Clinical significance of neurological soft signs in schizophrenia: Factor analysis of the Neurological Evaluation Scale

Abstract

Background

Nonlocalizing neurologic deficits detectable by clinical evaluation–“soft signs”–are a robust finding in patients diagnosed with schizophrenia, but their conceptual and neuroanatomical correlates remain unclear. The purpose of this study was to evaluate the organization of these deficits and their clinical correlates using the Neurological Evaluation Scale (NES).

Methods

Ninety-three male veterans with schizophrenia and schizoaffective disorder were evaluated using a detailed clinical assessment that included the NES, the Extrapyramidal Symptom Rating Scale, the Abnormal Involuntary Movement Scale (AIMS), the Barnes Akathisia Scale, the Positive and Negative Syndrome Scale, the Wisconsin Card Sorting Test (WCST), the Schedule for the Deficit Syndrome (SDS), and the Digit Symbol Substitution Task (DSST).

Results

Four factors explained 73% of the variance and had distinct clinical and neuropsychological correlates. Factor 1 reflected deficits involved with memory and sensory integration, and was associated with lower PANSS positive and higher AIMS scores. Factor 2 reflected impairments in motor control, and was associated with lower intelligence, more cognitive deficits, and deficit-syndrome schizophrenia. Factor 3 was related to lower intelligence and more perseverative errors on the WCST. Factor 4 was related to increasing age, more extrapyramidal symptoms, more perseverative errors, and worse scores on the DSST.

Conclusions

Neurologic deficits in schizophrenia have an intrinsic organization that appears to have clinical significance, highlighting the continued utility of the NES in studies of neurological deficits in schizophrenia patients. The theoretical underpinning of this organization remains unclear.

Introduction

One straightforward, inexpensive method of investigating brain dysfunction in schizophrenia is through the bedside assessment of neurological abnormalities with a standard neurological examination. Neurological abnormalities are traditionally classified as “hard signs”–impairments in basic motor, sensory, and reflex behaviors, which do not appear to be affected in schizophrenia–and “soft signs”, which refer to more complex phenomena such as abnormalities in motor control, integrative sensory functions, sensorimotor integration, and cerebral laterality (Boks et al., 2000, Hollander et al., 1991, Manschreck and Ames, 1984, Ovsiew, 1992). Neurological soft signs are neither indicative of dysfunction of a specific brain region nor part of a well-defined neurological syndrome.

Numerous studies over the last 40 years demonstrate that patients with schizophrenia and their family members have more soft signs than healthy controls and patients with other psychiatric diagnoses (Boks et al., 2000, Bombin et al., 2005, Chan et al., 2009). Prevalence rates for soft signs in schizophrenia range from 50% to 73%, compared with only 5% in controls. Family members of schizophrenia patients also manifest higher rates of soft signs (Compton et al., 2007). Positive symptoms tend not to be related to soft signs, whereas negative symptoms have been related to soft signs that reflect frontal (motor function) and parietal (sensory integration) functions (Bombin et al., 2005). Cognitive performance is partially linked with soft signs, but is also influenced in a way that soft signs are not by sociodemographic variables such as age, education, sex, and socioeconomic status (Bombin et al., 2005). Soft signs have been associated with multiple clinical features of schizophrenia, have been conceptualized as a vulnerability marker for schizophrenia, and may represent a phenotype useful in genetic studies.

Although soft signs are held to have little localizing value, this is not entirely true; for example, motor perseveration is associated with damage to the dorsolateral prefrontal cortex (Luria, 1965, Milner, 1964), grasp reflex localizes to the frontal lobes, and more recent studies indicate that soft signs have identifiable functional neuroimaging correlates (Chan et al., 2009, Rao et al., 2008, Schroder et al., 1995). However, their value lies more in that their presence indicates dysfunction within the distributed neural networks that underlie complex behaviors (Ovsiew, 1992). Thus, while most of the primitive reflexes (e.g. palmomental, snout, and glabellar reflexes) are not localizable, they do indicate cortical deterioration or diffuse cerebral dysfunction in patients diagnosed with schizophrenia (Youssef and Waddington, 1988). Soft signs may provide valuable prognostic information, as they may be associated with greater psychopathology (Hertzig and Birch, 1966, Larsen, 1964), more severe cognitive impairments (Arango et al., 1999, Faustman et al., 1988), and possibly poorer treatment response (Smith et al., 1999, Sweeney et al., 1991). They may also be a risk factor for the development of tardive dyskinesia (King et al., 1991, Youssef and Waddington, 1988).

Soft signs are traditionally organized into seven categories; 1) integrative sensory dysfunction, 2) motor incoordination, 3) impaired sequencing of complex motor tasks, 4) frontal release signs, 5) abnormal eye movements, 6) memory impairments, and 7) cerebral dominance (Heinrichs and Buchanan, 1988). A number of different structured instruments have been devised to assess soft signs: the Woods scale (Woods et al., 1986), the Condensed Neurological Examination (CNE) (Rossi et al., 1990), the Modified Quantified Neurological Scale (MQNS) (Convit et al., 1988), the Heidelberg Scale (Schroder et al., 1991), the Cambridge Neurological Inventory (CNI) (Chen et al., 1995), the Neurological Soft Sign Scale (Quitkin et al., 1976), the Brief Motor Scale (Jahn et al., 2006), and the Neurological Evaluation Scale (NES) (Buchanan and Heinrichs, 1989). All have their strengths and weaknesses. Neither the Woods scale, the CNE, the MQNS, nor the CNI has been previously subjected to factor analysis. The Brief Motor Scale is reliable, consistent, sensitive, and specific, but was unfortunately not available at the time the data for this study were gathered. The Heidelberg Scale has good test–retest and interrater reliability, but does not assess handedness, nor did its validation sample include measures of clinical characteristics or sociodemographic variables. We used the NES, which has good psychometric properties (although it lacks the test–retest reliability of some of the others), assesses a moderate number of soft signs (minimizing administration time while maximizing the number of signs assessed that are relevant to schizophrenia), and has been extensively utilized in other studies. It is a 25-item scale, some items of which are scored separately on both sides of the body, and was constructed with a conceptually based factor structure composed of three domains of functioning: 1) integrative sensory dysfunction, 2) motor incoordination, and 3) impaired sequencing of complex motor acts.

Factor analysis is an empirical technique for reducing data to underlying coherent subsets or factors that can be used to find latent variables among many observed variables by grouping together those with similar characteristics. The current study attempted to build on the soft signs literature by testing the hypothesis that the NES was comprised of distinct factors, amenable to factor analysis, that might reflect different aspects of brain dysfunction in schizophrenia and might therefore be associated with distinct clinical correlates. We predicted a correlation between NES and Wisconsin Card Sorting (WISC) scores, as noted by Mohr et al. (1996), and a correlation with the DSST, as increased soft signs have been linked to increased impairment on the DSST (Das et al., 2004).