Items in search results

• ARCHER 15-1113 UHF/VHF/FM 20 dB Signal Amplifier Antenna Booster - RadioShack

  • $17.49
  • or Best Offer
  • +$21.45 shipping

• Radio Shack Archer UHF/VHF/FM Amplifier model 15-1113 A Signal Amplifier

  • $9.99
  • Buy It Now
  • +$27.19 shipping

• New listing Radio Shack 15-1113A Signal Amplifier UHF VHF FM 117 VAC 60Hz 3.6W Archer

  • $10.00
  • or Best Offer
  • +$30.51 shipping

• Radio Shack 20dB Signal Amplifier UHF VHF FM 15-1113A Archer 117 VAC 60Hz 3.6W

  • $14.95
  • Buy It Now
  • +$30.00 shipping

• Radio Shack 20dB Signal Amplifier UHF VHF FM 15-1113A Archer 117 VAC 60Hz 3.6W

  • $16.60
  • or Best Offer
  • +$20.94 shipping

• Radio Shack Signal Amplifier 15-1113A 20dB UHF VHF FM 117 VAC 60Hz 3.6W Archer

  • $14.95
  • or Best Offer
  • +$24.72 shipping

• Archer UHF/VHF/FM Amplifier Model #15-1113

  • $6.01
  • or Best Offer
  • Shipping not specified

• Archer TV/FM Antenna Amplifier. UHF/VHF/FM 15-1113A

  • $4.30
  • 0 bids
  • +$24.97 shipping

• Archer UHF/VHF/FM Amplifier Model 15-1113

  • $14.95
  • Buy It Now
  • +$16.94 shipping

• Radio Shack Archer Amplifier UHF / VHF / FM MODEL 15-1113

  • $12.50
  • or Best Offer
  • Shipping not specified

• Archer UHF/VHF/FM Amplifier Model 15-1113A

  • $12.95
  • or Best Offer
  • +$67.25 shipping

• Radio Shack 20dB Signal Amplifier UHF VHF FM 15-1113A Archer 117 VAC 60Hz 3.6W

  • $22.99
  • Buy It Now
  • Shipping not specified

• New listing Vintage Radio Shack UHF/VHF/ FM High-Gain Signal Amplifier Model 15-1113B

  • $5.25
  • 0 bids
  • Shipping not specified

• Radio Shack 15-1113C 25dB Signal Amplifier (UHF VHF FM) w/FM Trap & Gain Control

  • $7.50
  • 0 bids
  • +$24.61 shipping

• 25dB Amplifier VHF UHF FM Variable Gain Antenna TV Signal Amp Reception SKY383

  • $37.49
  • Buy It Now
  • Shipping not specified

• Vintage Radio Shack 15-1113B 20dB Signal Amplifier UHF VHF FM 117 VAC 60Hz 3.6W

  • $17.50
  • Buy It Now
  • +$24.00 shipping

• Archer 15-1113A UHF/VHF/FM Amplifier

  • $25.00
  • Buy It Now
  • Shipping not specified

• Archer UHF/FM/VHF Coax Amplifyer

  • $14.99
  • Buy It Now
  • +$24.94 shipping

• Radio Shack 15-1113B UHF/VHF/FM Amplifier

  • $17.00
  • or Best Offer
  • Shipping not specified

• Archer 15-1113A UHF/VHF/FM Amplifier

  • $17.50
  • Buy It Now
  • +$12.95 shipping

• archer 4 channel UHF/VHF/Catv/FM distribution amplifier #15-1119

  • $2.99
  • Buy It Now
  • +$29.10 shipping

• New listing Radio Shack 20dB Signal Amplifier UHF VHF FM 15-1113A Archer 117 VAC 60Hz 3.6W

  • $11.99
  • 0 bids
  • Shipping not specified

• ARCHER 15-1113 VHF/UHF/FM 20 dB SIGNAL AMPLIFIER ANTENNA BOOSTER RADIO SHACK

  • $14.95
  • or Best Offer
  • +$25.81 shipping

• Vintage Aim Amplifier VHF UHF FM Model 14-4930

  • $13.99
  • Buy It Now
  • +$16.69 shipping

• Archer 15-1113B 20dB Signal Amplifier UHF VHF FM 117 VAC 60Hz 3.6W

  • $19.99
  • Buy It Now
  • +$12.99 shipping

• (Lot of 2) Archer / Centronics Signal Amplifier UHF VHF FM 117 VAC 60Hz - 3.6w

  • $12.95
  • Buy It Now
  • +$38.50 shipping

• Archer 15-1108 VHF/UHF/FM Amplifier Gain / FM Trap Feature

  • $9.85
  • or Best Offer
  • +$25.13 shipping

• TV UHF/VHF/FM ADJUSTABLE 20 DB AMPLIFIER RADIO SHACK (ARCHER) WITH FM TRAP

  • $22.95
  • Buy It Now
  • +$22.49 shipping

• Indoor UHF/VHF/FM Signal Amplifier

  • $5.00
  • Buy It Now
  • Shipping not specified

• (Lot of 2) RadioShack Archer #15-1116 2-way Signal Amplifier for VCR/VHF/CATV/FM

  • $19.95
  • or Best Offer
  • +$12.99 shipping

• New listing Archer VHF/UHF/FM Antenna Amplifier Power Supply Inserter 15-1124

  • $10.00
  • or Best Offer
  • +$30.51 shipping

• Archer 15-1119 4 Channel UHF/VHF/CATV/FM Distribution Amplifier 50-400 MHz

  • $6.74
  • Buy It Now
  • +$24.47 shipping

• Radio Shack Archer 1-input 75ohm / 4-output UHF/VHF/FM amplifier 15-1107

  • $15.00
  • Buy It Now
  • +$16.94 shipping

• 75 OHM UHF VHF FM Amplifier & Manual 120VAC 60 Hz Archer 15-1107 Radio Shack USA

  • $29.88
  • Buy It Now
  • Shipping not specified

• Winegard BC-382 15-db Gain FM/VHF/UHF Distribution Amplifier 300 Ohm Vintage

  • $55.00
  • Buy It Now
  • +$21.48 shipping

• Archer 75 OHM Uhf/vhf/fm Amplifier No 15-1107. 120 VAC 60 Hrz 3 W Max 92 M8 1 To

  • $13.99
  • or Best Offer
  • +$24.54 shipping

• UHF/VHF/FM Signal Amplifier + Switchable FM Trap NEW X9

  • $20.00
  • Buy It Now
  • +$20.89 shipping

• Archer UHF/VHF/FM Coaxial 2-way Splitter

  • $4.51
  • or Best Offer
  • Shipping not specified

• HD ANTENNA DISTRIBUTOR AMPLIFIER SIGNAL BOOSTER CABLE TV AMP UHF FM VHF GEMINI

  • $30.00
  • or Best Offer
  • Shipping not specified

• INDOOR TV AMPLIFIER SIGNAL BOOSTER ANTENNA HDTV COMPATIBLE VHF UHF FM RECEPTION

  • $18.66
  • Buy It Now
  • Shipping not specified

• Distribution Amplifier Booster Signal Reception Antenna to TV VHF/UHF/FM

  • $32.44
  • Buy It Now
  • Shipping not specified

• Radio Shack 15-1113B UHF/VHF/FM Amplifier

  • $30.00
  • Buy It Now
  • Shipping not specified

• 4-Way Signal Amplifier 10 dB UHF/VHF/FM NEW IN BOX

  • $12.00
  • or Best Offer
  • Shipping not specified

• STEALTHtenna UHF VHF Antenna Amplifier Off Air Outdoor Video Signal

  • $14.95
  • or Best Offer
  • Shipping not specified

• Archer Radio Shack MPN 15-1131 75 Ohm UHF VHF FM Amplifier For 4 Sets, Vintage

  • $17.95
  • Buy It Now
  • +$49.95 shipping

• Archer 15-1107 75 OHM UHF/VHF/FM Amplifier 120V 60Hz

  • $19.99
  • Buy It Now
  • +$18.34 shipping

• Pro Brand Uhf/vhf/fm Distribution Amplifier - 800mhz - Signal Amplifier - Eagle

  Aspen Distamp-25-gx (distamp25gx)
  • $32.53
  • Buy It Now
  • +$16.27 shipping

• Leviton Coaxial Signal Amplifier Model 48210-VA UHF VHF FM Coaxial Used

  • $9.99
  • Buy It Now
  • +$25.72 shipping

• HD ANTENNA DISTRIBUTOR AMPLIFIER SIGNAL BOOSTER CABLE TV AMP COMCAST UHF FM VHF

  • $34.99
  • Buy It Now
  • +$14.00 shipping

• Belkin 10dB Indoor FM/VHF/UHF Signal Amplifier, 'UL Listed' Excellent Quality!

  • $5.95
  • or Best Offer
  • Shipping not specified

15: A lost ball in the high weeds. You are too excited or clumsy to do something properly that requires manual dexterity.’All thumbs’ is an alternative form of the idiom. 86: All hat, no cattle (USA) When someone talks big, but cannot back it up, they are all hat, no cattle.(‘Big hat, no cattle’ is also used.). Example: If you.

Background. Neurological deficits after a stroke are commonly classified according to motor function for clinical decision making regarding discharge and rehabilitation. Participants in clinical stroke studies are also stratified by motor function to avoid a sampling bias. Objective. This post hoc analysis examined a suite of upper limb functional assessment tools to test the hypothesis that motor function of survivors of stroke can be stratified using 2 simple tests of manual dexterity despite the heterogeneity of the population. Methods. The functional ability of the more affected hand and arm was assessed for 67 hemiparetic patients, aged 18 to 83 years (mean ± standard deviation, 59.8 ± 14.0 years), at 1 to 264 months after a stroke (23.6 ± 39.6 months) using the Wolf Motor Function Test (WMFT), upper limb motor Fugl-Meyer Assessment (F-M), Box and Block Test (BBT), grooved pegboard test, and wrist range of motion. We tested the strength of our proposed stratification scheme with a hypothesis-driven hierarchical cluster analysis using standardized raw scores and dichotomous BBT and grooved pegboard test values. Results. The most salient discriminator between low and higher motor function was the ability to move >1 block on the BBT. Within the higher function group, the ability to place all 25 pegs on the grooved pegboard test discriminated between moderate and high motor function. The derived scheme was congruent with clinical observations. The WMFT timed tasks, F-M scores, and range of motion did not discriminate functional groups. Conclusions. Two simple unambiguous and objective tests of gross (BBT) and fine (grooved pegboard test) manual dexterity discriminated 3 groups of motor function ability for a heterogeneous group of patients after stroke.

Neurological deficits after a stroke are routinely categorized to assist the allocation of treatment options, discharge destination, rehabilitation, and long-term assistance. Tools such as the National Institutes of Health Stroke Scale, Barthel Index, modified Rankin Scale, and Functional Independence Measure are used to define broad classifications of a mild, moderate, or severe stroke,^1,2 particularly in the acute poststroke phase. Although these widely used tools assess multiple aspects of disability and outcomes, many are constrained by the compromise between measurement sensitivity and assessment time, and none specifically assesses upper limb motor function. Upper limb function is crucial for independence in activities of daily living and so remains a target of clinical rehabilitation trials. Motor stratification is necessary in such trials to prevent the potential for unbalanced study arms; yet, there is no standardized consensus approach or terminology.³

Active range of motion at the wrist and digits is commonly used to classify upper limb motor status, for example, when determining eligibility for constraint-induced movement therapy (CIMT).^4-6 These tests involve 1 to 3 repetitions of extension at the wrist and digits and may reflect the demands of the study intervention more than the diverse functional impairments of survivors of stroke. Patient heterogeneity, even when clinical signs and symptoms are similar,^7,8 is a difficult aspect of stroke research but one that must be accommodated to enable the generalization of trial outcomes to the wider population with stroke. Thus, sensitive assessment tools are needed not only to stratify participants in clinical trials but also to assess therapy outcomes and the efficacy of novel rehabilitation protocols.⁹

Newer methods of stratifying the motor function ability of patient cohorts have determined the delineating scores of single assessment tools. Woodbury and colleagues¹⁰ identified the Fugl-Meyer Assessment (F-M) scores that classified patients with mild, moderate, and severe upper limb motor impairment. However, such schemes may be constrained by the domains tested within the assessment tool: the F-M does not evaluate other aspects of motor function such as movement speed, strength, and dexterity. There is no currently available assessment or group of assessments that adequately measures survivors of stroke across the spectrum of motor impairment or all facets of upper limb function.^3,11-13 It has been suggested that the utility and sensitivity of different assessment tools depend on the functional status of the patient.^14,15 For example, the Wolf Motor Function Test (WMFT) is more sensitive for patients with higher motor function but has a floor effect (scoring the lowest possible score or an inability to complete the test) for patients with low motor function, and the F-M is more sensitive for patients with lower function but has a ceiling effect (scoring the highest possible score with little scope for further improvement) for patients with high function.^14,15 Thus, it is unlikely that any one tool can reliably stratify patients after a stroke.

This post hoc investigation examined upper limb functional assessment tools to identify the optimal method of stratifying survivors of stroke. The premise for this analysis stemmed from a clinical observation made during a study investigating the efficacy of upper limb rehabilitation after stroke. The primary hypothesis was that patients after a stroke could be stratified by the floor effects of the Box and Block Test (BBT) and grooved pegboard test so that patients with low motor function could not complete either test, those with moderate motor function could complete the BBT but not the grooved pegboard test, and those with high motor function could complete both tests. A corollary of this hypothesis was that single multiattribute tests such as the WMFT or F-M do not distinguish the functional status of patients across the spectrum of poststroke motor impairment, despite being specifically developed for use after stroke.^16,17 A secondary hypothesis was that active and passive range of motion of the wrist would not discriminate functional status. We identified motor functional ability using 2 simple tests of gross and fine manual dexterity: the BBT and grooved pegboard test, respectively. Unlike the WMFT and F-M, both tests require repetitive manipulation with subtle variations in movement trajectory. They are unambiguous (ie neither requires assessor judgment), are quick to administer, and do not require stroke-specific knowledge, but they reliably discriminated 3 strata of functional ability.

Sixty-seven patients (47 male, 20 female), aged 18 to 83 years (mean ± standard deviation, 59.8 ± 14.0 years) and at 1 to 264 months after a stroke (23.6 ± 39.6 months), were consecutively recruited through the outpatient units of St Vincent’s and Prince of Wales’ Hospitals in Sydney, Australia. All were hemiparetic with an upper limb deficit after a unilateral stroke in the territory of the middle cerebral artery. Inclusion criteria were (1) ≥14 years of age, (2) able to communicate in English, and (3) cognitively competent with a Mini-Mental State Examination score ≥24. Exclusion criteria were (1) comorbidities significantly affecting sensorimotor function, (2) receptive aphasia, and (3) unstable blood pressure. Assessments were conducted according to a standardized protocol by authors G.G.L. and C.T.S. and analyzed by author A.G.T.-B. Previously reported pilot data from 7 patients¹⁸ have been included in this novel analysis. All patients gave informed, written consent. This study was approved by St Vincent’s Hospital Human Research Ethics Committee and conducted in accordance with the Declaration of Helsinki.

Gross manual dexterity was assessed using the BBT in which patients move as many 2.5-cm blocks as possible in a 60-second timed trial using only the thumb and index finger.¹⁹ Patients who successfully moved ≥1 block attempted the grooved pegboard test (Lafayette Instrument, North Lafayette, IN) of fine manual dexterity, which measures the time taken to correctly orient and place 25 grooved pegs.²⁰ Passive and active range of motion (extension) of the wrist were assessed,²¹ and muscle resistance and spasticity were measured with the modified Ashworth²² and Tardieu²³ scales at the wrist, elbow, and shoulder.

Motor ability of the more affected hand and arm was assessed using the WMFT¹⁶ and the upper limb motor subscale of the F-M.¹⁷ Use of the more affected hand and arm in activities of daily living was assessed using the Motor Activity Log Quality of Movement Scale (MALQOM).^16,24 The WMFT includes 15 timed and 2 strength-based tasks that simulate activities of daily living from simple gross movements to complex fine motor tasks. The F-M assesses the ability to move in and out of synergy and to individuate movement in the shoulder, elbow, wrist, and hand. The MALQOM consists of 30 activities of daily living that are self-rated on a 6-point scale, with 0 representing an inability to complete the task using the more affected upper limb and 5 representing the same ability as before the stroke.

Poststroke functional stratification was determined using a series of hierarchical cluster analyses²⁵ in a commonly available statistics package (SPSS v20, IBM, Armonk, NY). Two hypothesis-driven hierarchical cluster analyses were performed to separate the 67 patients by upper limb motor function ability. Three clusters were specified a priori in accordance with clinical observation. The first analysis included the raw WMFT mean times, F-M scores, grooved pegboard test times, and BBT counts. These scores were entered in random order to reduce the potential for inadvertent bias and then standardized on a 0-to-1 scale, which maintains the relationship between scores. A time of 2000 seconds was arbitrarily chosen as the score for patients unable to complete the grooved pegboard test.

A second hypothesis-driven analysis was performed on the dichotomous BBT and grooved pegboard test scores. Dichotomous BBT scores were 0 and 1, where 0 represented 0 blocks moved and 1 represented ≥1 block moved. A grooved pegboard test score of 0 represented the inability to place all 25 pegs, and 1 represented all 25 pegs correctly placed. We compared the clusters derived by each analysis with our hypothesized allocations for each patient to establish the strength of the proposed classification system. The stratification criteria were consequently revised (see Results) so that patients who could move ≤1 block were classified with low motor function and those moving >1 block were classified as having moderate or high motor function. The amended classification criteria were tested with a third hypothesis-driven analysis in which dichotomous BBT scores were 0 and 1, where 0 represented ≤1 block moved and 1 represented >1 block moved. The definition of grooved pegboard test dichotomous scores remained unchanged.

To facilitate the use of this stratification scheme in the acute and subacute clinical setting, we determined the minimum number of tests required to accurately stratify the patients from this study. Cluster analyses were repeated using scaled scores for (1) the BBT and grooved pegboard test, (2) the WMFT and F-M, (3) the WMFT alone, and (4) the F-M alone.

Finally, to better understand the behavior of the clustering algorithms within our dataset, we conducted a hypothesis-free hierarchical cluster analysis. This parallel analysis provided a heuristic evaluation and included raw data for all assessments (n = 67) with the exception of active and passive range of motion (n = 60) and spasticity scales. Active and passive range of motion were excluded for 2 reasons. First, data were unavailable for 7 patients, and second, as outlined in the Discussion, range of motion may potentially be affected by increased muscle tone, pain, and assessor subjectivity. The Tardieu and modified Ashworth scales were also excluded because their subjective scoring is less resilient than other measures. Assessment score sets were entered in random order to avoid the potential for inadvertent bias, and data were standardized on a 0-to-1 scale. We used this hypothesis-free hierarchical cluster analysis to iteratively create 2, 3, 4, and 5 clusters. The derived 3-cluster model groups were compared with the amended hypothesis-driven hierarchical cluster analysis of dichotomous BBT and grooved pegboard test scores.

One-way ANOVAs with Holm-Sidak post hoc pairwise comparisons were used to compare differences between low, moderate, and high motor function groups for each assessment. Kruskal-Wallis 1-way ANOVAs with Dunn post hoc pairwise comparisons were used for data that were not normally distributed. Data are illustrated using means and 95% confidence intervals to facilitate comparisons with previous studies. Differences were considered significant when P < .05.

All patients attempted all tests with the exception of the grooved pegboard test. Of the 45 patients who moved ≥1 BBT block, 27 completed the grooved pegboard test. Passive and active range of motion of the wrist were included only after the trial began, and therefore, data are reported for 60 patients. The rank-ordered distribution of the WMFT timed tasks, F-M scores, active and passive range of motion of the wrist, MALQOM scores, and maximum grip strength results covered the spectrum of possible outcomes describing a nearly continuous distribution with evidence of floor and ceiling effects (Figures 1 and 2). A floor effect was evident on the WMFT for 5 patients who were unable to complete any timed task within the allotted 120 seconds (Figure 1A). Unlike the WMFT, the F-M was a more sensitive test for patients with low motor function. A ceiling effect was evident for patients with moderate and high function, with 3 patients scoring the maximum 66 points and 12 scoring ≥60 points (Figure 1B). The overlap between groups shown in Figure 1 suggests that no 1 test can be used in isolation to unambiguously classify motor function ability. Conversely, the rank-ordered distributions for the BBT counts and grooved pegboard test times shown in Figure 3 identified 2 distinct groups: those who could successfully perform the tests and those who could not (floor effect). From these results, we identified 3 qualitative levels of functional ability and tested our hypothesis using a series of hierarchical cluster analyses.

Figure 1. Results of the Wolf Motor Function Test (WMFT) and the Fugl-Meyer Assessment (F-M). Rank-ordered scores for (A) WMFT timed tasks and (B) F-M scores show continuous distributions with no clear boundary between low (black), moderate (gray), and high (white symbols) motor function. Horizontal dashed lines indicate the maximum score for each test; diagonal lines represent the classification boundaries according to patient numbers for each functional group after stratification by the Box and Block Test (BBT) and grooved pegboard test (23 low, 17 moderate, and 27 high motor function). Note that the different symbols illustrate functional group allocation as determined by hierarchical cluster analyses. The disparity between the dashed lines and the colored symbols indicates that patients would be allocated to different functional groups depending on the assessment used. (C) The WMFT timed tasks and (D) F-M scores for combined data (squares) and low (black circles), moderate (gray circles), and high (white circles) motor function groups with group means (triangles) and 95% confidence intervals.

Figure 2. Rank-ordered functional assessment scores. (A) Passive range of motion of the wrist, (B) active range of motion of the wrist, (C) maximal grip strength, and (D) Motor Activity Log Quality of Movement Scale (MALQOM) scores do not stratify patients into clear functional groups. The horizontal dashed line (D) indicates the maximum score of 150 for the MALQOM. Group boundaries (diagonal lines) and symbols are as for Figure 1.

Figure 3. Motor function stratification by the Box and Block Test (BBT) and grooved pegboard test. (A) The BBT distinguished patients with low motor function from those with moderate and high motor function. (C) The grooved pegboard test discriminated patients with high motor function from those with moderate and low motor function. Note that as the measurement scale is different in these 2 tests, better performance is indicated by the arrow. (B) The BBT and (D) grooved pegboard test scores plotted against rank-ordered Wolf Motor Function Test (WMFT) task times emphasize that both tests are required to identify 3 strata of motor function. The arrow (B) identifies the patient who moved 1 block on the BBT. Diagonal dashed lines emphasize the unambiguous classification of motor function groups when both tests are used in combination.

Archer 15 1263 Manual Dexterity Pdf

The initial hierarchical cluster analysis was conducted on raw data using mean WMFT times, F-M scores, BBT counts, and grooved pegboard test times. A second hypothesis-driven analysis was performed on the dichotomous BBT and grooved pegboard test scores. We compared the analysis allocations with our hypothesized allocations for each patient. A misclassification occurred when the allocations did not match. The single misclassification identified a patient with moderate motor function who moved 1 BBT block but had slow WMFT times (highlighted in Figure 3B). The level of dexterity in addition to poor movement speed clearly suggests low motor function in accordance with clinical observation.

This misclassification prompted us to amend our stratification criterion so that patients who could move ≤1 block were classified with low motor function and those moving >1 block were classified as having moderate or high motor function (see Methods). We then tested our amended classification criteria on a third hypothesis-driven analysis. The 3 clusters of patients were the same as those generated by the first hypothesis-driven analysis of raw scores.

We used a series of hypothesis-free hierarchical cluster analyses to create 2, 3, 4, and 5 clusters. The 3-, 4-, and 5-cluster models all identified 3 principal clusters. The fourth cluster showed no coherent functional grouping, and the fifth cluster contained a single patient. The 2-cluster model identified a high function group and a lower function group. However, the lower function group included patients with both low and moderate movement ability.

The classifications proposed in this 3-cluster model were compared with the amended hypothesis-driven hierarchical cluster analysis of dichotomous BBT and grooved pegboard test values. The group allocations of the amended hypothesis-driven analysis were the same as the hypothesis-free analysis, thus confirming the strength of our proposed stratification system.

The difference between group medians was significant for all assessment tools (P < .001), with significant between-group differences (P < .05) for the WMFT timed tasks, F-M, MALQOM, and BBT (Table 1). The post hoc pairwise comparisons for the WMFT strength tasks, grooved pegboard test, and range of motion measures revealed significant differences between low and high motor function and low and moderate motor function (both P < .05) but not between moderate and high motor function. The pairwise comparisons for spasticity scales were significant between low and high motor function groups at all joints and moderate and high motor function groups at the elbow (all P < .05).

In this study, we developed a novel scheme to stratify the upper limb motor functional status of patients after a stroke based on performance on the grooved pegboard test and BBT with the more affected side. These 2 dexterity measures are standardized, quantifiable, and reproducible.^26,27 Moreover, they are relatively quick and simple to administer and when used in combination unambiguously and objectively differentiate patients with low, moderate, or high motor function. Our results from a suite of functional assessments emphasize that no single test alone discriminates upper limb functional status across the spectrum of poststroke impairment. This reflects the heterogeneity of upper limb impairment in addition to the multifaceted nature of upper limb function that incorporates dexterity, range of motion, strength, and coordination.

Classification into well-defined functional groups is important for rehabilitation management²⁸ to optimize therapy selection, dose, and intensity. In clinical studies, active range of motion at the wrist and digits is commonly used to stratify patients with mild to moderate stroke into lower and higher function groups. For example, in CIMT trials,^5-7 patients with high motor function had ≥20° active extension at the wrist and ≥10° at each metacarpophalangeal and interphalangeal joint. Patients with lower function had ≥10° active extension at the wrist, thumb, and 2 additional digits with 3 repetitions of each movement within 60 seconds.^5,6 Although patients with <10° active range of motion are not usually considered suitable for CIMT, a modified program has been implemented in patients with very low motor function.²⁹ In this instance, a task-based approach was used to identify suitable patients, namely, a single attempt at picking up and releasing a rag. Each of these classification systems was designed to identify patients who could not safely complete CIMT.

Active and passive range of motion of the wrist did not classify functional ability in the current study. We did not attempt to measure digit extension due to spasticity and hypertonicity in both the proximal interphalangeal and metacarpophalangeal joints. As far as we can ascertain, if the patients in the current study were classified according to active range of motion at the wrist and digits, those with moderate and high motor function would have been classified as having high motor function, and those with low motor function would not have been eligible for CIMT and the majority of other clinical studies.

In this study, the most salient discriminator between low and higher motor function was the ability to move >1 block on the BBT, while within the higher function group, the ability to place all 25 pegs on the grooved pegboard test discriminated between moderate and high motor function (Figure 4). Previously, the BBT and grooved pegboard test were deemed unsuitable for patients with low function due to their limited dexterity,^19,30,31 but this study demonstrates the utility of employing the floor effects of these tests to stratify patient cohorts. A number of peg tests are used to measure fine motor control after stroke including the 9- and 10-hole peg tests.^32,33 The grooved pegboard test²⁰ adds task complexity as the pegs must be correctly oriented before placement. Compared to active and passive ranges of motion, the BBT and grooved pegboard test are simple, standardized tests that are less likely to be influenced by measurement error and the effect of assessor intervention, particularly in the presence of spasticity and hypertonicity after stroke.

Figure 4. Schematic representation of the stratification process. Patients demonstrating a floor effect on the Box and Block Test (BBT) (≤1 block moved) are classified with low motor function and do not attempt the grooved pegboard test. The remaining patients attempt the grooved pegboard test, and those demonstrating a floor effect on this test (ie unable to complete the test) are classified with moderate motor function. Patients with no floor effects on either test (ie, complete both the BBT and grooved pegboard test) are classified with high motor function. The score refers to the dichotomous score for each test used in the hierarchical cluster analyses (see text for details).

No assessment tool was sufficiently sensitive to measure functional impairment across the poststroke spectrum. Multiattribute tests such as the WMFT and F-M demonstrated floor and ceiling effects, respectively, despite being designed for use after stroke.^14,15 A recent study¹⁰ quantified F-M scores to define patient groups for mild, moderate, and severe upper limb movement deficits. This study identified a score of 19 ± 2 as the boundary between severe and moderate impairment and a score of 47 ± 2 as the boundary between moderate and mild impairment. Although the mean F-M score for the moderate motor function group in the current study of 51.4 ± 3.5 (range, 42-60) was higher than that of Woodbury and colleagues,¹⁰ these patients lacked the fine dexterity to complete the grooved pegboard test and so did not meet our criteria for the high motor function group. This is not surprising given that the F-M does not specifically test fine manual dexterity.

Our hypothesis-free analysis incorporated 5 tests of motor ability that together comprehensively assess many features of upper limb impairment after stroke. The allocations generated by this hypothesis-free analysis were the same as those generated solely by the dichotomous BBT and grooved pegboard test values. Thus, these 2 measures of dexterity provide a quick stratification that is as effective as a lengthy and comprehensive assessment. In our experience, one of the largest differences between those with moderate and high function is the ability to handle smaller items (fine manual dexterity). Those with some range of motion, movement speed, strength, and synergistic ability but lacking fine dexterity struggle with everyday tasks, that is, those with moderate motor function. In our analyses, most assessment tools distinguished the low motor function group from the higher motor function group due to floor effects for the former, but the distributions in Figures 1 and 2 emphasize the absence of a discrete boundary between moderate and high motor function. The apparent misclassifications highlighted by these distributions emphasize the diversity of poststroke deficits that may be compounded by ataxia, bradykinesia, and spasticity. Figure 3B demonstrates the extent to which the 6 patients with good movement speed and gross movement ability lacked fine manual dexterity. Poor manual dexterity is a substantial impediment to independence in activities of daily living.³⁴

Our classification system uses the floor effects on the BBT and grooved pegboard test to discriminate the level of upper limb motor function. It was confirmed by a series of hierarchical cluster analyses. These analyses were chosen as a viable method to assist in identifying a subset of tests that provided efficient discrimination of a complex phenomenon. A number of alternate statistical approaches are available, but as classification is a difficult statistical problem, there is no perfect method. We were initially surprised that the hypothesis-free analysis did not reveal an additional cluster of patients with very low motor function. Presumably, this reflects the lack of sensitivity of any of the tests used in this study for patients with very low functional ability, and we know of no appropriate tests for these patients. The low motor function group in this study encompasses patients with both low and very low motor function.

The results of this study confirm that the WMFT more accurately reflects the functional ability for patients with moderate and high motor function with floor effects for those with low motor function, while the F-M is more appropriate for patients with low motor function with ceiling effects for those with moderate and high functional ability.^14,15 In addition, neither test displayed clear boundaries between functional groups and particularly for those with moderate motor function. The measures of dexterity were the most salient for stratifying patients into motor function groups. However, these 2 tests should not be used alone to assess motor status or improvement. It is evident that timed tests such as the WMFT, BBT, and grooved pegboard test are preferable for measuring functional ability and improvements in patients with moderate and high motor function. Measurements of gross movements, body awareness, and use of the more affected side such as the F-M and MALQOM may be better for patients with low motor function. Without using the scheme devised in this study, we would have overestimated the ability of the patients with low motor function and underestimated the ability of the patients with moderate and high motor function. We believe that it is the timed repetition of tasks with variable start and end points, variations in movement trajectory, and the involvement of multiple joints that contribute to the robustness of our classification scheme. Isolated movements like those tested in active and passive range of motion may not adequately reflect functional upper limb motor ability.

This post hoc investigation originated from observations made during a suite of functional assessments before an upper limb therapy program. Thus, this study represents the testing of our hypothesis and not an a priori design. The assessment tools were selected and testing completed before this analysis was conceived. This minimizes the potential for measurement bias as the assessors were naive to this analysis at the time of testing. Although further work is needed to test this stratification scheme against a broader range of assessment tools, our results provide good evidence for a novel stratification system of motor function after stroke.

In conclusion, when used in combination, the BBT and grooved pegboard test objectively and unambiguously stratified patients after a stroke into 3 discrete motor function groups. These tests encompass multiple facets of functional ability with repeated and subtly varied movements. These measures can be administered quickly, inexpensively, and with little training. This scheme can be used to stratify the heterogeneous population with stroke into motor function groups to minimize study imbalance, the underestimation or overestimation of functional ability, and changes in therapy-induced movement recovery.

The authors are grateful to James Scandol for statistical advice.

Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding
The author(s) received the following financial support for the research, authorship, and/or publication of this article: This study was funded by the National Health and Medical Research Council of Australia and the New South Wales Office of Science and Medical Research, Australia.

Archer 15 1263 Manual