scholarly journals ADMISSION VARIABLES ASSOCIATED WITH INDEPENDENT AMBULATION AT TIME OF DISCHARGE FROM A COMPREHENSIVE STROKE UNIT

2021 ◽  
Vol 74 (8) ◽  
pp. 1844-1849
Author(s):  
Yuriy Flomin ◽  
Vitaliy Hurianov ◽  
Larysa Sokolova
Keyword(s):  
Logistic Regression ◽  
Stroke Unit ◽  
Selection Criteria ◽  
Study Cohort ◽  
Univariate Logistic Regression Analysis ◽  
Study Selection ◽  
Point Increase ◽  
Stroke Type ◽  
Independent Ambulation ◽  
Admission Variables

The aim: To identify admission variables associated with Functional Ambulation Classification (FAC) 1 to 4 (unable to walk without assistance) at time of discharge (dFAC<5) from a comprehensive stroke unit (CSU). Materials and methods: Patients admitted to CSU at Oberig Clinic, Kyiv, Ukraine, August 01, 2012 to July 31, 2018, were screened for study selection criteria. Association of qualifying patients’ data with FAC score at CSU discharge was retrospectively assessed by univariate and multivariate logistic regression, odds ratios (OR) and 95% confidence intervals (95% CI) using MedCalc v. 19.1. Results: The study cohort (442 of 492 admitted patients) had median age: 65.8 years, gender: 43% female, stroke-type: 84% ischemic strokes, median baseline NIHSS total score: 10. Estimated time from stroke onset to CSU admission was from less-than-24-hours to over-180-days. The univariate logistic regression analysis, revealed 28 variables significantly (p<0.05) related to dFAC<5; while in multivariate analysis only 4 admission variables were significantly (p<0.05) associated with dFAC<5: age (OR= 1.07; 95% CI 1.03-1.10, on average, for each additional year, p<0.001), baseline NIHSS score (OR= 1.15; 95% CI 1.08-1.22, on average, with a 1-point increase in the total score, p<0.001), initial FAC score (OR= 0.40; 95% CI 0.31–0.52, on average, with a 1-point decrease in the score, p<0.001), and very late CSU admission (over 180 days; OR= 5.7; 95% CI 1.9–17.1, p=0.002). Conclusions: Four admission variables may be independently associated with dFAC<5 and provide opportunity for improving CSU outcomes and mitigating risk for inability to ambulate without assistance after CSU discharge.

Menopausal Symptoms Are Associated With Oral Sensory Complaints in Perimenopausal Women: An Observational Study

2021 ◽  
Author(s):  
Tomoharu Taga ◽  
Kayoko Ito ◽  
Kiyoshi Takamatsu ◽  
Mariko Ogawa ◽  
Saori Funayama ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Univariate Analysis ◽  
Menopausal Symptoms ◽  
Study Cohort ◽  
Tongue Coating ◽  
Taste Disturbance ◽  
Factors Associated ◽  
Oral Sensory ◽  
Perimenopausal Women ◽  
Burning Mouth

Abstract Background: Perimenopausal women experience a wide variety of systemic symptoms: hot flashes, sweating, psychiatric symptoms and various oral sensory complaints (OSC). OSC in perimenopausal women include xerostomia, taste disturbance and burning mouth. However, the factors associated with these OSC have not been identified. The purpose of this investigation was to elucidate the factors associated with OSC in perimenopausal women．Methods: The study cohort comprised 43 perimenopausal women aged 45–55 years. Data on medical history, medications, menstrual status, menopausal symptoms, xerostomia, taste disturbance and burning mouth were collected. Volumes of unstimulated and stimulated saliva were measured. Tongue coating was evaluated according to a tongue coating index. Univariate analysis was performed to identify factors significantly associated with having xerostomia, taste disturbance, burning mouth and more than two OSC (2OSC). Next, the factors strongly associated with these symptoms were examined by logistic regression analysis.Results: The number of menopausal symptoms was significantly higher, and volume of unstimulated saliva significantly lower in participants with xerostomia, taste disturbance, burning mouth or 2OSC than in those without these characteristics. Agents targeting the central nervous system were more frequently taken by participants with burning mouth and 2OSC than by those without these characteristics. According to logistic regression analysis, the number of menopausal symptoms was an explanatory variable for xerostomia, taste disturbance, burning mouth and 2OSC. Conclusions: Our findings suggested that OSC associated with the number of menopausal symptoms. Management of menopausal symptoms may decrease OSC, leading to improved quality of life of perimenopausal women.

Abstract 577: Long Pentraxin 3: A New, Independent Marker of Mortality in Acute Chest Pain

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Frederic Kontny ◽  
Trygve Brügger-Andersen ◽  
Harry Staines ◽  
Heidi Grundt ◽  
Kyoko Miyamoto ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Chest Pain ◽  
Clinical Outcome ◽  
Risk Measures ◽  
Acute Chest Pain ◽  
Study Cohort ◽  
Pentraxin 3 ◽  
All Cause Mortality ◽  
Independent Marker

Long Pentraxin 3 (PTX3) is a newly identified member of the Pentraxin protein family that includes C-reactive protein (CRP). Unlike CRP, PTX3 is produced by the major cell types involved in atherosclerotic lesions in response to inflammatory stimuli. Increased PTX3 levels are found in acute coronary syndromes (ACS). Its role in long-term prediction of clinical outcome is, however, unknown. The aim of the current study was to assess the predictive value of PTX3 concerning all-cause mortality in patients hospitalized for acute chest pain. Plasma PTX3 was measured with a new, high-sensitive ELISA method (PPMX, Tokyo, Japan) in blood samples taken on admission in 784 patients admitted for acute chest pain suggestive of ACS. The patients were followed for 24 months concerning clinical outcome. For statistical analysis, the study cohort was divided into quartiles according to PTX3 levels. A multiple logistic regression model was fitted to include standard risk measures. At 24 months follow-up 121 patients had died. By logistic regression, the odds Odds Ratio for death among patients with highest PTX3 levels was 3.13 as compared to those with lowest levels (p=0.007) (table). Long Pentraxin 3 is a new, independent marker that strongly predicts long-term all-cause mortality in patients with acute chest pain.

scholarly journals Embolic stroke of undetermined source: a retrospective analysis from an Italian Stroke Unit

2016 ◽  
Vol 10 (3) ◽  
pp. 202 ◽  
Author(s):  
Marco Masina ◽  
Annalena Cicognani ◽  
Carla Lofiego ◽  
Simona Malservisi ◽  
Riccardo Parlangeli ◽  
...  
Keyword(s):  
Stroke Unit ◽  
Cerebral Arteries ◽  
Real Life ◽  
Antiplatelet Agents ◽  
Embolic Stroke ◽  
Recurrence Rates ◽  
Stroke Type ◽  
Mean Time ◽  
Real Life Condition

The new clinical construct of embolic stroke of undetermined source (ESUS) suggests that many cryptogenic strokes are related to minor-risk covert embolic cardiac sources or to embolus from non-occlusive plaques in the aortic arch or in the cerebral arteries. The authors analyzed the prevalence of ESUS in a real-life condition in Italy and compared the recurrence rates in cryptogenic strokes, cardioembolic strokes, and ESUS. The authors retrospectively reassessed according to ESUS criteria 391 consecutive admissions in a stroke unit where extensive diagnostic search was routinely performed. Recurrences in each stroke type within a 3-year follow-up period (mean time: 25.44 months - standard deviation: 9.42) were also compared. The prevalence of ESUS in the aforementioned cohort was 10.5%. All ESUS patients received antiplatelet agents. Warfarin was prescribed in 56.9% of cardioembolic strokes. The recurrence rate in ESUS patients was 4.4% per year, slightly higher than in cardioembolic strokes (3.5%) and significantly higher than in cryptogenic non-ESUS (1.2%) (P&lt;0.0001). This is the first description of a cohort of ESUS patients in an Italian stroke unit. Patients with ESUS have a significantly higher risk of recurrence than in those with non-ESUS cryptogenic strokes, and slightly higher than in those with cardioembolic strokes. Results support the hypothesis of a more extensive diagnostic evaluation in cryptogenic strokes and the feasibility of such approach.

A Multiparametric Gene-Based Diagnosis Model for HNSCC

2008 ◽  
Vol 139 (2_suppl) ◽  
pp. P88-P89
Author(s):  
Maria J Worsham ◽  
Mei Lu ◽  
Seema Sethi ◽  
Alissa Kapke ◽  
Kang-Mei Chen ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Late Stage ◽  
Tumor Grade ◽  
Healthcare Setting ◽  
Classification And Regression Tree ◽  
Multivariate Logistic Regression Model ◽  
Study Cohort ◽  
Sample Type ◽  
Roc Curve Analysis ◽  
Clinical Variables

Problem A current shortcoming in the diagnosis, prognosis and treatment of HNSCC is a lack of methods that adequately addresses the complexity and diversity of the disease. Diagnostic and prognostic marker systems based on single parameters have generally proven inadequate. Multiparametric methods, which rely on many pieces of information, are ideally suited to the grouping of tumor subtypes, identification of specific patterns of disease progression, and in predicting clinical outcomes. Methods In a retrospective multi-ethnic primary HNSCC cohort drawn from a primary healthcare setting, and constructed through re-review of the primary biopsy, gene alterations (104 genes) and clinical variables (9 histopathology and 3 demographic variables) were evaluated as predictors of stage (TNM, early versus late). Statistical analysis compared logistic regression and Classification and Regression Tree (CART®) analyses to derive the most predictive model, assessed using receiver operating characteristic (ROC) curve analysis. Results Considering all clinical and gene variables for the 360 primary HNSCC study cohort, the multivariate logistic regression model retained only tumor grade, sample type (radical dissection) and their interaction with ROC as 64%. CART® generated a multivariable model with 12 variables: clinical variables of age, pattern of invasion, and tumor grade and gene variables of TP53, F3, TFF1, CDKN2A, KIAA0170, HS222808, TANK, MYC, and UTY1, with an ROC of 0.82%. Conclusion A group of clinical variables in multiparametric combinations with molecular alterations discriminated early and late stage HNSCC. CART® improved the model's performance. Significance Validation of this initial multiparametric strategy for predicting late stage HNSCC comprising several genes and clinical factors, currently underway, should yield a multiparametric, comprehensive genome-wide molecular algorithm integrated with clinical risk factors in order to refine HNSCC diagnosis and prognosis associated with clinical and pathological staging to aid in the clinical management of patients at the earliest stages. Support NIH R01 DE15990.

scholarly journals Predictors of Pharmaco-Resistance in Patients with Post-Stroke Epilepsy

2021 ◽  
Vol 11 (4) ◽  
pp. 418
Author(s):  
Simona Lattanzi ◽  
Claudia Rinaldi ◽  
Claudia Cagnetti ◽  
Nicoletta Foschi ◽  
Davide Norata ◽  
...  
Keyword(s):  
Status Epilepticus ◽  
Intracerebral Hemorrhage ◽  
Stroke Onset ◽  
Study Cohort ◽  
Seizure Freedom ◽  
Clinical Predictors ◽  
Post Stroke ◽  
History Of ◽  
Stroke Type ◽  
Patients With Epilepsy

Objectives: The study aimed to explore the clinical predictors of pharmaco-resistance in patients with post-stroke epilepsy (PSE). Methods: Patients with epilepsy secondary to cerebral infarct or spontaneous intracerebral hemorrhage were included. The study outcome was the occurrence of pharmaco-resistance defined as the failure of adequate trials of two tolerated and appropriately chosen and used antiseizure medication schedules, whether as monotherapies or in combination, to achieve sustained seizure freedom. Results: One-hundred and fifty-nine patients with PSE and a median follow-up of 5 (3–9) years were included. The mean age of the patients at stroke onset was 56.7 (14.9) years, and 104 (65.4%) were males. In the study cohort, 29 participants were pharmaco-resistant. Age at stroke onset [odds ratio (OR) 0.97, 95% confidence interval (CI) 0.93–0.99; p = 0.044], history of intracerebral hemorrhage (OR 2.95, 95% CI 1.06–8.24; p = 0.039), severe stroke (OR 5.43, 95% CI 1.82–16.16; p = 0.002), status epilepticus as initial presentation of PSE (OR 7.90, 1.66–37.55; p = 0.009), and focal to bilateral tonic-clonic seizures (OR 3.19, 95% CI 1.16–8.79; p = 0.025) were independent predictors of treatment refractoriness. Conclusions: Pharmaco-resistance developed in approximately 20% of patients with PSE and was associated with younger age at stroke onset, stroke type and severity, status epilepticus occurrence, and seizure types.

Changes Related To Inpatient Mortality From Acute Stroke In The Stroke Unit Of The Klaipeda University Hospital In 2007-2015

2016 ◽  
Vol 26 (5) ◽  
pp. 74-78
Author(s):  
Henrikas Kazlauskas ◽  
Elena Bovina ◽  
Geriuldas Žiliukas
Keyword(s):  
Acute Stroke ◽  
Odds Ratio ◽  
Stroke Unit ◽  
Hemorrhagic Stroke ◽  
Age Groups ◽  
University Hospital ◽  
Inpatient Mortality ◽  
Significant Difference ◽  
Icd 10 ◽  
Stroke Type

The aim of the study was to analyse the changes in inpatient mortality from acute stroke in the stroke unit of the Klaipeda University Hospital in 2007- 2015. Medical history data of 265 patients who died from acute stroke in the stroke unit were analysed. Inpatient mortality rate was calculated among all patients diagnosed with acute stroke who were treated in the stroke unit during the entire study period. The number of deaths in different age groups (up until 65; 65 and older) and comorbidities in patients who died from acute stroke were analysed, depending on stroke type in different treatment periods (2007-2011 and 2012-2015). The International Classification of Diseases, Tenth Revision (ICD-10), Codes I60-I64 were used to diagnose different stroke types in 2007-2011, while ICD-10 AM, Codes I60-I64 were used in 2012- 2015. The statistical analysis was performed using SPSS 17.0 for Windows. Chi-squared (χ2) criterion and Fisher’s exact test were used for small samples to evaluate dependency and homogeneity of qualitative characteristics. The difference between them was considered as statistically significant at p <0.05. Data are presented as a percentage. Student’s t-test was applied for average age comparison. Odds ratio (OR), reflecting the mortality from acute stroke in different periods, was established. The comparison of the two study periods revealed the decrease in patients who died from acute stroke - from 7.0% (2007-2011) to 4,3 % (2012-2015), (p<0.001). Mortality from ischemic and hemorrhagic stroke was similar. The analysis showed significant age difference (p=0.007) among patients who died from acute stroke: in the later study period (2012-2015), the patients were older than those who died in the earlier period; however, no significant difference was observed when analysing them by age groups (up until 65; 65 and older). The odds of dying in 2007- 2011 were 1.69 times higher than in 2012-2015 (p<0.001), whereas the odds ratio for ischemic stroke in 2007-2011 was 1.75 times higher than in 2012- 2015 (p<0.0001). No significant difference between different study periods was established when analysing the changes in the number of comorbidities in patients who died from acute stroke. The assesment of differences in comorbidities depending on the stroke type revealed that significantly more patients who died from ischemic stroke had been diagnosed with coronary heart disease (CHD) (including angina pectoris (AP) and atrial fibrillation (AF)) than those who died from hemorrhagic stroke. It was concluded that, when comparing the two study periods, the number of patients who died from acute stroke decreased significantly - from 7.0% (2007- 2011) to 4.3% (2012-2015) (p<0.001). The odds ratio for dying from acute stroke in 2007-2011 was established to be significantly higher than in 2012- 2015 and patients who died from acute stroke in the later study period were significantly older.

scholarly journals Circulating miR-30d Predicts Survival in Patients with Acute Heart Failure

2017 ◽  
Vol 41 (3) ◽  
pp. 865-874 ◽  
Author(s):  
Junjie Xiao ◽  
Rongrong Gao ◽  
Yihua Bei ◽  
Qiulian Zhou ◽  
Yanli Zhou ◽  
...  
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Univariate Logistic Regression Analysis ◽  
Kaplan Meier ◽  
All Cause Mortality

Background/Aims: Identification of novel biomarkers to identify acute heart failure (AHF) patients at high risk of mortality is an area of unmet clinical need. Recently, we reported that the baseline level of circulating miR-30d was associated with left ventricular remodeling in response to cardiac resynchronization therapy in advanced chronic heart failure patients. However, the role of circulating miR-30d as a prognostic marker of survival in patients with AHF has not been explored. Methods: Patients clinically diagnosed with AHF were enrolled and followed up for 1 year. Quantitative reverse transcription polymerase chain reactions were used to determine serum miR-30d levels. The univariate logistic regression analysis and multivariate logistic regression analysis were used to determine the predictors for all-cause mortality in AHF patients. Kaplan–Meier survival analysis was used to analyze the role of miR-30d in prediction of survival. Results: A total of 96 AHF patients were enrolled and followed up for 1 year. Serum miR-30d was significantly lower in AHF patients who expired in the one year follow-up period compared to those who survived. Univariate logistic regression analysis yielded 18 variables that were associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 4 variables including heart rate, hemoglobin, serum sodium, and serum miR-30d level associated with mortality. ROC curve analysis showed that hemoglobin, heart rate and serum sodium displayed poor prognostic value for AHF (AUCs not higher than 0.700) compared to miR-30d level (AUC = 0.806). Kaplan–Meier survival analysis confirmed that patients with higher serum miR-30d levels had significantly lower mortality (P=0.001). Conclusion: In conclusion, this study shows evidence for the predictive value of circulating miR-30d as 1-year all-cause mortality in AHF patients. Large multicentre studies are further needed to validate our findings and accelerate the transition to clinical utilization.

scholarly journals Assessing and predicting neuropathic pain after spinal cord injury: a TRACK-SCI study

2021 ◽  
Author(s):  
Kenneth A. Fond ◽  
Abel Torres-Espin ◽  
Austin Chou ◽  
Xuan Duong-Fernandez ◽  
Sara L. Moncivais ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Logistic Regression ◽  
Neuropathic Pain ◽  
Injury Severity ◽  
Hospital Setting ◽  
Study Cohort ◽  
Research Database ◽  
Pain Status ◽  
Cord Injury

Neuropathic pain is one of the most common secondary complications occurring after spinal cord injury (SCI), and often surpasses motor and sensory deficits in the patient population preferences of the most important aspects to be treated. Despite the better understanding of the molecular and physiological mechanisms of neuropathic pain, reliable treatments are still lacking and exhibit wide variations in efficiency. Previous reports have suggested that the most effective pain management is early treatment. To this end, we utilized the TRACK-SCI prospective clinical research database to assess the neuropathic pain status of all enrolled patients and identify acute care variables that can predict the development of neuropathic pain 6- and 12-months post SCI. 36 out of 61 patients of our study cohort reported neuropathic pain at the chronic stages post SCI. Using multidimensional analytics and logistic regression we discovered that (1) the number of total injuries the patient sustained, (2) the injury severity score (ISS), (3) the lower limb total motor score, and (4) the sensory pin prick total score together predict the development of chronic neuropathic pain after SCI. The balanced accuracy of the corresponding logistic regression model is 74.3%, and repeated 5-fold cross validation showed an AUC of 0.708. Our study suggests a crucial role of polytrauma in chronic pain development after SCI and offers a predictive model using variables routinely collected at every hospital setting.

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