SYSTEM AND METHOD FOR PREDICTION OF ADVERSE EVENTS DURING TREATMENT OF PSYCHOLOGICAL AND NEUROLOGICAL DISORDERS
CROSS REFERENCE TO RELATED APPLICATION
This application claims benefit of U.S. Provisional Application Ser. No. 60/643,350 filed on Jan. 12, 2005.
Depression is a mood disorder that affects 17 million Americans each year, and is responsible for 9.7 million doctor visits. It affects sufferers in a variety of ways, resulting in depressed mood, irritability, sleep disorders, feelings of agitation, guilt and worthlessness, loss of energy and initiative, an inability to concentrate and an increased incidence of suicide. There are a number of antidepressant pharmacological agents, and once the proper treatment is detennined, their effectiveness is quite high.
Maj or Depressive Disorder (MDD) is the psychiatric diagnosis most commonly associated with completed suicide. The American Association of Suicidology notes on their website that the lifetime risk of suicide among patients with untreated MDD is nearly 20%. About 2/3 of people who complete suicide are depressed at the time of their deaths. In a study conducted in Finland, of 71 individuals who completed suicide and who had Major Depressive Disorder, only 45% were receiving treatment at the time of death and only a third of these were taking antidepressants.
Evidence suggests that phannacological treatment of some depressed subjects may increase the risk of suicidal thinking and behavior in adolescents. Development of methods to identify those subjects who are at increased risk of developing adverse events, especially suicide, would provide significant benefit to both patients and clinicians.
Cook et al. demonstrated that pre-frontal electroencephalographic (EEG) cordance, a quantitative EEG (QEEG) parameter, predicts successful response to fluoxetine antidepressant therapy. Greenwald et al. in U.S. patent application Ser. No. 10/337,088 described the use of EEG indices using bispectral features to assess the severity of depression and to predict response to antidepressant phannacological treatment. It has been reported that side effect burden, characterized as the mean number of side effects per clinical visit, correlated with changes in an EEG index (prefrontal cordance) during the placebo lead-in period in patients receiving antidepressant treatment, but not in a placebo control group.
Others have observed that abnonnal electroencephalographic (EEG) activity has been associated with various psychiatric disorders and behaviors, including depression, suicide, and aggression and reported that differences in the intrahemispheric distribution of EEG alpha band power (alpha asymmetry), particularly over posterior regions of the scalp, differed between adolescent female suicide attempters and matched controls. Specifically, the controls exhibited greater EEG alpha band power over right than left hemispheres as compared to suicide attempters. Note that this study was not a prediction of the risk of suicidal behavior, but an observational study of EEG pattems conducted subsequent to suicide attempts. Several researchers have reported that paroxysmal EEG abnormalities increase the risk of suicide in patients.
The present invention is a system and method of deriving and computing features and indices that predict the likelihood
of psychological and neurological adverse events such as suicidal thoughts and/or actions. The method of the present invention further predicts the likelihood of suicidal thoughts and/or actions prior to and or during treatment for psychological disease. To obtain such features and indices, power spectrum and time domain values are derived from biopotential signals acquired from the subject being tested. The system and method identify people who are likely to experience changing, especially worsening, symptoms of psychological and neurological adverse events such as suicidal thoughts or actions and who therefore may be at risk (e.g. suicide).
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram of the system of the present invention for predicting adverse events during treatment of psychological and neurological disorders.
FIG. 2 is a flow chart of the steps of the method of the present invention.
FIG. 3 is an error bar chart showing the values of the Index Pred2 for the Worsening Suicide Ideation (SI) and Not Worsening SI groups, stratified by antidepressant treatment.
FIG. 4 is an error bar chart showing the value of Pred2 vs. the maximum change from baseline ob served in Ham-D item 3 during the first four weeks of treatment.
FIG. 5 is an error bar chart showing the baseline value of the left-minus-right relative theta+alpha asymmetry feature (BDRTAS12) for the Worsening SI and Not Worsening SI groups, stratified by antidepressant treatment.
FIG. 6 is a scatter plot of left-minus-right relative theta+ alpha asymmetry measured at baseline (BDRTAS12) and at 1 week (DRTAS12).
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
Referring to FIGS. 1 and 2, a preferred embodiment of the present invention shown in FIG. 1 incorporates a Data Acquisition Unit (DAU) 20 that is used to acquire an EEG signal in step 22 from a subject 10 for subsequent processing. The DAU 20 typically consists of a computer system with an integral analog-to-digital (A-D) converter 25 and a set of electrodes that is representatively shown placed on the scalp of a subject 10. While only a single electrode 15 is shown, any montage of electrodes used to obtain EEG signals may be used in the invention. The A-D converter 25 is used to transform in step 24 the analog EEG signals obtained from the electrodes 15 into a sampled set of signal values that may then be analyzed by the processor 35 of a Data Computation Unit (DCU) 30. The DCU 30 incorporates a processor 35 and a communications device that receives the sampled values from the DAU 20. In the preferred embodiment, the processors of the DAU 20 and DCU 30 are one and the same. In an altemate embodiment, however, the DAU 20 may acquire the EEG signals and transmit the sampled EEG signals over a communications link to a remote DCU 30. Such a communications link may be a serial or parallel data line, a local or wide area network, a telephone line, the Intemet, or a wireless cormection. The clinician conducting the assessment may communicate with the DCU 30 using a keyboard 40 and display device 50. In the altemate embodiment that utilizes a DCU 30 remote from the DAU 20, an additional keyboard and display device may be attached to the DAU 20 for the use of the clinician.
After the DCU 30 receives the sampled values from the DAU 20, the DCU 30 first examines in step 26 the sampled EEG signals for artifact arising from patient movement, eye