scholarly journals What Differentiates Poor and Good Outcome Psychotherapy? A Statistical-Mechanics-Inspired Approach to Psychotherapy Research

2019 ◽  
Author(s):  
Giulio De Felice ◽  
Franco Orsucci ◽  
Andrea Scozzari ◽  
Omar Gelo ◽  
Gabriele Serafini ◽  
...  
Keyword(s):  
Statistical Mechanics ◽  
Multivariate Time Series ◽  
Specific Effect ◽  
Psychotherapy Research ◽  
Principal Component ◽  
Coarse Grained ◽  
Emergent Properties ◽  
Good Outcome ◽  
Poor Outcome ◽  
Abstract Language

Statistical mechanics investigates how emergent properties of macroscopic systems (such as temperature and pressure) relate to microscopic state fluctuations. The underlying idea is that global statistical descriptors of order and variability can monitor the relevant dynamics of the whole system at hand. Here we test the possibility of extending such an approach to psychotherapy research investigating the possibility of predicting the outcome of psychotherapy on the sole basis of coarse-grained empirical macro-parameters. Four good-outcome and four poor-outcome brief psychotherapies were recorded, and their transcripts coded in terms of standard psychological categories (abstract, positive emotional and negative emotional language pertaining to patient and therapist). Each patient-therapist interaction is considered as a discrete multivariate time series made of subsequent word-blocks of 150-word length, defined in terms of the above categories. Static analysis (Principal Component Analysis) highlighted a substantial difference between good-outcome and poor-outcome cases in terms of mutual correlations among those descriptors. In the former, the patient’s use of abstract language correlated with therapist’s emotional negative language, while in the latter it co-varied with therapist’s emotional positive language, thus showing the different judgment of the therapists regarding the same variable (abstract language) in poor and good outcome cases. On the other hand, the dynamic analysis, based on five coarse-grained descriptors related to variability, degree of order and complexity of the series, demonstrated a relevant case-specific effect, pointing to the possibility of deriving a consistent picture of any single psychotherapeutic process. Overall, the results showed that the systemic approach to psychotherapy (an old tenet of psychology) is mature to shift from a metaphorical to a fully quantitative status.

scholarly journals What Differentiates Poor and Good Outcome Psychotherapy? A Statistical-Mechanics-Inspired Approach to Psychotherapy Research

Systems ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 22 ◽  
Author(s):  
Giulio Felice ◽  
Franco Orsucci ◽  
Andrea Scozzari ◽  
Omar Gelo ◽  
Gabriele Serafini ◽  
...  
Keyword(s):  
Statistical Mechanics ◽  
Multivariate Time Series ◽  
Specific Effect ◽  
Psychotherapy Research ◽  
Principal Component ◽  
Coarse Grained ◽  
Emergent Properties ◽  
Good Outcome ◽  
Poor Outcome ◽  
Abstract Language

Statistical mechanics investigates how emergent properties of macroscopic systems (such as temperature and pressure) relate to microscopic state fluctuations. The underlying idea is that global statistical descriptors of order and variability can monitor the relevant dynamics of the whole system at hand. Here we test the possibility of extending such an approach to psychotherapy research investigating the possibility of predicting the outcome of psychotherapy on the sole basis of coarse-grained empirical macro-parameters. Four good-outcome and four poor-outcome brief psychotherapies were recorded, and their transcripts coded in terms of standard psychological categories (abstract, positive emotional and negative emotional language pertaining to patient and therapist). Each patient-therapist interaction is considered as a discrete multivariate time series made of subsequent word-blocks of 150-word length, defined in terms of the above categories. “Static analyses” (Principal Component Analysis) highlighted a substantial difference between good-outcome and poor-outcome cases in terms of mutual correlations among those descriptors. In the former, the patient’s use of abstract language correlated with therapist’s emotional negative language, while in the latter it co-varied with therapist’s emotional positive language, thus showing the different judgment of the therapists regarding the same variable (abstract language) in poor and good outcome cases. On the other hand, the “dynamic analyses”, based on five coarse-grained descriptors related to variability, the degree of order and complexity of the series, demonstrated a relevant case-specific effect, pointing to the possibility of deriving a consistent picture of any single psychotherapeutic process. Overall, the results showed that the systemic approach to psychotherapy (an old tenet of psychology) is mature enough to shift from a metaphorical to a fully quantitative status.

scholarly journals Integration of Cognitive and Emotional Processing Predicts Poor and Good Outcomes of Psychotherapy

2021 ◽  
Author(s):  
Giulio de Felice ◽  
Alessandro Giuliani ◽  
Silvia Andreassi ◽  
Franco Orsucci ◽  
Helmut Schöller ◽  
...  
Keyword(s):  
Emotional Processing ◽  
Principal Component ◽  
Well Being ◽  
University Hospital ◽  
Linear Discriminant ◽  
Daily Monitoring ◽  
Good Outcome ◽  
Poor Outcome ◽  
Monitoring Procedure ◽  
Affective Components

Abstract With the aim of investigating analogies and differences between psychotherapeutic processes, ten good-outcome and ten poor-outcome cases were selected from a sample of patients treated at the University Hospital of Psychiatry, Salzburg, Austria, and the Department of Psycho-Traumatology of the Clinic St. Irmingard, Prien am Chiemsee, Germany. They were monitored daily using the Therapy Process Questionnaire (TPQ), and their evolution over time was analyzed by means of Principal Components Analysis and Linear Discriminant Analysis. The results highlight that poor-outcome patients show a separation between cognitive processes (Principal Component 1) and relational-emotional processes (Principal Component 2) (r = − 0.25; p = n.s.), while in the good-outcome patients these aspects are well integrated (r = 0.70; p = 0.02). These results corroborate the validity of the daily monitoring procedure and also indicate the need for greater attention to the relational and emotional aspects of the patients rather than merely to their cognitive functioning and well-being. Key Message In poor-outcome cases, burdensome emotions and interpersonal experiences on the one hand and cognitive/well-being aspects of the mental processing on the other, stay unrelated. Successful therapeutic processing, as in good-outcome cases, requires an integration of cognitive and affective components.

scholarly journals What Differentiates Poor- and Good-Outcome Psychotherapy? A Statistical-Mechanics-Inspired Approach to Psychotherapy Research, Part Two: Network Analyses

2020 ◽  
Vol 11 ◽  
Author(s):  
Giulio de Felice ◽  
Alessandro Giuliani ◽  
Omar C. G. Gelo ◽  
Erhard Mergenthaler ◽  
Melissa M. De Smet ◽  
...  
Keyword(s):  
Statistical Mechanics ◽  
Psychotherapy Research ◽  
Network Analyses ◽  
Good Outcome

Langfeldt's Schizophreniform Psychoses Fifty Years Later

1990 ◽  
Vol 157 (3) ◽  
pp. 351-354 ◽  
Author(s):  
A. L. Mina Bergem ◽  
Alv A. Dahl ◽  
Cato Guldberg ◽  
Helge Hansen
Keyword(s):  
Clinical Picture ◽  
Affective Disorders ◽  
Diagnostic Systems ◽  
Good Outcome ◽  
Poor Outcome ◽  
Follow Up Studies

As a result of follow-up studies published in 1937 and 1939, Langfeldt divided schizophrenia into two groups; ‘typical schizophrenia’ which had a poor outcome, and the ‘schizophreniform psychoses' which had a less typical clinical picture of schizophrenia and a good outcome. Langfeldt's cases of schizophreniform psychoses were reclassified according to the ICD–9 and DSM–III–R diagnostic systems. Most of the schizophreniform psychoses did not appear ‘schizophrenia-like’ at all, but turned out to be mainly affective disorders. Those included in Langfeldt's diagnosis of ‘schizophreniform psychoses' were found to be too heterogenous to validate the existence of this syndrome.

Abstract TP195: Pre-Stroke Cognitive Impairment is Associated With Poor Outcome in Acute Ischemic Stroke Patients Treated With Mechanical Thrombectomy

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Takuya Kanamaru ◽  
Satoshi Suda ◽  
Junya Aoki ◽  
Kentaro Suzuki ◽  
Yuki Sakamoto ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Cognitive Impairment ◽  
Acute Ischemic Stroke ◽  
Mechanical Thrombectomy ◽  
Modified Rankin Scale ◽  
Good Outcome ◽  
Poor Outcome ◽  
Poor Outcome Group ◽  
Outcome Group ◽  
Significant Difference

Background: It is reported that pre-stroke cognitive impairment is associated with poor functional outcome after stroke associated with small vessel disease. However, it is not clear that pre-stroke cognitive impairment is associated with poor outcome in patients treated with mechanical thrombectomy. Method: We enrolled 127 consecutive patients treated with mechanical thrombectomy for acute ischemic stroke from December 2016 to November 2018. Pre-stroke cognitive function was evaluated using the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). We retrospectively compared poor outcome (a score of 3 to 6 on the modified Rankin Scale at 90 days) group (n=75) with good outcome (a score of 0, 1, or 2 on the modified Rankin Scale at 90 days) group (n=52) and examined that IQCODE could be the predictor of PO. Result: IQCODE was significantly higher in poor outcome group than in good outcome group (89 vs. 82, P=0.0012). Moreover, age (77.2 years old vs. 71.6 years old, P= 0.0009), the percentage of female (42.7% vs. 17.3%, P= 0.0021), complication of hypertension (HT, 68.0% vs. 44.2%, P=0.0076), National Institutes of Health Stroke Scale (NIHSS) at admission (20 vs. 11, P<0.0001), the percentage of postoperative intracerebral hemorrhage (ICH, 33.3% vs. 15.4%, P=0.0233) were higher in poor outcome group than in good outcome group, too. However, there was no significant difference between poor outcome and good outcome groups in occlusion site (P= 0.1229), DWI-ASPECTS (P= 0.2839), the duration from onset to recanalization (P=0.4871) and other risk factors. Multivariable logistic regression analysis demonstrated that IQCODE, HT and NIHSS at admission were associated with poor outcome (P= 0.0128, P=0.0061 and P<0.0001, respectively). Conclusion: Cognitive impairment could be associated with poor outcome in patients treated with mechanical thrombectomy.

Abstract 150: Multicenter Validation of SPOT, an Artificial Intelligence Based Tool, to Optimize Selection of Elderly Stroke Patients for Mechanical Thrombectomy - Insights From the STAR Collaboration

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Ali M Alawieh ◽  
Mohamed Baker Alawieh ◽  
Fadi Zaraket ◽  
Reda M Chalhoub ◽  
Mohammad Anadani ◽  
...  
Keyword(s):  
Elderly Patients ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Mechanical Thrombectomy ◽  
Characteristic Curve ◽  
Linear Regression Models ◽  
Good Outcome ◽  
Poor Outcome ◽  
Multicenter Validation ◽  
Selection Of

Introduction: Mechanical thrombectomy for acute ischemic stroke (AIS) is the current standard of care based on level 1 evidence from multiple randomized controlled trials. Recently, real-world indications for mechanical thrombectomy (MT) has extended beyond the inclusion criteria used in the majority of trials including elderly patients. We have recently developed a machine-learning based tool, SPOT, to optimize selection of elderly patients for MT based on single-center data. Here, we use a large cohort of international multicenter patients who underwent MT for AIS to externally validate SPOT. Methods: Patients who underwent MT for AIS at 12 comprehensive stroke centers in the US and Europe between 01/2013 and 12/2018 were reviewed. Patients age 80 years or older were included for validation of SPOT. SPOT is designed based on a combination of decision trees and linear regression models to provide binary output of predicted good (mRS 0-2) or poor outcome (mRS 3-6) after MT. SPOT uses admission variables: age, gender, comorbidities, admission NIHSS, baseline mRS score, ASPECT score and whether IV-tPA was administered. Predicted outcome was compared to actual outcome recorded at 90-days after treatment. A receiver operating characteristic curve was used to evaluate the accuracy of SPOT, and the negative predictive value was computed. The rate of post-procedural hemorrhage and mortality were compared between patients predicted by SPOT to have good versus poor outcome. Results: A total of 3,228 patients underwent MT for AIS during the study duration, of which 647 patients were at least 80 years of age or older and were included in the study. The average age was 85±5 years, and 65% were females. The median mRS score at 90 days was 4, and 21.3% had a good outcome (mRS 0-2). Of patients predicted by SPOT to have a poor outcome, 90% had a poor outcome. The area under the ROC curve was 0.7. The mortality rate in patients predicted by SPOT to have poor outcome had twice higher mortality than those predicted to have good outcome (55% vs 27%, p<0.001). Conclusions: Based on multicenter validation, SPOT presents a clinical decision in aid in assisting for exclusion of elderly patients unlikely to benefit from MT for AIS with a 90% negative predictive value.

Abstract 10: Predictors of Poor Outcome in Acute Ischemic Stroke Patients after Successful Recanalization

2014 ◽  
Vol 7 (suppl_1) ◽  
Author(s):  
Amy K Starosciak ◽  
Italo Linfante ◽  
Gail Walker ◽  
Osama O Zaidat ◽  
Alicia C Castonguay ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Cerebral Infarction ◽  
Acute Stroke ◽  
Acute Ischemic Stroke ◽  
Predictive Power ◽  
Rescue Therapy ◽  
Univariate Analysis ◽  
Stroke Patients ◽  
Good Outcome ◽  
Poor Outcome

Background: Recanalization of the occluded artery is a powerful predictor of good outcome in acute ischemic stroke secondary to large artery occlusions. Mechanical thrombectomy with stent-trievers results in higher recanalization rates and better outcomes compared to previous devices. However, despite successful recanalization rates (Treatment in Cerebral Infarction, TICI, score ≥ 2b) between 70 and 90%, good clinical outcomes assessed by modified Rankin Scale (mRS) ≤ 2 is present in 40-50% of patients . We aimed to evaluate predictors of poor outcomes (mRS > 2) despite successful recanalization (TICI ≥ 2b) in the acute stroke patients treated with the Solitaire device of the North American Solitaire Stent Retriever Acute Stroke (NASA) registry. Methods: The NASA registry is a multicenter, non-sponsored, physician-conducted, post-marketing registry on the use of SOLITAIRE FR device in 354 acute, large vessel, ischemic stroke patients. Logistic regression was used to evaluate patient characteristics and treatment parameters for association with 90-day mRS score of 0-2 (good outcome) versus 3-6 (poor outcome) within patients who were recanalized successfully (Thrombolysis in Cerebral Infarction or TICI score 2b-3). Univariate tests were followed by development of a multivariable model based on stepwise selection with entry and retention criteria of p < 0.05 from the set of factors with at least marginal significance (p ≤ 0.10) on univariate analysis. The c-statistic was calculated as a measure of predictive power. Results: Out of 354 patients, 256 (72.3%) were successfully recanalized (TICI ≥ 2b). Based on 90-day mRS score for 234 of these patients, there were 116 (49.6%) with mRS > 2. Univariate analysis identified increased risk of mRS > 2 for each of the following: age ≥ 80 years (upper quartile of data), occlusion site other than M1/M2, NIH Stroke Scale (NIHSS) score ≥ 18 (median), history of diabetes mellitus (DM), TICI = 2b, use of rescue therapy, not using a balloon-guided catheter (BGC) or intravenous tissue plasminogen activator (IV t-PA), and time to recanalization > 30 minutes (all p ≤ 0.05). Three or more passes was marginally significant (p=0.097). In multivariable analysis, age ≥ 80 years, site other than M1/M2, initial NIHSS ≥18, DM, absence of IV t-PA, use of rescue therapy and three or more passes were significant independent predictors of poor 90-day outcome in a model with good predictive power (c-index = 0.80). Conclusions: Age, occlusion site, high NIHSS, diabetes, not receiving IV t-PA, use of rescue therapy and three or more passes, were associated with poor 90-day outcome despite successful recanalization.

Quantitative MR spectroscopic imaging in metachromatic leukodystrophy: value for prognosis and treatment

2017 ◽  
Vol 89 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Diane F van Rappard ◽  
Antoine Klauser ◽  
Marjan E Steenweg ◽  
Jaap Jan Boelens ◽  
Marianna Bugiani ◽  
...  
Keyword(s):  
Logistic Regression ◽  
White Matter ◽  
Metachromatic Leukodystrophy ◽  
Spectroscopic Imaging ◽  
Complete Separation ◽  
Significant Group ◽  
Good Outcome ◽  
Poor Outcome ◽  
Metabolite Concentrations

ObjectiveTo determine whether proton magnetic resonance spectroscopic imaging is useful in predicting clinical course of patients with metachromatic leukodystrophy (MLD), an inherited white matter disorder treatable with haematopoietic cell transplantation (HCT).Methods21 patients with juvenile or adult MLD (12 HCT-treated) were compared with 16 controls in the same age range. Clinical outcome was determined as good, moderate or poor. Metabolites were quantified in white matter, and significance of metabolite concentrations at baseline for outcome prediction was assessed using logistic regression analysis. Evolution of metabolic changes was assessed for patients with follow-up examinations.ResultsIn this retrospective study, 16 patients with baseline scans were included, 5 with good, 3 with moderate and 8 with poor outcome, and 16 controls. We observed significant group differences for all metabolite concentrations in white matter (p<0.001). Compared with controls, patients had decreased N-acetylaspartate and glutamate, and increased myo-inositol and lactate, most pronounced in patients with poor outcome (post hoc, all p<0.05). Logistic regression showed complete separation of data. Creatine could distinguish poor from moderate and good outcome, the sum of glutamate and glutamine could distinguish good from moderate and poor outcome, and N-acetylaspartate could distinguish all outcome groups. For 13 patients (8 with baseline scans), one or more follow-up examinations were evaluated, revealing stabilisation or even partial normalisation of metabolites in patients with moderate and good outcome, clearly visible in the ratio of choline/N-acetylaspartate.ConclusionIn MLD, quantitative spectroscopic imaging at baseline is predictive for outcome and aids in determining eligibility for HCT.

scholarly journals Predictors of Poor Outcome after Successful Mechanical Thrombectomy in Patients with Acute Anterior Circulation Stroke

2017 ◽  
Vol 01 (03) ◽  
pp. 139-143 ◽  
Author(s):  
Yosuke Tajima ◽  
Michihiro Hayasaka ◽  
Koichi Ebihara ◽  
Masaaki Kubota ◽  
Sumio Suda
Keyword(s):  
Clinical Outcome ◽  
Cerebral Artery ◽  
Mechanical Thrombectomy ◽  
Infarct Volume ◽  
Complete Revascularization ◽  
Anterior Circulation ◽  
Clinical Imaging ◽  
Good Outcome ◽  
Poor Outcome ◽  
Favorable Clinical Outcome

AbstractSuccessful revascularization is one of the main predictors of a favorable clinical outcome after mechanical thrombectomy. However, even if mechanical thrombectomy is successful, some patients have a poor clinical outcome. This study aimed to investigate the clinical, imaging, and procedural factors that are predictive of poor clinical outcomes despite successful revascularization after mechanical thrombectomy in patients with acute anterior circulation stroke. The authors evaluated 69 consecutive patients (mean age, 74.6 years, 29 women) who presented with acute ischemic stroke due to internal cerebral artery or middle cerebral artery occlusions and who were successfully treated with mechanical thrombectomy between July 2014 and November 2016. A good outcome was defined as a modified Rankin Scale score of 0 to 2 at 3 months after treatment. The associations between the clinical, imaging, and procedural factors and poor outcome were evaluated using logistic regression analyses. Using multivariate analyses, the authors found that the preoperative National Institute of Health Stroke Scale (NIHSS) score (odds ratio [OR], 1.152; 95% confidence interval [CI], 1.004–1.325; p = 0.028), the diffusion-weighted imaging Alberta Stroke Program Early Computed Tomography Score (DWI-ASPECTS) (OR, 0.604; 95% CI, 0.412–0.882; p = 0.003), and a Thrombolysis in Cerebral Infarction (TICI) 2b classification (OR, 4.521; 95% CI, 1.140–17.885; p = 0.026) were independent predictors of poor outcome. Complete revascularization to reduce the infarct volume should be performed, especially in patients with a high DWI-ASPECTS, to increase the likelihood of a good outcome.

scholarly journals Heavy minerals in the Wajid Sandstone from Abha-Khamis Mushayt area, southwestern Saudi Arabia: implications on provenance and regional tectonic setting

GeoArabia ◽  
2004 ◽  
Vol 9 (4) ◽  
pp. 77-102 ◽  
Author(s):  
Mahbub Hussain ◽  
Lameed O. Babalola ◽  
Mustafa M. Hariri
Keyword(s):  
Saudi Arabia ◽  
Tectonic Setting ◽  
Principal Component ◽  
Heavy Mineral ◽  
Heavy Minerals ◽  
Coarse Grained ◽  
Distribution Data ◽  
The South ◽  
Quartz Content ◽  
The North

ABSTRACT The Wajid Sandstone (Ordovician-Permian) as exposed along the road-cut sections of the Abha and Khamis Mushayt areas in southwestern Saudi Arabia, is a mediun to coarse-grained, mineralogically mature quartz arenite with an average quartz content of over 95%. Monocrystalline quartz is the dominant framework grain followed by polycrystalline quartz, feldspar and micas. The non-opaque heavy mineral assemblage of the sandstone is dominated by zircon, tourmaline and rutile (ZTR). Additional heavy minerals, constituting a very minor fraction of the heavies, include epidote, hornblende, and kyanite. Statistical analysis showed significant correlations between zircon, tourmaline, rutile, epidote and hornblende. Principal component R-mode varimax factor analysis of the heavy mineral distribution data shows two strong associations: (1) tourmaline, zircon, rutile, and (2) epidote and hornblende suggesting several likely provenances including igneous, recycled sedimentary and metamorphic rocks. However, an abundance of the ZTR minerals favors a recycled sedimentary source over other possibilities. Mineralogical maturity coupled with characteristic heavy mineral associations, consistent north-directed paleoflow evidence, and the tectonic evolutionary history of the region indicate a provenance south of the study area. The most likely provenances of the lower part (Dibsiyah and Khusayyan members) of the Wajid Sandstone are the Neoproterozoic Afif, Abas, Al-Bayda, Al-Mahfid, and Al-Mukalla terranes, and older recycled sediments of the infra-Cambrian Ghabar Group in Yemen to the south. Because Neoproterozic (650-542 Ma) rocks are not widespread in Somalia, Eritrea and Ethiopia, a significant source further to the south is not likely. The dominance of the ultrastable minerals zircon, tourmaline and rutile and apparent absence of metastable, labile minerals in the heavy mineral suite preclude the exposed arc-derived oceanic terrains of the Arabian Shield in the west and north as a significant contributor of the sandstone. An abundance of finer-grained siliciclastic sequences of the same age in the north, is consistent with a northerly transport direction and the existence of a deeper basin (Tabuk Basin?) to the north. The tectonic and depositional model presented in this paper differs from the existing model that envisages sediment transportation and gradual basin filling from west to east during the Paleozoic.

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