Impaired nonverbal language patterns may help determine subsequent depression risk in patients who have had a recent stroke, new research suggests.
A small, pilot study of 49 patients showed that overall, 23% of the participants developed depression within 3 months of sustaining a stroke. Significant predictors of post-stroke depression (PSD) included impaired affective prosody, such as voice breaks at baseline, and shimmer, defined as "small variations in glottal pulse amplitude."
The investigators, led by Marie Villain, University of Bordeaux, Talence, France, note the importance of paying attention to "early alterations of affective prosody" in this patient population.
"This new physiological approach overcomes traditional barriers associated with clinical instruments and contributes to the prediction of this disorder," they write.
The findings were published online August 9 in Stroke.
Impaired "Extraverbal" Information
"The identification of patients at risk for developing [PSD] remains an important issue for clinicians because its early diagnosis is essential to improve therapeutic strategies," note the researchers.
"Impairment of affective prosody, defined as extraverbal information indicating the emotional state of the speaker, independent of verbal content, has been extensively reported in major depression."
They add that prosody factors can include shimmer, voice breaks, speech rate, intensity of sound emissions, and frequency of voice signal.
"Because changes in emotional states are often coupled with modifications in laryngeal tension and subglottal pressure, it is hypothesized that affective prosody would be a reliable biomarker of this disorder," report the investigators.
All of the study participants (78% men; mean age, 59.3 years) had had a minor ischemic stroke, as confirmed by MRI. Exclusion criteria included symptoms of depression or anxiety during hospitalization, a history of dementia, or post-stroke dysarthria or aphasia.
Four days after stroke onset (baseline) and at 3 months after stroke, the patients' voices were recorded while they performed a picture description task and read a story out loud. Various voice parameters were than measured.
Other measurements at the 3-month timepoint included the Rankin Scale for functional outcomes and the Hospital Anxiety and Depression Scales.
Improved Detection
Results from the reading task showed significantly more voice breaks at baseline (P = .047) for patients who had PSD 3 months later than for those who did not have the disorder. Interestingly, the depression group showed a significant decrease in this measure between baseline and 3 months (P = .002).
A lower shimmer was found in the PSD than in the non-PSD group at baseline (P = .002) and at 3 months (P = .03).
In addition, the PSD group showed a significant decrease from baseline in fundamental voice frequency during both the reading (P = .02) and description (P = .01) tasks.
After adjustment for sex, there was also a significant inverse association between fundamental frequency deviation and depressive symptom severity (P = .02).
Although the PSD group had more anxiety symptoms, no significant associations were found between any prosody factors and anxiety severity. There were also no association between stroke location and PSD development.
"The main results of this pilot study are that a combination of prosodic markers measured early after stroke permits the identification of patients at risk of subsequent PSD," summarize the investigators.
Although they caution that "the results cannot be generalized" because of the study's small sample size, "baseline evaluation of this new biomarker could improve our ability to detect patients at risk of PSD and, therefore, improving its management."
The study authors have disclosed no relevant financial relationships.
Stroke. Published online August 9, 2016. Abstract
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Cite this: Altered Speech Patterns May Predict Post-Stroke Depression - Medscape - Aug 17, 2016.
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