INS NYC 2024 Program

Poster	Poster Session 04 Program Schedule 02/15/2024 12:00 pm - 01:15 pm Room: Shubert Complex (Posters 1-60) Poster Session 04: Neuroimaging \| Neurostimulation/Neuromodulation \| Teleneuropsychology/Technology Final Abstract #52 Do pretreatment neurocognitive scores predict response to TMS for treatment resistant depression? Robert Hickson, Palo Alto University, Palo Alto, United States Michelle Madore, Palo Alto Veteran Affairs, Palo Alto, United States Category: Neurostimulation/Neuromodulation Keyword 1: depression Keyword 2: neuromodulation Keyword 3: computerized neuropsychological testing Objective: Major Depressive Disorder (MDD) is associated with deficits in several cognitive domains, including memory, attention, processing speed, cognitive flexibility, and executive functioning. The utilization of computerized assessments to measure these domains is growing with the field of neuropsychology. Transcranial magnetic stimulation (TMS) is an effective treatment for resistant depression. While the relationship between cognitive deficits and MDD has been extensively studied, the extent to which specific cognitive deficits can predict the response to TMS treatment remains uncertain. Understanding cognitive profiles as they relate to treatment response can help providers identify patients who might benefit less from TMS intervention. To this end, this study looks at pre-treatment neurocognitive scores from a computerized battery as predictors of response to TMS treatment. We hypothesize that lower scores in neurocognitive measures of attention, executive functioning, and cognitive flexibility will be predictive of response to TMS treatment. Participants and Methods: Participants consisted of 36 Veterans (17% female; age M = 46.9, SD = 12.7; years of education ranging from 12-18) who completed a full 30-session course of TMS treatment and had significant depressive symptoms at baseline (Patient Health Questionnaire-9; PHQ-9 score ≤ 5). Participants were given PHQ-9 and Computerized Neurocognitive Assessment Vital Signs (CNSVS) at baseline and again after completion of TMS treatment. We performed a multiple logistic regression of Veterans’ standardized scores in memory, simple attention, complex attention, processing speed, cognitive flexibility, and executive functioning from CNSVS predicting TMS treatment response as indicated by a reduction of 10 points or greater on PHQ-9 scores at post-treatment compared to pre-treatment scores. Results: The predictor variables – memory, simple attention, complex attention, processing speed, cognitive flexibility, and executive functioning – were tested a priori to verify that assumptions of linearity were met. In order to assess the significance of the predictors in the logistic regression model, a likelihood ratio test was conducted to compare two logistic regression models. The first model included the predictor variables while the second model served as a null model without any predictors. The likelihood ratio test yielded a chi-square statistic of 2.43 (df = 7, p = .88), indicating there was not a significant difference between the model in predicting treatment response. Additionally, none of the predictor variables were found to be significant contributes to the logistic regression model. Conclusions: The results from the study indicate that there is not a relationship between pretreatment scores in neurocognitive domains often associated with depression and one’s response to TMS treatment for depression. An important consideration and limitation of the study is that neurocognitive data was collected via a computerized battery, and the assumed cognitive deficits at pretreatment in the domains of attention, memory, processing speed, executive functioning, and cognitive flexibility did not hold to be true for this sample. Therefore, this study calls into question the robustness of computerized assessments in their ability to detect subtle depression-related cognitive deficits which can provide insight into individual differences that guide treatment.

Poster

02/15/2024
12:00 pm - 01:15 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 04: Neuroimaging | Neurostimulation/Neuromodulation | Teleneuropsychology/Technology

Final Abstract #52

Do pretreatment neurocognitive scores predict response to TMS for treatment resistant depression?

Robert Hickson, Palo Alto University, Palo Alto, United States
Michelle Madore, Palo Alto Veteran Affairs, Palo Alto, United States

Category: Neurostimulation/Neuromodulation

Keyword 1: depression
Keyword 2: neuromodulation
Keyword 3: computerized neuropsychological testing

Objective:

Major Depressive Disorder (MDD) is associated with deficits in several cognitive domains, including memory, attention, processing speed, cognitive flexibility, and executive functioning. The utilization of computerized assessments to measure these domains is growing with the field of neuropsychology. Transcranial magnetic stimulation (TMS) is an effective treatment for resistant depression. While the relationship between cognitive deficits and MDD has been extensively studied, the extent to which specific cognitive deficits can predict the response to TMS treatment remains uncertain. Understanding cognitive profiles as they relate to treatment response can help providers identify patients who might benefit less from TMS intervention. To this end, this study looks at pre-treatment neurocognitive scores from a computerized battery as predictors of response to TMS treatment. We hypothesize that lower scores in neurocognitive measures of attention, executive functioning, and cognitive flexibility will be predictive of response to TMS treatment.

Participants and Methods:

Participants consisted of 36 Veterans (17% female; age M = 46.9, SD = 12.7; years of education ranging from 12-18) who completed a full 30-session course of TMS treatment and had significant depressive symptoms at baseline (Patient Health Questionnaire-9; PHQ-9 score ≤ 5). Participants were given PHQ-9 and Computerized Neurocognitive Assessment Vital Signs (CNSVS) at baseline and again after completion of TMS treatment. We performed a multiple logistic regression of Veterans’ standardized scores in memory, simple attention, complex attention, processing speed, cognitive flexibility, and executive functioning from CNSVS predicting TMS treatment response as indicated by a reduction of 10 points or greater on PHQ-9 scores at post-treatment compared to pre-treatment scores.

Results:

The predictor variables – memory, simple attention, complex attention, processing speed, cognitive flexibility, and executive functioning – were tested a priori to verify that assumptions of linearity were met. In order to assess the significance of the predictors in the logistic regression model, a likelihood ratio test was conducted to compare two logistic regression models. The first model included the predictor variables while the second model served as a null model without any predictors. The likelihood ratio test yielded a chi-square statistic of 2.43 (df = 7, p = .88), indicating there was not a significant difference between the model in predicting treatment response. Additionally, none of the predictor variables were found to be significant contributes to the logistic regression model.

Conclusions:

The results from the study indicate that there is not a relationship between pretreatment scores in neurocognitive domains often associated with depression and one’s response to TMS treatment for depression. An important consideration and limitation of the study is that neurocognitive data was collected via a computerized battery, and the assumed cognitive deficits at pretreatment in the domains of attention, memory, processing speed, executive functioning, and cognitive flexibility did not hold to be true for this sample. Therefore, this study calls into question the robustness of computerized assessments in their ability to detect subtle depression-related cognitive deficits which can provide insight into individual differences that guide treatment.