Effect of depressive symptoms on the length of hospital stay among patients hospitalized for acute stroke in Japan

Development of predictive model for post-stroke depression at discharge based on decision tree algorithm: A multi-center hospital-based cohort study

OBJECTIVE

Post-stroke depression (PSD) is one of the most common and severe neuropsychological sequelae after stroke. Using a prediction model composed of multiple predictors may be more beneficial than verifying the predictive performance of any single predictor. The primary objective of this study was to construct practical prediction tools for PSD at discharge utilizing a decision tree (DT) algorithm.

METHODS

A multi-center prospective cohort study was conducted from May 2018 to October 2019 and stroke patients within seven days of onset were consecutively recruited. The independent predictors of PSD at discharge were identified through multivariate logistic regression with backward elimination. Classification and regression tree (CART) algorithm was employed as the DT model's splitting method.

RESULTS

A total of 876 stroke patients who were discharged from the neurology departments of three large general Class A tertiary hospitals in Wuhan were eligible for analysis. Firstly, we divided these 876 patients into PSD and non-PSD groups, history of coronary heart disease (OR = 1.835; 95 % CI, 1.106-3.046; P = 0.019), length of hospital stay (OR = 1.040; 95 % CI, 1.013-1.069; P = 0.001), NIHSS score (OR = 1.124; 95 % CI, 1.052-1.201; P = 0.001), and Mini mental state examination (MMSE) score (OR = 0.935; 95 % CI, 0.893-0.978; P = 0.004) were significant predictors. The subgroup analysis results have shown that hemorrhagic stroke, history of hypertension and higher modified Rankin Scale score (mRS) score were associated with PSD at discharge in the young adult stroke patients.

CONCLUSIONS

Several predictors of PSD at discharge were identified and convenient DT models were constructed to facilitate clinical decision-making.

Does Self-Reported BMI Modify the Association Between Stroke and Depressive Symptoms?

BACKGROUND

Depressive symptoms are common in stroke survivors. While obesity has been associated with stroke and depression, its influence on the association between stroke and depressive symptoms is unknown.

METHODS

Cross-sectional data from 2015 to 2016 Canadian Community Health Survey was used. History of stroke was self-reported and our outcome of interest was depressive symptoms in the prior 2 weeks, measured using the 9-item Patient Health Questionnaire. Self-reported body mass index (BMI) was modeled as cubic spline terms to allow for nonlinear associations. We used multivariable logistic regression to evaluate the association between stroke and depressive symptoms and added an interaction term to evaluate the modifying effect of BMI.

RESULTS

Of the 47,521 participants, 694 (1.0%) had a stroke and 3314 (6.5%) had depressive symptoms. Those with stroke had a higher odds of depressive symptoms than those without (aOR = 3.13, 95% CI 2.48, 3.93). BMI did not modify the stroke-depressive symptoms association (P interaction = 0.242) despite the observed variation in stroke-depressive symptoms association across BMI categories,: normal BMI [18.5-25 kg/m2] (aOR† = 3.91, 95% CI 2.45, 6.11), overweight [25-30 kg/m2] (aOR† = 2.63, 95% CI 1.58, 4.20), and obese [>30 kg/m2] (aOR† = 2.76, 95% CI 1.92, 3.94). Similar results were found when depressive symptoms were modeled as a continuous measure.

CONCLUSION

The association between stroke and depressive symptoms is not modified by BMI, needing additional work to understand the role of obesity on depression after stroke.

Attempted Suicide Is Independently Associated with Increased In-Hospital Mortality and Hospital Length of Stay among Injured Patients at Community Tertiary Hospital in Japan: A Retrospective Study with Propensity Score Matching Analysis

Suicide is an increasingly important public healthcare concern worldwide. Studies examining the effect of attempted suicide on clinical outcomes among patients with trauma are scarce. We conducted a retrospective cohort study at a community emergency department in Japan. We included all severely injured patients with an Injury Severity Score > 15 from January 2002 to December 2021. The primary outcome measure was in-hospital mortality. The other outcome of interest was hospital length of stay. One-to-one propensity score matching was performed to compare these outcomes between suicide attempt and no suicide attempt groups. Of the 2714 eligible patients, 183 (6.7%) had trauma caused by a suicide attempt. In the propensity score-matched analysis with 139 pairs, the suicide attempt group showed a significant increase in-hospital mortality (20.9% vs. 37.4%; odds ratio 2.27; 95% confidence intervals 1.33-3.87) compared with the no suicide attempt group. Among survivors, the median hospital length of stay was significantly longer in the suicide attempt group than that in the no suicide attempt group (9 days vs. 12 days, p = 0.0076). Because of the unfavorable consequences and potential need for additional healthcare, increased attention should be paid to patients with trauma caused by a suicide attempt.

Comparison of outcomes for patients with and without a serious mental illness presenting to hospital for chronic obstruction pulmonary disease: retrospective observational study using administrative data

BACKGROUND

There are few data on the profile of those with serious mental illness (SMI) admitted to hospital for physical health reasons.

AIMS

To compare outcomes for patients with and without an SMI admitted to hospital in England where the primary reason for admission was chronic obstructive pulmonary disease (COPD).

METHOD

This was a retrospective, observational analysis of the English Hospital Episodes Statistics data-set for the period from 1 April 2018 to 31 March 2019, for patients aged 18-74 years with COPD as the dominant reason for admission. Patient with an SMI (psychosis spectrum disorder, bipolar disorder) were identified.

RESULTS

Data were available for 54 578 patients, of whom 2096 (3.8%) had an SMI. Patients with an SMI were younger, more likely to be female and more likely to live in deprived areas than those without an SMI. The burden of comorbidity was similar between the two groups. After adjusting for covariates, SMI was associated with significantly greater risk of length of stay than the median (odds ratio 1.24, 95% CI 1.12-1.37, P ≤ 0.001) and with 30-day emergency readmission (odds ratio 1.51, 95% confidence interval 1.34-1.69, P ≤ 0.001) but not with in-hospital mortality.

CONCLUSION

Clinicians should be aware of the potential for poorer outcomes in patients with an SMI even when the SMI is not the primary reason for admission. Collaborative working across mental and physical healthcare provision may facilitate improved outcomes for people with SMI.

Risk factor identification and prediction models for prolonged length of stay in hospital after acute ischemic stroke using artificial neural networks

Background

Accurate estimation of prolonged length of hospital stay after acute ischemic stroke provides crucial information on medical expenditure and subsequent disposition. This study used artificial neural networks to identify risk factors and build prediction models for a prolonged length of stay based on parameters at the time of hospitalization.

Methods

We retrieved the medical records of patients who received acute ischemic stroke diagnoses and were treated at a stroke center between January 2016 and June 2020, and a retrospective analysis of these data was performed. Prolonged length of stay was defined as a hospital stay longer than the median number of days. We applied artificial neural networks to derive prediction models using parameters associated with the length of stay that was collected at admission, and a sensitivity analysis was performed to assess the effect of each predictor. We applied 5-fold cross-validation and used the validation set to evaluate the classification performance of the artificial neural network models.

Results

Overall, 2,240 patients were enrolled in this study. The median length of hospital stay was 9 days. A total of 1,101 patients (49.2%) had a prolonged hospital stay. A prolonged length of stay is associated with worse neurological outcomes at discharge. Univariate analysis identified 14 baseline parameters associated with prolonged length of stay, and with these parameters as input, the artificial neural network model achieved training and validation areas under the curve of 0.808 and 0.788, respectively. The mean accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of prediction models were 74.5, 74.9, 74.2, 75.2, and 73.9%, respectively. The key factors associated with prolonged length of stay were National Institutes of Health Stroke Scale scores at admission, atrial fibrillation, receiving thrombolytic therapy, history of hypertension, diabetes, and previous stroke.

Conclusion

The artificial neural network model achieved adequate discriminative power for predicting prolonged length of stay after acute ischemic stroke and identified crucial factors associated with a prolonged hospital stay. The proposed model can assist in clinically assessing the risk of prolonged hospitalization, informing decision-making, and developing individualized medical care plans for patients with acute ischemic stroke.

The efficacy of therapist-supported acceptance and commitment therapy-based bibliotherapy for psychological distress after stroke: a single-case multiple-baseline study

BACKGROUND

Psychological distress is common after stroke, and affects recovery. However, there are few evidence-based psychological treatments. This study evaluates a bibliotherapy-based approach to its amelioration.

AIMS

To investigate a stroke-specific self-management book, based on acceptance and commitment therapy (ACT), as a therapist-supported intervention for psychological distress after stroke.

METHOD

The design was a single case, randomised non-concurrent multiple-baseline design (MBD). Sixteen stroke survivors, eight males and eight females (mean age 60.6 years), participated in an MBD with three phases: A (randomised-duration baseline); B (intervention); and follow-up (at 3 weeks). During the baseline, participants received therapist contact only. In the bibliotherapy intervention, participants received bi-weekly therapist support. The primary measures of psychological distress (General Health Questionaire-12; GHQ-12) and quality of life (Satisfaction with Life Scale; SWLS) were completed weekly. Secondary measures of mood, wellbeing and illness impact were completed pre- and post-intervention.

RESULTS

Omnibus whole-group TAU-U analysis was statistically significant for each primary measure with a moderate effect size on both (0.6 and 0.3 for GHQ-12 and SWLS, respectively). Individual TAU-U analyses demonstrated that the majority of individuals exhibited positive change. All the secondary measures showed significant pre-post improvements. Eighty-one per cent of participants reported the book was helpful and 81% also found the ACT-based sections helpful. Relative risk calculations showed finding the book helpful was associated with improvement in GHQ-12 and SWLS scores.

CONCLUSIONS

ACT-based bibliotherapy, with therapist support, is a promising intervention for psychological difficulties after stroke.

Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females

BACKGROUND

Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. The occurrence, development and prognosis of PSD have long been different between males and females. The main purpose of this study was to explore the influencing factors of PSD at 3 months in males and females, and construct random forest (RF) models to rank the influencing factors.

METHODS

This is a prospective multicenter cohort study (Registration number: ChiCTR-ROC-17013993). Stroke patients hospitalized in the department of Neurology of three hospitals in Wuhan were enrolled from May 2018 to August 2019. Scale assessments were performed 24 hours after admission and 3 months after stroke onset. Binary logistic regression analysis was used for univariate and multivariate (stepwise backward method) analysis, when p was less than 0.05, the difference between groups was considered statistically significant. Lastly, the RF models were constructed according to the results of multivariate regression analysis.

RESULTS

This study found that several baseline variables were associated with PSD at 3 months in males and females. RF model ranked them as stroke severity (OR [odds ratio] =1.17, p < 0.001, 95%CI [confidence interval]:1.11-1.24), neuroticism dimension (OR = 1.06, p = 0.002, 95%CI:1.02-1.10), physical exercise (OR = 0.62, p = 0.007, 95%CI:0.44-0.88), sleeping time < 5 h (OR = 1.91, p = 0.006, 95% CI:1.20-3.04) and atrial fibrillation (OR = 4.18, p = 0.012, 95%CI:1.38-12.68) in males. In females, RF model ranked them as psychological resilience (OR = 0.98, p = 0.015, 95%CI:0.96-1.00), ability of daily living (OR = 0.98, p = 0.001, 95%CI:0.97-0.99), neuroticism dimension (OR = 1.11, p = 0.002, 95%CI:1.04-1.18) and subjective support (OR = 1.11, p < 0.001, 95%CI:1.05-1.78).

CONCLUSION

The study found influencing factors of PSD at 3 months were different in males and females, and construct RF models to rank them according to their importance. This suggests that clinicians should focus their interventions on sex-specific influencing factors in order to improve the prognosis of PSD patients.

TRIAL REGISTRATION

ChiCTR-ROC-17013993.

tDCS over the left prefrontal Cortex improves mental flexibility and inhibition in geriatric inpatients with symptoms of depression or anxiety: A pilot randomized controlled trial

BACKGROUND

Patients with depression and/or anxiety are commonly seen in inpatient geriatric settings. Both disorders are associated with an increased risk of cognitive impairments, notably in executive functioning. Transcranial direct current stimulation (tDCS), a type of non-invasive brain stimulation, involves the administration of a low-dose electrical current to induce neuromodulation, which ultimately may act on downstream cognitive processing.

OBJECTIVE

The purpose of this study was to determine the effects of tDCS on executive functioning in geriatric inpatients with symptoms of depression and/or anxiety.

DESIGN

Pilot Randomized Controlled Trial.

SETTING

Specialized geriatric wards in a tertiary rehabilitation hospital.

METHODS

Thirty older-aged adults were recruited, of which twenty completed ten-to-fifteen sessions of 1.5 mA anodal or sham tDCS over the left dorsolateral prefrontal cortex. Cognitive assessments were administered at baseline and following the tDCS protocol; analyses examined the effects of tDCS on cognitive performance between groups (anodal or sham tDCS).

RESULTS

tDCS was found to increase inhibitory processing and cognitive flexibility in the anodal tDCS group, with significant changes on the Stroop test and Trail Making Test-Part B. No significant changes were observed on measures of attention or working memory.

DISCUSSION

These results provide preliminary evidence that tDCS-induced neuromodulation may selectively improve cognitive processing in older adults with symptoms of depression and/or anxiety.

CLINICAL TRIALS REGISTRATION

www.clinicaltrials.gov, NCT04558177.

International PRISMA scoping review to understand mental health interventions for depression in COVID-19 patients

Preliminary research indicates that the COVID-19 illness affects the mental well-being of patients. This scoping review, thus, aims to examine the current state of research into mental health treatments for depression symptoms in COVID-19 patients. Select databases were searched on 7/1/2021. Full-text articles involved (1) mental health treatment (2) suicide and/or depression outcomes, (3) a quasi-experimental research trial, and (4) a primary analysis. 11 articles were included in this review. The studies spanned 5 countries, and demonstrated immediate positive effects of mental health treatments and tele-health as a treatment modality for depression in COVID-19 patients. 6 studies were randomized controlled trials. Various treatments were administered, including cognitive behavior therapy, mindfulness, and muscle relaxation. Most interventions were conducted in in-patient units and focused on acute symptoms. There were limitations in the design and description of methodology in many studies, which affects the generalizability and replicability of positive findings. Only two studies included a post-intervention follow-up and one study assessed suicide risk. Thus, this review found there is a pressing need for more research in the area, with greater rigor in study methodology, and for treatments targeting long-term symptoms and suicidality, and outpatient services.

Higher Serum Lactic Dehydrogenase is Associated with Post-Stroke Depression at Discharge

Purpose

Post-stroke depression (PSD) is one of the most common and severe psychological sequelae after stroke, negatively affecting the patient’s functional outcome and quality of life. Rapidly measurable biomarkers to predict PSD are pivotal for the optimized care and allocation of healthcare resources. Lactic dehydrogenase (LDH) levels are increased in patients with central nervous system (CNS) disorders such as cerebral infarction and hypoxic–ischemic encephalopathy, which may be related to the occurrence of PSD in acute ischemic stroke (AIS) patients. This study aimed to investigate whether LDH levels on admission are associated with PSD at discharge.

Patients and Methods

A multicenter prospective cohort study was conducted, including all consecutive AIS patients within 7 days after symptom onset from May 2018 to October 2019. According to the distribution of LDH and the number of patients, patients were divided into equal tertiles. PSD was evaluated by DSM-V criteria and the 17-item Hamilton Rating Scale for Depression (HRSD-17) at discharge.

Results

A total of 518 AIS patients were included. The optimal cut-off points of LDH were: lowest tertile (T1) 102–159/L, middle tertile (T2) 160–189 U/L, and upper tertile (T3) 190–520 U/L. A total of 249 patients (48.07%) were diagnosed with PSD at discharge. After adjusting for potential confounding factors, the odds ratio of T3 PSD was 1.698 (95% CI, 1.070–2.694, P=0.025), compared with T1.

Conclusion

In summary, LDH serum levels on admission are associated with PSD at discharge. Clinicians should pay more attention to the baseline LDH level in screening for PSD at discharge.

Factors Affecting Post-Stroke Depression in Acute Ischemic Stroke Patients after 3 Months

Post-stroke depression (PSD) affects approximately one-third of stroke patients. PSD not only impairs recovery and lowers quality of life, but has also serious neurological consequences, high mortality, and stroke recurrence risks. Studies on PSD-related prognostic factors are still lacking, especially environmental factors. Moreover, relieving factors after PSD in stroke patients has not been reported. This study aimed to investigate (study design 1) risk factors for PSD diagnosis after three months, and (study design 2) related factors for the relieving of early PSD after three months. This retrospective study included 227 patients hospitalized for acute ischemic stroke within three days at Jeonbuk National University Hospital from January to December 2019. The depressive status was assessed using the Hamilton Depression Rating Scale (HDRS) at admission and after three months. Clinical and laboratory data were analyzed for relevant prognostic factors. (Study design 1) HDRS score at admission (adjusted odds ratio (aOR) 1.22, 95% confidence interval (CI) 1.14–1.31; p < 0.001) and hospitalization period (aOR 1.11, 95% CI 1.02–1.20; p = 0.013) were confirmed as prognostic factors of PSD after three months. (Study design 2) The National Institute of Health Stroke Scale (NIHSS) score at discharge (aOR 0.80, 95% CI 0.68–0.94; p = 0.006) and HDRS score at admission (aOR 0.80, 95% CI 0.71–0.89; p < 0.001) were confirmed as prognostic factors of depression improvement after three months. In conclusion, environmental factors such as hospitalization period could be important in managing PSD. Factors related to PSD improvement are expected to be helpful in establishing a strategy for PSD recovery.

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression

BACKGROUND

Post-stroke depression (PSD) is a major complication in stroke survivors, especially in elderly stroke survivors. But there are still no objective methods to diagnose depression in elderly stroke survivors. Thus, this study was conducted to identify potential biomarkers for diagnosing elderly PSD subjects.

METHODS

Elderly (60 years or older) stroke survivors with depression were assigned into the PSD group, and elderly stroke survivors without depression and elderly healthy controls (HCs) were assigned into the non-depressed group. Urinary metabolite signatures obtained from gas chromatography-mass spectrometry (GC-MS)-based metabolomic platform were collected. Both univariate and multivariate statistical analysis were used to find the differential urinary metabolites between the two groups.

RESULTS

The 78 elderly HCs, 122 elderly stroke survivors without depression and 124 elderly PSD subjects were included. A set of 13 differential urinary metabolites responsible for distinguishing PSD subjects from non-depressed subjects were found. The Phenylalanine, tyrosine and tryptophan biosynthesis, Phenylalanine metabolism and Galactose metabolism were found to be significantly changed in elderly PSD subjects. The phenylalanine was significantly negatively correlated with age and depressive symptoms. Meanwhile, a biomarker panel consisting of 3-hydroxyphenylacetic acid, tyrosine, phenylalanine, sucrose, palmitic acid, glyceric acid, azelaic acid and α-aminobutyric acid was identified.

CONCLUSION

These results provided candidate molecules for developing objective methods to diagnose depression in elderly stroke survivors, suggested that taking supplements of phenylalanine might be an effective method to prevent depression in elderly stroke survivors, and would be helpful for future revealing the pathophysiological mechanism of PSD.

Role of functional pharmacological therapy in post-stroke depression: a narrative review

Objective

We conducted a narrative review to investigate whether antidepressant therapy, including the use of selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs) or the use of supportive drugs (i.e., citicoline or choline alfoscerate) as a substitute for antidepressant therapy, reduces depression in patients with cerebrovascular diseases.

Methods

A systematic search of the PubMed and Web of Science databases was performed, including review articles and other studies to identify additional citations. Only 4 of 1566 publications met the inclusion/exclusion criteria and were selected.

Results

Studies showed that post-stroke depression (PSD) could be treated with antidepressant therapy, as well as supportive drugs such as citicoline or choline alfoscerate, which may have antidepressant effects.

Conclusions

The findings support the efficacy of citicoline as a treatment for depression. Studies aimed to discover the characteristics of these psychostimulants in relation to PSD treatment should be performed.

Nurses' Late-Life Depression Knowledge and Attitudes Toward Depression: A Cross-Sectional Study

Depression in older population is more common now. Due to increasing numbers of older patients in hospitals, nurses have more opportunities to care for these patients. Therefore, nurses should have correct knowledge of late-life depression and more favorable attitudes about depression. The study aimed to understand hospital nurses' knowledge level of late-life depression and attitudes about depression. A cross-sectional research design was used. A convenience sample of 307 nurses from 3 hospitals in Taiwan was recruited. Nurses scored 55.15% in the Late-Life Depression Quiz. The average score of the Revised Depression Attitude Questionnaire was 71.76 (SD = 6.13). The study also found that hospital nurses had more favorable attitudes about depression when their late-life depression knowledge was higher; their interest level in providing care for older patients with depression was greater; they had ever taken care of older patients with depressive symptoms or depression; they had never received in-service training on depression in the past year; and they had ever attended lectures about depression in school. Hospital nurses' knowledge about late-life depression was limited, and they had neutral to slightly favorable attitudes about depression in Taiwan. It is suggested to carefully examine and evaluate in-service training related to depression for nurses in hospitals. In addition, developing appropriate interventions to increase hospital nurses' knowledge level of late-life depression and attitudes toward depression is recommended.

The validity and reliability of the PHQ-9 in screening for post-stroke depression

BACKGROUND

Depression affects about 30% of stroke survivors within 5 years. Timely diagnosis and management of post-stroke depression facilitate motor recovery and improve independence. The original version of the Patient Health Questionnaire-9 (PHQ-9) is recognized as a good screening tool for post-stroke depression. However, no validation studies have been undertaken for the use of the Thai PHQ-9 in screening for depression among Thai stroke patients.

METHODS

The objectives were to determine the criterion validity and reliability of the Thai PHQ-9 in screening for post-stroke depression by comparing its results with those of a psychiatric interview as the gold standard. First-ever stroke patients aged ≥45 years with a stroke duration 2 weeks-2 years were administered the Thai PHQ-9. The gold standard was a psychiatric interview leading to a DSM-5 diagnosis of depressive disorder and adjustment disorder with a depressed mood. The summed-scored-based diagnosis of depression with the PHQ-9 was obtained. Validity and reliability analyses, and a receiver operating characteristic curve analysis, were performed.

RESULTS

In all, 115 stroke patients with a mean age of 64 years (SD: 10 years) were enrolled. The mean PHQ-9 score was 5.2 (SD: 4.8). Using the DSM-5 criteria, 11 patients (9.6%) were diagnosed with depressive disorder, 12 patients (10.5%) were diagnosed with adjustment disorder with a depressed mood. Both disorders were combined as a group of post-stroke depression. The Thai PHQ-9 had satisfactory internal consistency (Cronbach's alpha: 0.78). The algorithm-based diagnosis of the Thai PHQ-9 had low sensitivity (0.52) but very high specificity (0.94) and positive likelihood ratio (9.6). Used as a summed-scored-based diagnosis, an optimal cut-off score of six revealed a sensitivity of 0.87, specificity of 0.75, positive predictive value of 0.46, negative predictive value of 0.95, and positive likelihood ratio of 3.5. The area under the curve was 0.87 (95% CI: 0.78-0.96).

CONCLUSIONS

The Thai PHQ-9 has acceptable psychometric properties for detecting a mixture of major depression and adjustment disorder in post-stroke patients, with a recommended cut-off score of ≥6 for a Thai population.

Identification of Potential Metabolite Markers for Middle-Aged Patients with Post-Stroke Depression Using Urine Metabolomics

BACKGROUND

Post-stroke depression (PSD) is one of the most common complications in stroke survivors. But, there are still no objective methods to diagnose PSD. This study aims to identify potential biomarkers for diagnosing PSD in middle-aged stroke survivors.

METHODS

Middle-aged subjects aged 30 to 59 years (92 PSD patients and 89 stroke survivors without depression) were included in this study. Urinary metabolites were detected by gas chromatography-mass spectrometry (GC-MS). Differential urinary metabolites and potential biomarkers were screened by applying statistical analysis.

RESULTS

The different urinary metabolic phenotypes between PSD patients and stroke survivors without depression were identified. A total of 12 differential urinary metabolites were accurately identified by using orthogonal partial least-squares-discriminant analysis. After analyzing those 12 differential urinary metabolites by step-wise logistic regression analysis, only seven metabolites (palmitic acid, hydroxylamine, myristic acid, glyceric acid, lactic acid, tyrosine and azelaic acid) were finally selected as potential biomarkers for diagnosing PSD in middle-aged stroke survivors. A panel consisting of these potential biomarkers could effectively diagnose middle-aged PSD patients.

CONCLUSION

Urinary metabolic profiles were different between middle-aged PSD patients and stroke survivors without depression. Our results would be helpful in future for developing an objective method to diagnose PSD in middle-aged stroke survivors.

Prediction of life-space mobility in patients with stroke 2 months after discharge from rehabilitation: a retrospective cohort study

Purpose: To determine the predictors of life-space mobility among patients with stroke 2 months after discharge from a post-acute rehabilitation unit.Materials and methods: The study population was 1023 patients discharged from a post-acute rehabilitation unit in Japan. We assessed the relationships between life-space mobility 2 months after discharge and age, sex, length of hospital stay, cognition and motor function (Functional Independence Measure), severity of hemiparesis, falls efficacy, physical function (Timed Up and Go (TUG) test), walking distance ability and social support from family and friends.Results: Bivariate and multiple regression analyses showed that life-space mobility was predicted by sex, age, cognitive score at discharge, TUG score <15 s, length of hospital stay and falls efficacy at discharge. Taken together, these factors accounted for 54% of the variability in life-space mobility. A predictive formula was determined for clinical use.Conclusions: The predictive formula provides an objective measure of life-space mobility for stroke patients after discharge. The clinical application of this formula could help health care professionals working in stroke rehabilitation to prepare patients for discharge and to set concrete goals for in-hospital rehabilitation to improve life-space mobility after discharge.Implications for rehabilitationAccurate prediction of the prognosis for life-space mobility 2 months after discharge is useful in establishing clear goals for community-based rehabilitation.Long-term life-space mobility in the community is not only affected by physical function, but also by sex, age, cognitive ability and falls efficacy at discharge.Life-space mobility in female patients is affected by factors reflecting physical function, whereas life-space mobility in male patients is affected by both physical and cognitive function.Prediction of life-space mobility after stroke is important to determine unique mobility goals in rehabilitation and the required use of adaptive equipment after discharge (e.g., returning to work, engaging in a hobby or travelling beyond the immediate neighbourhood).

Poststroke Depression Biomarkers: A Narrative Review

Poststroke depression (PSD) is the most prevalent psychiatric disorder after stroke, which is independently correlated with negative clinical outcome. The identification of specific biomarkers could help to increase the sensitivity of PSD diagnosis and elucidate its pathophysiological mechanisms. The aim of current study was to review and summarize literature exploring potential biomarkers for PSD diagnosis. The PubMed database was searched for papers published in English from October 1977 to December 2017, 90 of which met inclusion criteria for clinical studies related to PSD biomarkers. PSD biomarkers were subdivided into neuroimaging, molecular, and neurophysiological. Some of them could be recommended to support PSD diagnosing. According to the data, lesions affecting the frontal-subcortical circles of mood regulation (prefrontal cortex, basal nuclei, and thalamus) predominantly in the left hemisphere can be considered as neuroimaging markers and predictors for PSD for at least 1 year after stroke. Additional pontine and lobar cerebral microbleeds in acute stroke patients, as well as severe microvascular lesions of the brain, increase the likelihood of PSD. The following molecular candidates can help to differentiate PSD patients from non-depressed stroke subjects: decreased serum BDNF concentrations; increased early markers of inflammation (high-sensitivity C-reactive protein, ferritin, neopterin, and glutamate), serum pro-inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-18, IFN-γ), as well as pro-inflammatory/anti-inflammatory ratios (TNF-α/IL-10, IL-1β/IL-10, IL-6/IL-10, IL-18/IL-10, IFN-γ/IL-10); lowered complement expression; decreased serum vitamin D levels; hypercortisolemia and blunted cortisol awakening response; S/S 5-HTTLPR, STin2 9/12, and 12/12 genotypes of the serotonin transporter gene SLC6A4, 5-HTR2a 1438 A/A, and BDNF met/met genotypes; higher SLC6A4 promoter and BDNF promoter methylation status. Neurophysiological markers of PSD, that reflect a violation of perception and cognitive processing, are the elongation of the latency of N200, P300, and N400, as well as the decrease in the P300 and N400 amplitude of the event-related potentials. The selected panel of biomarkers may be useful for paraclinical underpinning of PSD diagnosis, clarifying various aspects of its multifactorial pathogenesis, optimizing therapeutic interventions, and assessing treatment effectiveness.

Hospital length of stay variation and comorbidity of mental illness: a retrospective study of five common chronic medical conditions

BACKGROUND

With the increasing burden of mental illness globally, it is becoming common for hospitalised patients with chronic medical conditions to have a comorbidity of mental illness. This combination could prolong length of stay (LOS) of this patient cohort. We conducted an investigation in Tasmania, Australian hospitals to characterise this cohort and assess if co-morbidity of mental illness is a distinguishing factor that generates LOS variation across different chronic medical conditions.

METHODS

The retrospective study analysed 16,898 admissions of patients with a primary diagnosis of one of five chronic medical conditions: lung or colorectal cancer, chronic obstructive pulmonary disease (COPD), type II diabetes, ischaemic heart disease (IHD) and stroke. Data were from July 2010 to June 2015, across four hospitals that collectively cover 95% of public hospital admissions in Tasmania, Australia. Descriptive statistics were used to compare characteristics of patients between the scenarios of with and without co-morbidity of mental illness. We used negative binomial regression models to assess whether co-morbidity of mental illness, along with its sub-types, after adjustment for potential confounding variables, associated with LOS variation in patients of each medical condition. Based on the adjusted LOS variation, we estimated differences in bed days' use between patients with and without comorbidity of mental illness.

RESULTS

Patients with co-morbidity of mental illness were significantly younger in comparison to patients without mental illness. With each medical condition, patients with comorbidity of mental illness had incurred higher bed days' use than for those without mental illness. In cancer and stroke cohorts, co-morbidity of mental illness unfavourably affected the LOS variation by as high as 97% (CI: 49.9%-159%) and 109% (78%-146%), respectively. Though mental and behavioural disorders due to psychoactive substances was a dominant sub-type of mental illness across the medical conditions, it contributed significant unfavourable LOS variation only in the stroke patients i.e. 36.3% (CI: 16.2%-59.9%).

CONCLUSIONS

Mental illness consistently produced unfavourable LOS variation. Upskilling of healthcare teams and greater reporting and analysis of LOS variation for this patient cohort, and the sub-cohorts within it, are necessary to provide improved medical care and achieve system efficiencies.

Acute Poststroke Depression Is Associated with Thalamic Lesions and Clinical Outcomes: A Case-Control Study

BACKGROUND

We investigated the role of acute-phase stroke lesions and patient characteristics in poststroke depression (PSD) and its effect on the clinical outcome.

PATIENTS AND METHODS

Five and 30 days after admission, 175 patients self-reported their depressive symptoms on the Patient Health Questionnaire-9. We compared the clinical characteristics and outcomes in patients with (n = 41) and without PSD (n = 134). Stroke severity was assessed with the National Institutes of Health Stroke Scale (NIHSS); the modified Rankin Scale (mRS) was used to determine the functional outcome.

RESULTS

There was no significant difference between patients with and without PSD in the age, gender ratio, lesion side, and the history of hypertension, diabetes mellitus, alcohol and tobacco use, and previous stroke. Thalamic lesions were significantly associated with PSD (P = .03), although there was no significant difference in both the NIHSS score and the final mRS score of patients with thalamic lesions. Backward stepwise logistic regression analysis showed that a higher NIHSS score and thalamic lesions were independent predictors of PSD. Total hospitalization was significantly longer in patients with PSD. At the time of admission, the NIHSS score was significantly higher in patients who developed moderate to severe PSD than in those with mild PSD or without PSD.

CONCLUSIONS

PSD in the acute phase was associated with thalamic lesions and severe stroke. Hospitalization was significantly longer in patients with PSD and their functional disability was more severe, suggesting that PSD played a role in the unsatisfactory results of poststroke rehabilitation.