Acta Med. Okayama, 2024
Vol. 78, No. 2, pp. 163‑170
CopyrightⒸ 2024 by Okayama University Medical School.

Original Article

http://escholarship.lib.okayama-u.ac.jp/amo/

The Impact of Light Touch and Pin Prick on Functional Outcomesin Patients with Traumatic Spinal Cord Injury
Takayuki Deguchia,b＊, Kanae Kandab, Kazunari Furusawac, Nlandu Roger Ngatub,and Tomohiro HiraobaDepartment of Rehabilitation, Kagawa Rosai Hospital, Marugame, Kagawa 763-0013, Japan,
Department of Public Health, Faculty of Medicine, Kagawa University, Miki, Kagawa 761-0793, Japan,c
Department of Rehabilitation Medicine, Kibikogen Rehabilitation Center for Employment Injuries,
Kibichuo, Okayama 716-1241, Japanb

A spinal cord injury (SCI) can cause severe lifelong functional disability and profoundly affect an individual’s
daily life. We investigated the prediction of patients’ post-SCI functional outcomes by evaluating sensory scores
rather than motor scores, as the latter’s association with functional outcomes is well established. We examinedpatients’ responses to a light touch (LT) and pin prick (PP) at admission and the response data’s usefulness as
predictors of functional outcomes (i.e., ability to perform activities of daily living) at discharge. This exploratory observational study used data from the Japanese National Spinal Cord Injury Database (SCI-J). Data
from 3,676 patients who met the inclusion criteria and were admitted for an SCI between 1997 and 2020 wereanalyzed. The motor score of the Functional Independence Measure (mFIM) at discharge was used as an index
of functional outcome. A multiple regression analysis revealed that the mFIM was associated with both the LT
response (β = 0.07 (0.01), p < 0.001) and the PP response (β = 0.07 (0.01), p < 0.001) at admission. The false discovery rate log-worth values for LT and PP were 6.6 and 8.5, respectively. Our findings demonstrate that LT
and PP scores at admission can help predict patients’ functional outcomes after an SCI, although the magnitudeof their contributions is not high.
Key words: functional independence measure, light touch, pin prick, spinal cord injury, Japanese National Spinal
Cord Injury DatabaseA

spinal cord injury (SCI) can cause severe lifelong
disability, profoundly affecting an individual’s
daily life due to complete or incomplete paraplegia or
quadriplegia. The global incidence of SCIs is estimatedto be 40-80 per million people annually, with the SCIs
due mostly to traffic accidents, falls, and violence;these figures indicate that approx. 250,000-500,000
people are afflicted by an SCI each year [1]. The estimated incidence of SCI in Japan is 49 individuals per
million people per year, which has a considerable
Received August 23, 2023; accepted November 30, 2023.
Corresponding author. Phone : +81-877-23-3111; Fax : +81-877-24-1147
E-mail : td.krh.rpt@gmail.com (T. Deguchi)＊

impact on the country’s society [2 , 3].
Early intervention is associated with improved outcomes in SCI [4], and early initiations of preventive
measures and treatment can have beneficial effects on
SCI patients. In addition, the patient’s early and active
mobilization is a key principle of rehabilitation [5]. The
prediction of patients’ functional outcomes is essential
in rehabilitation planning for patients who have incurredan SCI, and such a prediction requires an accurate neurological examination conducted within 72 hours to
4 weeks after the injury [6 , 7]. The most commonly used
Conflict of Interest Disclosures: No potential conflict of interest relevantto this article was reported.

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Deguchi et al.

tool to predict post-SCI outcomes is the International
Standard for Neurological Classification of Spinal Cord
Injury (ISNCSCI), which is used together with theAmerican Spinal Injury Association (ASIA) Functional
Impairment Scale (AIS) [8]. The ISNCSCI includes a
motor component, i.e., the ASIA Motor Score (AMS)
that is used to assess patients’ motor function and a sensory score used to assess their sensory function. The
AMS evaluates muscle strength based on the patient’s
achievement on the Muscle Manual Test (MMT), andthe sensory score includes Light Touch (LT) and Pin
Prick (PP) scores, which evaluate a patient’s responses
to touch and pain.
The association between patients’ motor scores atadmission and their functional outcomes, i.e., the ability to perform activities of daily living, has been wellestablished [9-11]. However, few studies have evaluated sensory scores in this context, particularly for LT
and PP. We conducted the present study to investigate
the ability of SCI patients’ responses to LT and PP at
admission to predict functional outcomes at discharge.

Patients and Methods
Data sources. This was an exploratory observational
study using a patient database and performed in accord
with the Strengthening the Reporting of Observational
Studies in Epidemiology (STROBE) statement checklist.
The database used in this study was the Japan Spinal
Cord Injury Database (SCI-J) (<https://www.kibirihah.
johas.go.jp/200_SCI_DB/top.html>; accessed July 23,2023). The SCI-J was established in 1997; to date, 30
hospitals and two SCI centers have participated in thecollection of data on traumatic SCI cases throughout
Japan. The SCI-J database includes the following
patient information: demographic information (ageand sex), injury characteristics (mechanism and neurological level of injury), functional outcomes (level ofdaily activities), and discharge outcomes (discharge tothe patient’s home or a rehabilitation facility).
The study population was comprised of patients withSCI-J-registered cases who had been hospitalized
between 1997 and 2020. A total of 5,774 cases wereregistered in the SCI-J database, among whom weselected 5,413 cases after excluding deaths and cases withdata errors. Of these, 3,676 cases that met the following
criteria were included in the analysis: age ≥ 18 years,
ASIA AIS grade A-D on admission, and time fromActa Med. Okayama Vol. 78, No. 2

injury to admission ≤ 270 days; this period was usedbecause the greatest part of neurological recovery generally occurs within 9 months of the injury, after which
the rate of improvement declines rapidly [7 , 12].
Patients with missing data were excluded (Fig. 1).
Variables. The Light Touch score (LT) at admission and the Pin Prick score (PP) at admission wereused as explanatory variables. LT and PP are methodsof measuring sensory function in individuals with SCIs
and are used in the ASIA AIS to determine the AIS
grade and injury level [8]. These sensory tests arehighly reliable and reproducible among evaluators [13].
The LT and PP measurements followed the ISNCSCI
guidelines [14 , 15], which are the gold standard for the
documentation of SCI levels and severity. Each patient’s
LT and PP responses were rated from 0 to 2 in each of
the 28 dermatomes (from C2 to S4-5) on both sides ofthe body (0 = absent, 1 = altered [diminished or partial
sensation, including hyperesthesia], 2 = normal or
intact [similar to the cheek]); the higher the number,the more sensation was retained. The combined maximum score on both sides is 112.
The outcome variable was the Functional Independence Measure (FIM) at discharge as the functional
outcome representing the ability to perform activities ofdaily living [16], for which the motor score of the FIM(mFIM) was used [11]. The mFIM is composed of four
items: (i) self-care (eating, grooming, bathing, dressing-upper body changing, dressing-lower body changing, toileting), (ii) sphincter control (bladder management, urinary management, bowel management,
defecation management), (iii) transfer, and (iv) locomotion (walk/wheelchair, stairs). Each item is scoredon a scale of 1 to 7; the higher the score, the greater the
degree of independence. The maximum possible scoreis 91.
The following covariates were used: the ASIA motorscore (AMS) at admission, the AIS grade at admission,
the FIM cognition score (cFIM) at admission, age (< 65or ≥ 65 years), sex, level of injury (cervical/below thoracic), injury mechanism (fall, fall from a height, traffic accident, sports, other), presence/absence of central cord injury, presence/absence of bone injuries tothe spine, and comorbidities (diabetes, heart disease,lung disease, and renal disease). We used the Japaneseversion of the FIM (ver. 3.0), with culturally relevant
modifications for some items [17-20]. Age was definedas the patient’s age at admission, and we divided theImpact of Sensory Scores on SCI Outcomes

April 2024

165

Cases registered in the Spinal Cord Injury Database of Japan (n = 5,774)
Excluded (n = 361)
・Admissions before 1997 (110)・Deaths (89)・Incorrect entries (162)Cases admitted between 1997 and 2020 (n = 5,413)

Excluded (n = 1,737)
・< 18 year old (151)
・AIS Gradeb E (481)・Days from injury to Admission > 270 days (225)・Incomplete data
AISA motor / sensory score (324)FIM (73)
Level of injury (169)
Bone injury / Comorbidity (314)

Subjects included in the analysis (n= 3,676)

Fig. 1

Flowchart of patient selection based on the study inclusion and exclusion criteria.

patients into younger (< 65) and older (≥ 65) age groups
because the older the patient, the lower the mFIM has
been during follow-up [21]. We classified the patients’level of injury into two groups: cervical (quadriplegic)
and thoracic and below (paraplegic). Central cord
injury is one of the clinical syndromes associated with
SCI, and because it has a relatively good prognosis, we
divided the patients into two groups according to thepresence or absence of central cord injury [22 , 23].
Statistical analyses. Data related to continuous
variables are expressed as means and standard deviations, whereas those in relation to categorical variables
are expressed as proportions. To determine the relationships between explanatory and outcome variables,
we used Student’s t-test for the comparison of means foroutcome variables that had two strata; a one-way analysis of variance (ANOVA) was used when the outcome
variable had three or more strata. A multiple regression
analysis was performed to determine whether thepatients’ LT and PP data were associated with theirmFIM scores. We also created analysis of covariance(ANCOVA) models considering LT at admission and PP
at admission, as follows.
・LT model: LT at admission + AMS at admission + cFIM at admission + sex + age category +injury mechanism+AIS at admission+level of
injury + central cord injury + bone injury + diabetes + heart disease + lung disease + renal disease.
・PP model: PP at admission + AMS at admission +cFIM at admission + sex + age category + injury
mechanism + AIS at admission + level of injury +central cord injury + bone injury + diabetes + heartdisease + lung disease + renal disease.
We obtained the false discovery rate (FDR) logworth to assess the order of the strength of the relationships between the covariates and the patients’ mFIM
scores at discharge. The statistical analysis was performed with JMP® Pro ver. 16.1.0 (SAS, Cary, NC,
USA). The statistical tests were two-sided and performed with a significance level of 5%.
As this was an exploratory study using an existing
database, no calculation of the required sample size was
performed.
Ethical considerations.
This study was approvedby the Ethics Committee of Kagawa Rosai Hospital of
the Japan Labor Health and Safety Organization(approval no. R4-30). Permission to use the SCI-J
database was obtained from the National Spinal Cord
Injury Database Management Steering Committee. Allanalytical procedures were performed in accord with theprinciples of the Declaration of Helsinki.

Results
The patients’ characteristics. Of the 3,676 patients,
84% were male and 72% were < 65 years of age. The
most common mechanisms of injury were a fall from aheight (34%), a traffic accident (32%), another type of

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Acta Med. Okayama Vol. 78, No. 2

fall (15%), and sports (6%). The AIS at admission was
Grade A in 33% of the patients, Grade B in 11%,
Grade C in 25%, and Grade D in 31%, with Grade A
accounting for one-third of the patients. Regarding thelevel of disability, 71% of the injuries were at cervicallevel and 57% of the patients had bone injuries.
Twenty-one percent of the patients had a central cord
injury. In terms of comorbidities, 13% of the patients
had diabetes, 7% had heart disease, 4% had lung disease, and 2% had renal disease. The mean mFIM scores
Table 1at admission and discharge were 30.1 and 58.0, respectively, demonstrating that the patients’ mFIM scores
improved during their hospitalization. The mean LT
and PP scores at admission were 66.4 and 62.4 points,
respectively (Table 1).
Bivariate analysis. The patients’ LT and PP responses
at admission were significantly associated with sex(p < 0.0001), age category (p < 0.0001), injury mechanism (p < 0.0001), AIS at admission (p < 0.0001), levelof injury (p < 0.0001), central cord injury (p < 0.0001),

Characteristics of the subjects and light touch and pin prick scores at admission and mFIM at discharge
Light touch scoreat admission％

mean (SD)

3,676

100

66.4 (32.0)

Female
Male

582
3,094

16
84

72.0 (32.2)
65.3 (31.8)<.000168.3 (34.5)
61.3 (33.3)<.000157.8 (1.2)
58.1 (0.5)

0.808≧ 65 years< 65 years

2,658
1,018

72
28

65.2 (31.3)
69.6 (33.5)<.0001

61.1 (32.9)
65.9 (35.0)<.000162.0 (0.5)
47.7 (0.9)<.0001

Mechanism of injury

Fall
Falls from heightTraﬃc accident
SportsOthers

568
1,232
1,166
232
478

15
34
32
6
13

74.2 (31.3)
65.8 (32.4)
62.7 (32.0)
62.9 (29.9)
69.4 (30.8)<.000170.5 (33.7)
61.7 (33.6)
58.2 (33.4)
57.8 (31.9)
67.1 (32.3)<.000155.4 (1.2)
54.8 (1.2)
59.6 (0.8)
64.0 (1.9)
62.7 (1.3)<.0001

AIS at admision

A
B
C
D

1,205
403
911
1,157

33
11
25
31

41.7 (26.4)
62.4 (26.7)
73.2 (26.3)
88.2 (24.1)<.000139.6 (26.7)
52.3 (29.4)
67.3 (29.3)
85.9 (26.7)<.000146.2 (0.7)
46.0 (1.3)
53.8 (0.8)
77.8 (0.7)<.0001

Level of injury

CervicalBelow thoracic

2,626
1,050

71
29

62.7 (33.6)
75.8 (25.0)<.000157.9 (35.1)
73.6 (26.1)<.000151.6 (0.5)
74.0 (0.8)<.0001

Central cord injury

Yes
No

786
2,890

21
79

76.1 (29.7)
63.8 (32.0)<.000174.0 (32.0)
59.3 (33.3)<.000165.6 (27.0)
55.9 (28.8)<.0001Bone injury

Yes
No

2,103
1,573

57
43
0

62.9 (32.4)
71.2 (30.8)<.000158.9 (33.6)
67.1 (32.9)<.000158.8 (0.6)
57.0 (0.7)

0.058

Diabetes

Yes
No

475
3,201

13
87

69.0 (32.6)
66.0 (31.9)

0.062

64.1 (33.9)
62.2 (33.5)

0.300

50.6 (1.3)
59.1 (0.5)<.0001

Heart diseases

Yes
No

243
3,433

7
93

69.6 (31.3)
66.2 (32.0)

0.148

65.3 (33.0)
62.2 (33.6)

0.205

49.9 (1.8)
58.6 (0.5)<.0001Lung diseases

Yes
No

133
3,543

4
96

62.3 (33.7)
66.6 (31.9)

0.156

57.8 (34.9)
62.6 (33.5)

0.101

48.3 (2.5)
58.4 (0.5)<.0001

Renal diseases

Yes
No

89
3,587

2
98

68.9 (32.8)
66.3 (31.9)

0.397

66.5 (34.0)
62.3 (33.5)

0.202

53.7 (3.1)
58.1 (0.5)

0.154

Sex
Age

mean (SD)P-valuemFIM
at discharge

ｎ
Total

P-value

Pin prick scoreat admission

62.4 (33.6)

mean (SD)P-value

58.0 (28.7)

SD, standard deviation; AIS, ASIA impairment scale; mFIM, motor scale of Functional Independence Measure; cFIM, cognition scaleof Functional Independence Measure; AMS, ASIA motor score.

Impact of Sensory Scores on SCI Outcomes

April 2024

and bone injury (p < 0.0001), with the patients withmore severe injuries tending to have lower LT and PP
scores (Table 1).
Multivariate analysis results. In the multivariate
analysis, analytical models were created for LT and PP.
In the LT model, LT on admission was associated withthe mFIM score at discharge (β = 0.07, standard error[SE] = 0.01; p < 0.001). Significant associations werealso revealed for age, injury mechanism, AIS score on
admission, level of injury, central cord injury, bone
injury, diabetes, heart disease, AMS score on admission, and cFIM score on admission. In the PP model,
PP on admission was associated with the mFIM score atdischarge (β = 0.07, SE = 0.01; p < 0.001), and significant associations were also observed for age, injury
Table 2mechanism, AIS score on admission, level of injury,
central cord injury, bone injury, diabetes, heart disease, AMS score on admission, and cFIM score on
admission. The variance inflation factor (VIF) was low
in both models (Table 2).
We identified the FDR log-worth of each factor inorder to determine the magnitude of the factors’ associations. In the LT model, the AMS score on admission
was the largest contributor (236.5), followed by age(38.0), level of injury (24.4), and cFIM on admission(19.1). The LT response on admission was 6.6, and its
contribution was not very high (Fig. 2). In the PP
model, AMS on admission was also the largest contributor at 226.2, followed by age (38.7), level of injury(23.8), and cFIM on admission (19.5), whereas the PP

Association of LT, PP and mFIM at discharge
Multivariate analysis: LT Model

Variables

β (SE)

P-value

VIF

LT score at admission
PP score at admission
AMS at admission
cFIM at admission

0.07 (0.01)<.0001

2.2

0.71 (0.02)
0.48 (0.05)<.0001<.0001

Multivariate analysis: PP Modelβ (SE)

P-value

VIF

3.9
1.1

0.07 (0.01)
0.70 (0.02)
0.49 (0.05)<.0001<.0001<.0001

2.2
4.0
1.1

Sex

Female-0.40 (0.38)

0.297

1.0

-0.42 (0.38)

0.273

1.0

Age

< 65 years

4.56 (0.35)<.0001

1.3

4.61 (0.35)<.0001

1.3

Mechanism of injury

Fall
Falls from heightTraﬃc accident
Sports-2.12 (0.69)-1.76 (0.50)
1.00 (0.51)
2.93 (0.93)

0.002
0.0004
0.050
0.002

1.8
1.4
1.4
2.2

-2.15 (0.69)-1.77 (0.50)
1.04 (0.51)
3.00 (0.93)

0.002
0.0004
0.042
0.001

1.8
1.4
1.4
2.2

AIS at admisionA
B
C

1.30 (0.66)
1.68 (0.73)-2.67 (0.52)

0.048
0.022
<.0001

3.7
2.7
2.0

1.05 (0.64)
1.88 (0.73)-2.60 (0.51)

0.101
0.010
<.0001

3.5
2.7
2.0

Level of injury

Cervical-4.32 (0.41)<.0001

1.9-4.26 (0.41)<.0001

1.8

Central cord injury

Yes

2.23 (0.37)<.0001

1.2

2.13 (0.37)<.0001

1.2

Bone injury

Yes

0.84 (0.33)

0.011

1.4

0.85 (0.33)

0.010

1.4

DiabetesYes-1.42 (0.43)

0.001

1.1

-1.39 (0.43)

0.001

1.1

Heart diseases

Yes-1.23 (0.58)

0.033

1.1

-1.21 (0.58)

0.035

1.1

Lung diseases

Yes-1.42 (0.75)

0.058

1.0

-1.40 (0.75)

0.062

1.0

Renal diseases

Yes-0.31 (0.91)

0.735

1.1

-0.35 (0.91)

0.698

1.1

Adjusted R2

0.665

167

0.666

ANCOVA for multivariate analysis.
SE, standard error; VIF, Variance Inﬂation Factor; ref, reference; AIS, ASIA impairment scale; mFIM, motor scaleof Functional Independence Measure; cFIM, cognition scale of Functional Independence Measure; AMS, ASIA motorscore. LT, Light Touch score; PP, Pin Prick score.

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Acta Med. Okayama Vol. 78, No. 2

Source

FDR logworth

FDR P-value

AMS at admission

236.5<.0001Age (65 +)38.0<.0001

Level of injury

24.4<.0001cFIM at admission

19.1<.0001

Central cord injury

8.6<.0001

LT at admission

6.6<.0001

AIS at admission

5.2<.0001

Mechanism of injury

5.0<.0001Diabetes

3.0

0.001

Bone injury

2.0

0.011

Heart disease

1.5

0.033

Lung disease

1.2

0.058

Sex

0.5

0.297

Renal disease

0.1

0.735

Fig. 2
The false discovery rate (FDR) log-worth of the parameters in the light touch (LT) model. FDR log-worth = -log10 (FDR p-value).
AMS, American Spinal Injury Association (ASIA) motor score; cFIM, Functional Independence Measure cognition score; AIS, ASIA
Impairment Scale.
SourceFig. 3

FDR logworth

FDR P-value

AMS at admission

226.2<.0001Age (65 +)38.7<.0001

Level of injury

23.8<.0001cFIM at admission

19.5<.0001

PP at admission

8.5<.0001

Central cord injury

8.0<.0001

Mechanism of injury

5.2<.0001

AIS at admission

4.9<.0001Diabetes

2.9

0.001

Bone injury

2.0

0.010

Heart disease

1.5

0.035

Lung disease

1.2

0.062

Sex

0.6

0.273

Renal disease

0.2

0.698

The FDR log-worth of the parameters in the pin prick (PP) model. FDR log-worth = -log10 (FDR p-value).

response on admission did not contribute as much at
8.5 (Fig. 3).

Discussion
The results of our analyses of the cases of 3,676
patients with an SCI suggest that both the LT and PP
scores (which are sensory assessments) at admission

were significantly associated with the patients’ mFIM
scores at discharge. To our knowledge, most studies
have focused on motor scores for predicting functional
outcomes [9-11], with few analyses of sensory assessments. Saboe et al. showed a correlation between LT
and PP data at admission and the FIM score at 2 years
post-SCI, but this was based on an evaluation of the
impact of post-discharge care and wheelchair use andApril 2024

not with FIM at discharge [24]. Kaminski et al. developed a predictive model for a spinal cord independence
measure (SCIM) at 1-year post-SCI in which the LTscore was included as a parameter [25]. Hicks et al.
developed a predictive model of independent walking
outcome after SCI in which the LT score at admission
was used [26]. Thus, an association between a sensory
evaluation (LT, PP) and functional prognosis in patientswith SCI has been suggested, but few studies have analyzed SCI patients’ functional outcomes at discharge,
which is a novel focus of the present investigation.
We did not include interventions such as surgery as
variables in the present models because we analyzed theimpacts of LT and PP responses at admission on themFIM at discharge. Early surgery has been reported to
improve the outcomes of SCI patients in cases of spinal
cord compression or instability [23 , 27]. The mFIM
score at discharge in our present patient population was
58.2 ± 0.58 among the patients who underwent surgery
and 57.5 ± 0.82 among those without surgery, a nonsignificant difference (p = 0.484).
We evaluated the patients’ LT and PP sensory functions; a light touch is widely used to assess the extent of
injury to the posterior columns of the spinal cord,
whereas the use of a pin prick assesses the spinothalamic tract, with the light touch often having a greater
value than a pin prick [28]. According to our present
findings, the usefulness of the LT was greater than thatof the PP, but the difference was small, and no apparent
difference were identified between the LT and PP interms of involvement in the patients’ mFIM scores. In
addition, although the AIS classification is commonlyused as an index, in our study, the mFIM score wasused as the functional outcome. The AIS is easy tounderstand with the five categories A-E, but it is difficult to evaluate the AIS result due to the presence of
only five categories. In a study that used the AIS classification as a functional outcome, the grade A patients
showed little improvement; the grade B and C patients
showed greater improvement, and the grade D patients
showed little improvement, with a ceiling effect [29].
The use of the mFIM as an outcome measure in thepresent study was thus considered appropriate.
We set the patients’ mFIM scores at discharge as thisstudy’s outcome variable, and the results of our analyses
demonstrated that the patients’ admission score on the
AMS (which measures motor function) was a major
contributor to their mFIM scores at discharge, as were

Impact of Sensory Scores on SCI Outcomes169

other factors such as age, level of injury, central cord
injury, cFIM at admission, LT at admission, and PP
score. Since these factors are measured in patients who
have experienced an SCI, they may be used to create
prognostic nomograms of SCI. We also observed thatthe presence of diabetes and that of heart disease wereassociated with the mFIM at discharge. Diabetes is aparticularly important health issue in Japan, where thenumber of individuals with diabetes continues toincrease. Patients with stroke and diabetes have a lower
mFIM at discharge [30], and a similar effect may bepresent in patients with SCI.
Study strengths and limitations. The strength of
this study lies in the use of a major Japanese databasewith a sample size over 3,000. The participating facilities cover the entire country, and the data are considered representative of Japan; this increased the reliability of the results. This study also had the following
limitations.
(1) The data collection was limited to the period
from the patients’ initial admission to their discharge,
with no information available after discharge; however,
little improvement is expected at 9 months after SCIs
[7 , 12], and this limitation is thus not expected to havesignificantly affected the results.
(2) Patient cases from 1997 to 2020 were analyzed,
and changes in treatment and rehabilitation during that
period were not taken into account. Although the
ISNCSCI was revised during this period, no significant
changes in the indicators used in this study existed, andthe impact on the results is considered minimal.
(3) The variables collected were limited, with insufficient information on the patients’ socioeconomic
background and complications during hospitalization.
(4) A total of 880 cases were excluded due to incomplete data; however, this was < 20% of the total numberof patients who could have been included in the analysis
and was not considered a selection bias.
In conclusion, among patients with a spinal cord
injury, the Light Touch score and Pin Prick score atadmission contributed to the prediction of the patients’
functional outcome at discharge; however, the magnitude of these contributions was not large.
Acknowledgments. We thank all of the study participants, research
assistants, and our colleagues.

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