psychological remission from ED symptoms, this TBW could be adjusted for both adolescent and adult patients. It should be noted that the concept of minimum TBW replaces the term ideal body weight (IBW), which has been used for many years in the ED field, because the word “ideal” in this context is both value-laden and imprecise.Of the 1,485 patients treated (>1 day) at Center For Discovery ED residential facilities between 2006 and 2013, 1,421 (95.7%) were included in this study. Inclusion criteria were: (a) first admission to Center For Discovery, (b) data on ED diagnosis, and (c) data on patient age. As fewer of the facilities were dedicated to adults (three facilities) than were dedicated to adolescents (eight facilities), it was not surprising that the sample was predominately adolescent (68.9%). So as not to skew the descriptive data unrepresentatively, the samples were examined separately.Of the 979 adolescent patients, 91.0% identified as female, 8.9% identified as male, and 0.1% (1 patient) were unspecified; 73.0% identified as White, 13.7% as Hispanic, 2.7% as Asian, 1.0% as Black, 5.7% as multiracial/multiethnic, 1.8% as other races/ethnicities, and 2.0% (20 patients) did not have data for race/ethnicity. Of the 442 adult patients, 98.0% identified as female and, as some of the (gender-inclusive) adolescent facilities treated patients up to age 19, 2.0% (nine patients) identified as male; 77.8% of adult patients identified as White, 11.31% as Hispanic, 1.6% as Asian, 0.9% as Black, 4.1% as multiracial/multiethnic, 0.9% as other races/ethnicities, and 3.4% (15 patients) did not have data for race/ethnicity.In 2014, Center For Discovery sent their data for the years 2006 through 2013 to the Biostatistics Unit and the Divisions of Adolescent Medicine and Child/Adolescent Psychiatry of the North Shore-Long Island Jewish Health System  for analysis and interpretation. Descriptive statistics were calculated to explore the demographics of the sample and to determine: (a) the changes in GAF score experienced by all patients, (b) the changes in purging behaviors experienced by patients diagnosed with AN-P and BN, and (c) the changes in weight experienced by patients diagnosed with AN.SD = 1.6) and 442 were adults with an average age of almost 25 years (SD = 9.2). As evident in n = 337) and almost 90% of adolescents (n = 824) having received prior outpatient treatment and almost half of all adolescents (n = 496) and adults (n = 187) having been hospitalized prior to Center For Discovery. Fewer patients, especially adolescent patients, had received prior treatment on the middle of the continuum of care . In total, 96.9% of the patients  had at least one form of prior treatment.Of the 1,421 patients in this study, 979 were adolescents with an average age of 15 years (n = 545) were diagnosed with AN, whereas approximately 45% of adult patients (n = 198) were diagnosed with AN. On the contrary, approximately 45% of adolescent patients (n = 452) were treated for purge behaviors, whereas 60% of adult patients (n = 266) were treated for purge behaviors. The difference between the percentage of adults and the percentage of adolescents diagnosed with BN was over 10%, with adults more frequently receiving the BN diagnosis. Of importance to note, with the edition of DSM-5 , about half of both adults and adolescents were treated for purging behaviors (AN-P or BN), and a similar percent of adolescents and adults had the diagnosis of either AN-P or EDNOS see . There wof DSM-5 , the diaof DSM-5 , would hSD = 15.1) and for all adults was 35.3 days (SD = 24.9); thus, treatment stays were, on average, 12 days longer for adolescents than adults.Also in Both adolescents and adults, across ED diagnoses, were admitted to residential treatment with similarly impaired presentations of global functioning—that is, had average GAF scores in the mid-30s (indicating “major impairment”) with a range of 10–61 see , 3. Uponn = 726), 89.1% were able to completely cease purging while in treatment.Whereas the patients diagnosed with AN-R, unsurprisingly, had relatively few purge episodes on admission  of adults and adolescents diagnosed with AN who were admitted with weight that was below 85% of their minimum TBW and who remained in treatment for 7 or more days  for patients who needed weight restoration upon admission, adolescent and adult patients gained 2.0 and 2.1 lb/week, respectively; (2) of patients who reported purge behavior the month before admission, 89.1% were able to completely cease purging while in treatment; (3) although improvement of approximately 10 mean GAF points was made during treatment, patients were still quite impaired at discharge; and (4) mean length of stay was 12 days longer for adolescents than adults, and 10–15 days longer for patients diagnosed with anorexia compared to bulimia or EDNOS, respectively.Prior to this paper, there have been eight studies in the literature that have reported discharge outcomes on a total of 1,157 patients treated for EDs in residential facilities. Those 1,157 patients represented less than 65% of the patients treated during those studies . The addition of the 1,421 patients in the current study more than doubles the total number of patients with outcomes treated in ED residential facilities reported in the literature. Furthermore, because this study includes data on 96% of patients treated during the study period, it represents a significant increase from the aggregate percentage of data available in previous studies.The clear majority (96.9%) of the patients in this study had received ED treatment prior to their admission to Center For Discovery—over 80% had prior outpatient and almost half had prior hospitalization. Such a high percentage of patients having past treatment is typical for this level-of-care . As prioMost patients in this study were diagnosed with AN, followed by BN, and then EDNOS. Examining the other residential outcome studies, AN is the most common of the EDs treated in residential care. However, some studies showed a higher prevalence of patients diagnosed with EDNOS than BN . The finAlthough GAF scores improved over the course of treatment, the means increased from the mid-30s—“major impairment”—on admission to the mid-40s—“serious symptoms”—on discharge, with adolescents scoring slightly higher (showing less impairment) than adults on discharge. GAF scores have not been retained in the DSM-5 because of a “conceptual lack of clarity… and questionable psychometrics in routine practice” , p. 16. n = 456) reported purging equivalent to a mean of 3.7 times per day on admission and the patients diagnosed with AN-P (n = 184) reported equivalent to a mean of 3.2 times per day. Both groups reported virtually no purging at time of discharge . Looking at all patients who had purging behavior on admission and purge data on discharge (n = 726), almost 90% were able to completely cease purging while in treatment.Among the patients with purging behaviors on admission, the patients diagnosed with BN (n = 686) had a mean increase in BMI of 2.1 and a mean length of stay of 53.7 days. Examining just the patients diagnosed with AN who met DSM-IV-TR (n = 411), the mean BMI increase was 2.6 points and the mean length of stay was 55.8 days. This increase is higher than findings reported by the other residential ED treatment programs included in The patients treated for AN (SM-IV-TR  diagnost1-year treatment period (The change in BMI in the patients diagnosed with AN represents a mean weight gain of approximately 12.4 lb (1.7 lb per week) and an increase of approximately 10% TBW, from 82.8 to 93.0% TBW. For the subset of these patients who met DSM-IV-TR diagnostic criteria on admission , the BMIt period . Thus, at period . And altAdolescent and adult patients varied in almost all domains examined: prior treatment, most prevalent diagnosis, length of treatment received, and symptom improvement. Higher percentages of adults had received levels-of-care that fall in the middle of the continuum; whereas, a higher percentage of adolescents had been hospitalized previously. Adolescents were more often diagnosed with AN, whereas adults were more often diagnosed with BN. Adolescents received more days of treatment than adults—12.5 days more on average; this may be because the adults were less willing to stay as long and/or because insurance companies authorized shorter treatment lengths for adults. Adolescents had more favorable outcomes (though some only slightly more favorable) than adult patients in terms of GAF scores, purging frequency, and weight gain. Notably, adolescents, but not adults, diagnosed with AN were able to weight restore to above an average of 90% TBW. Reaching the benchmark of 90% TBW, particularly for developing adolescents, is important for a number of reasons including: (a) at 90% TBW there is often a marked reduction of symptoms of malnutrition ; (b) eviIn summary, the data in this study answer the call presented by The dataset generated for this study is available for review on request to the corresponding author.This study was reviewed and approved by the IRB of Northwell Health. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.MF oversaw the analysis and writing. JH and SC were responsible for research design, oversaw data collection and de-identifying, and participated in the writing. RF, VF, LM, and JM supported the analysis, participated in the interpretation, and reviewed the manuscript. MS and SL contributed to data collection and reviewed the manuscript. JF cleaned and coded the data and ran analyses.JH, SC, RF, MS, and SL were or are employed by Center For Discovery.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.