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APPENDIX E Review of Obstetrical Risk Assessment Methods
Beatrice/. Selwyn
Thirty-three articles on obstetrical risk assessment methods reported
in the literature are described in Table 1. The studies represent the
uae of 19 different scoring systems. Nine studies were published prior
to 1973J the reaaining 24 were reported in 1973 or later. A historical
review of the risk assessment literature by Robel (1976) included 7 of
the systems in Table 1. In the pre-1973 era, 3 of the most widely used
risk assessment methods were reporteds Apgar (1953), Goodwin et al.
(1969), and Nesbitt and Aubry (1969). In 1973, Robel's method was
first published (Robel et al., 1973) and now joins the others as one of
the most widely used methods.
ATTRIBUTES OP THE METHODS
The methodology used in the studies described in Table 1 varies from
saaplea of highly selected groups of women (James et al., 1976J Kaminski
et al., 1973) to collections of large numbers of consecutively sampled
WOBen (Coopland, et al., 1977J Robel, et al. 1973J Nesbitt and Aubry,
1969). Methodology influences findings because the occurrence of an
outcome in the study group is affected by the characteristics of the
group chosen for study. The predictive accuracy of the system may also
be affected by the generalizability of findings from one group to
another.
Most of the methods require observations of the woman being scored,
and a few require interviews with the woman (Robel et al., 1973J
laainski et al., 1973). The number of characteristics ascertained
varies from method to method: 155 were assessed by Effer (1969)J 126
by Robel et al. (1973)J 123 by Stembera et al. (1975)J approximately 45
by Nesbitt and Aubry (1969)J and approximately 21 by Goodwin et al.
(1969).
The categories of factors assessed in all methods are similar. They
include demographic data, socioeconomic data, data based on past preg-
nancies, medical history, present pregnancy and, in the more recent
studies, data on fetal heart rate and uterine contractions from
electronic monitoring. All authors have baaed their selection of
factors on the existing information concerning variables associated
149
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TABLE 1 Attributes of Obstetrical Risk Assessment Methods
Study Matboda Risk Aa ..a...nt Matbod
llo. llo. stye When Collected ScorinG
of of
Data Sub- rec- Pre- Intr ... Manner of Outco.e of
. .fa ranee Dedgn Source a jecta Title tor a Pectora Included natal partua Neonatal Scoring Interest
AP9ar, U53 Coneec:utive Obeervation! 1,760 AP9ar 5 Heart rate, reapiratory 1 minute Points Acidoaia1
birtha, infant acore effort, reflex. irrita- after birth giveno 110rtality
delivery bility, auacla tone, 0. bad
color 2 • 9-d
aua points,
10 1a beat,
arbitrary
Prachtel, Sa.ple 30' lladical 1,378 Obatat- 42 Obatetrical and IIOCio- Yea Yea 3 and 10 1 point for Abnor.. l
U67 higb-riak vo.en, record~ ~
deal ec:onoaic (SBSI variables, daya after each non- neurology Ul
study groupo Score 58 neurological signa birth optlaal 0
infanta born factor,
in boapital aua points
Larks and Coneec:utive Obaarvatioa 2,028 54 DeiiOgraphic characterie- Yes Multivariate AP9ar
Larks, lt68 births tics, blood presaure of acora acore1
110thar, bioelectrical 110rtallty
-••urea
»asbitt and Coneec:utive Obaarvatlon 1,001 MCB care !,45 DeiiOgraphic character- Only Arbitrary ._r pari-
Aubry, 1969 ward patients, Indesi istics parity, obatatri- veightso natal out-
care giYSn , ... i- cal history, aedical 0 • good ~e
without knowing objactiYS history, IIOCioeconollic 30 • bad!
acore greding status, aaotional sua points
syat•l status and subtract
fraa 100
Wilson and RandOII 118J111le Obaarvation 148 MCB care 21 s... Only saae Sue
Sill, 1973 of ~king~, and recorda Indax of
aa.ple of 150 »aabitt
dellveriaaJ and Aubry,
coabinad the 1969
t110 aa.ple a
Aubry and Coneec:uti,. Obaervation 450 MCB ears 21 s - . with tba Yea Yea s - . but s-
PaMington, adllisaioas to and records Index of addition of .. tunal, with Labor
U73 labor and Nallbitt fatal, and placental Index, aua,
delivery, and Aubry, factor a and subtract
alxed clinic U6!1 plus 5 fraa 200
and privata Labor Index
patients
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Goodwin et al., Several study ObHrvation 1136 Antepartua !,21 laae1ine and obsta- Yea Arbitl:ary Perinatal
uu groups are and records retal Risk trical history, and based 110rtality
co.blned 1 peri- Score preMnt praguncy, on litera-
natal deaths, gestational age ture, weight
at birth factors
ward dellverles, 0-10 (0 •
and private
Bebb et al.,
11180
CaMs
All preutal
patients of
Observation 17,270 Antepartua
retal Risk
!21 a... , except no uH
of gestational age
Yes
good), sua
Saas ....
various MDs Score of
in region Goodwin,
et al.,
·-
11169
Coopland et al., All wc.en Records 5,U9 Modified !21 a... , except aoae Yes Weights are
U77 adaitted to Goodwin, deaagraphic factors 0-3
labor and Tlloaes
Yeh et al.,
1977
w-en aonitored
during labor
Records 266
1969
Goodwin et
alo 1 19611
!21 a... ,plus fetal heart
rate and uterine con-
Yes Yes Weights are
0-4
....
plus fetal traction
·-
110nitoring
Morrison and
Olsen, 111711
Deliveries in
80 hospitals
ObMrvation 16,733 Goodwin
et al.,
19611
!21
·- Yes On ad-
aission
in labor
Weights are
0-3
Butler and
Alber•n,
All births in ObHrvation
l week in Great recorda,
17,024 Rona 6 Age,
parity,
Yes Yea Multivariate
score for ....
1969 Britainr still- birth and
births and death car-
7,851 social class,
height,
each factor
and sua
....
Ul
neoutal deaths tificates pre-eclaapsia, and
for 3 110nths 8110king
Alberasn and
Goldstein,
1970
rr- Perinatal
Mortality
Surveyr iden•
tify children
at 7 years
·- 12,083 Hone-
167 with
handicaps
3 Parity 4+, adverse
aethod of delivery,
neonatal illness
in 1st week of life
Yes Yes Yea One point
for preHnce
of factor
Handicap
with and
without
handicaps
Bffer, 1969 All adaissions Records 211 Prognostic 155 Pathology, Assigned Not clear, Apgar
to high-risk 350 Risk Score test results, at labor aasuae 1
pregnancy unitr deaagraphic and au, point if
rancSo. naple past and preHnt preHnt
of thoH with obstetrical probl...
standard care
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Table 1' Continued
Study Methode Risk As . .s . . .nt Method
ao. ao. Stage When Collected Scoring
of of
Data Sub- rae- Pre- Intra- Manner of Outca.e of
aeference Design Sources jecte 'l'itle tore ractora Included natal partua Neonatal Scoring Interest
Rantakallio, All births in Recorda and 11,391 Hone U! Biological factora, Yes Diacr i11inant Poor neo-
11169 one year intervie'M!! in factors of aother, function, natal out-
lat .acioeconoaic status Eigenvector c-e
anal- weights given
yaia1 each factor
27 in
l final
RObel et al., All v-.n c..- Intervi8V and 725 Screening 51 Prenatal, intrapartua, Yea Yea Yea Arbitrary Perinatal
1973 ing to clinic1 observation to predict 40 and neonatal weights of 110rbidity
acrHned, but high riak 35 1 (good), and
attending MD
did not know
neonate a 5 and 101 aortality ....
Ul
acore pre-
acore N
natal aa . .an,
acore intra-
partua as eu11
·-
of pointe
Bobel, 1976 s... , update Sue 1,417 llobel'a 35 Yea Yes Yea Saae Sue
aodified
High-riak n - a... 60 Robel'• 35 Neonatal factors Yea Yea Yea s ... Morbidity
nate . . tched 52 aodified in lat 2
with l~riak years of
RObel,
11179
Sokol at al.,
neonate
s . . . aaaple
Conaecutive
....
Intervi.., and
1,417 Sobel'•
aodified
1,275 Sobel'•
21
18
49
Prenatal,
intrapartu11
Prenatal,
Yea Yes Multivariate
acorea given
life
s...
Yea Yea s ... s ...
1977
Sokol et al.,
1979
deli varia a
Delivery with
perinatal deathJ
delivery with-
observation
s-
aodified
143
Robal'a-
aodified
36
36
intrapartu•
s... Yea Yes Yea .... sa-
out perinatal
death 5,235
Chik at al., Conaecutively Intervi.., and 4,500 Sobel'• 36 s ... , but with Yea Yes Diacri11inant s...
l97t delivered observation aodified 17 fetal aonitoring function
- n with factors acorea
fetal aoni-
toringr He
Sokol at al.,
1979
L
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Wlntel'• et al ••
1.171
8l.aok and Hi-
panic - n
%n~ei'Y1ew
record•
and 62 llobel'•
·- ·- Yee Yee Yea
··- ....
bavlnv Uve
infanta
Ilea•-~ Ra
Table 1 Continued
Study Methoda Risk Aaaea... nt Method
No, No. Stage When Collecte4 Scoring
of of
Data Sub- rae- Pre- Intra- Manner of Outc011e of
Reference Design Source a jecta Title tors Pactora Inclu4e4 natal partu11 Neonatal Scoring Interest
Cora4ello et al., Unknown1 None 41 Not apeciUe4 Yea Yea Not Mortality
1975 retroapecti ve Unknown 1,067 apecitie4
prospective Unknown 230
Ala anCI Neurologically ObHrvation
Braselton, 1975 auapect infanta 53 Braselton 46 Behavioral, Yea Behavioral Neonatal
followe4 for Bxa• neurological, factors 9et JDOrbi4ity
7 yean vi9or anCI attention, 9 points,
.otor activity, an4 reflex
tone autono.ic ..aaurea 9et
reaponae 4 pointa1
BUll
Ja..a et al., w-en elec- Recor4a 665 PHR-UP9. 10 Characteriatica of Yea Use4 Neonatal
1976 tronically Monitoring fetal heart rate an4 Receiver morbi4ity
.onitore4 Score uterine preaaure Operator ....
Ul
Character-
istic Curve
anCI clinical
•
experience
to vei9ht
factors
l'e4rick, 1976 CaHa • apon- Unknown 283 None 10 Dnoographic, Yea Calculate Preutur-
taneoua pre- previoua pregnancy relative ity
ter• birtha history risk for
each factor~
eo.peen auple 510 •ultiply
of singleton relative
birthaa retro- risks for
apective score
Uwar4a et al,, WC..n 4eliver- Obaervation 2,085 None 67 Dnoographic, Yea Yea ArbitraryJ Neonatal
1!17!1 i ng conaec~t- obatetric, baH4 on .orbi4ity
tively in ~ical, anCI i!lpOrtance anCI
hoapital other to outc,.., .ortality
wights • 1
(9oodl to 7
Jl)baervati- • 4ata collecte4 by ex-ination of the .otber of the infant,
iaecor4a • 4ata collecte4 throuvh the uH of exiating recor4aa ~ical, birth certificatea, 4eath certificatea, etc.
£Maternal Chil4 Bealth Care In4ex • MCB Care In4ex.
!Interview • the riak inatru.ent require• 4ata obtained 4irectly fro. the other .othar•-.ora than what ia routinely collecte4 in hoapitals.
SAl in firat analyaia, 27 in final analyaia,
1BPLII • h iatory, prenatal, labor, neonatal.
lrsa-ur • fatal heart rata, uterine praaaure.
155
with outcomes such as perinatal mortality or morbidity, rather than on
data concerning maternal mortality or morbidity.
The stage of pregnancy when factors are assessed can affect the
accuracy of the prediction and the timeliness of intervention or
prevention (Chng et al., 1980). Of the 19 systems, 15 require assess-
ment of the woman prenatallyr 8 require assessment of the woman only
during the prenatal period, e.g., Nesbitt et al. (1969), Goodwin et al.
(1969). Thirteen methods include intrapartum factors, and six assess
the neonate. Two scoring methods are used solely for assessment of
infants: the Apgar Score (Apgar, 1953, 1966) and the Brazelton Method
(Brazelton, 1973). Robel (1977, 1978), Robel et al. (1973, 1979),
Prechtl (1967), and Stembera (1975) provide for collection of informa-
tion during the entire pregnancy, i.e., prenatally through labor and
delivery, including assessment of the neonate's characteristics.
The manner of scoring each risk factor is handled uniformly by
arbitrarily assigning a weight based on reports in the literature and
on experience. Most of the scoring systems are easy to user indeed,
this characteristic is frequently cited as a criterion in developing
the system. Even in systeas in which scores were obtained by using a
•ultivariate technique, arbitrary decisions were made at some point,
e.g., level of seriousness of risk (James et al., 1976J Stembera et
al., 1975). In some of the methods, attempts were made to accommodate
weights to different outcome factors by using multiple regression
techniques and discriminant function analysis (Donahue and Wan, 1973r
Robel, 1979r James et al., 1976r Rantakallio, 1969).
Biochemical measures and fetal monitoring are occasionally used
together with existing risk assessment methods. Yeh et al., (1977)
coabined them with the suggestion of Goodwin et al. (1969)J Chik et al.
(1979) did the same with the Robel (1973) method. James et al. (1976)
developed a scoring system for fetal monitoring and uterine contraction
data. Appropriate use of biochemical indices to predict outcome re-
quires detailed knowledge of the biochemical process (Tulchinsky,
1980). A thorough understanding of findings concerning fetal heart
rate and judicious decisions about their clinical importance are
necessary for successful prediction of outcomes (Chik et al., 1979).
PREDICTIVE POWER OF THE MB'l'HODS
Evaluation of the ability of a screening test to predict an outcome
successfully entails knowledge of the test's sensitivity, specificity,
and predictive value as well as information on the frequency of occur-
rence of the outcome (Table 2). Many of the reports referenced in
Table 2 did not contain the requisite information. Therefore, the
screening parameters presented in the table were calculated from the
data presented by the authors. In some instances numbers were extracted
from graphs in which only percentages were displayed. An attempt vas
aade to standardize all parameters for purposes of comparison. Lesinski
(1975) has reviewed the risk assessment literature emphasizing the
clinical elements in screening. The following comments are focused on
TABLE 2 Predictive Power of Obstetrical Risk Assessment Methods
Ability of High- and Low-Riak Scoraa to Predict a Given Outca.e~
Prevalence of ---
Riak Neonatal C~licationa Low Birth weisht ILBMI Perinatal Death
Titlea and 'riak
low- ' low- ' low-
riak risk
Reference
Scorea for
Rlak (t) ,,,
high Mdiu. 1-
(t) ,,,
inci aena
(t) ,,, ,,, ,,,
apec fal+ fal- with
probl- ,,, ,,, ,,,
inci aena a pee fal+
(t) ,,,
fal- with
,,, ,,, ,,, ,,,
inci sena spec fal+ fal- with
proble• l'l proble•
Apgar, U53 ApcJar 6 l8 76
Score a 1.2 92 77 23 8 0.1
high • Q-2 (Neonatal only)
Md • 3-7
~ • 8-10
Prechtel, Obatetri- 12 &8 19 38 16 23 10 14 28
1967 cal ecorea (Neurological only)
high • 7+
. .d • 2-6
1- • 0-1 ....
U'l
Larka and No title• Rot known 0\
Larka, Multi-
1968 a 2 for stillbirth • 41~
variate a 2 for death in 2 years • 41'
8COrlng
...bitt and MCB Care 30 3t 31 6 47 32 28 19 4 ll 43 33 27 23 10 3 43 31 29 27 2.6
Aubry' 196!1 Index a
high • 0-70
Md • 71-84
1- • 85-100
Wlleon and MCB Care 8 72 20
Bill, U73 Index a 17 6 22 8 15 13
high • 0-40
Md • 41-89
~ • tO+
Aubry and MCB Care 21 7t
Pennington, 8.4 63 82 l7 37 4
Index plua
U73 Labor Inclexa
high • none
1- • none
Goodwin, Antepart~a 7 6!1 24
et al., Petal Riek 15 46 28 0 0 0
U6!1 Score•
high • 7-10
Md • l-6
1- • 0
Bebb et al., Antepart~a 10 75 15
ltiO Petal Riak 2.6 86 15 8 l 0.2
Score a
high • 4+
Md • l-3
1- • 0
L
~1and Ante..-rt.u. •ot. known • hi9heat cl•k wlt.h lt. - so• ' hl9heat rl•k with it .• 1U t hi9he•t ri•k wlth it • 11.0'
et; al., Petal lliall ' 1oweat riak with it • '' ' 1oweat riak with it • lt t 1oweat riak with it • 0.4t
lt77 Score•
IIOdified
higheet• 7+
high • 3-6
low • 1-2
loweat • o
Yeh et el., Antepertua 28 72 t high riak with it • 22t
1977 l'etel Rial! t low riak with it • 13t
Score, of
fetal - i -
toring•
high • 4+
low • G-3
Mor:riaon Ante~rtua 19 81 1.9 70 82 18 30 0.7
end Ol .. n l'etd Rial!
lt79 Score•
high • 3+
low • 0-2
Butler end No title• Not known Bigheat riak • 85/1,000 deeth
Albe~n, Multiveriete rete
1969 Score of 800 Loveat riak • 8.9/1,000 deeth
(high risk) rete
to -800
(low riakl
Albe~n No title• 13 87 1.4 26 87 13 74 1.2
endGold- high • (Bandicepa only)
etein, 1970 preHnce
of eny 1
factor ~
Bffer, 1969 Prognoatic (high riak group) 38 Ul
Risk Score• 46 54
55 62 38 45 31
(1 •inute Apger only, high-riak
.....
high • 51+ IRa'*- group) group only)
low • G-50 11 89
Rentelldlio, 14 86 2.4 30 87 13 70 2
1969 Diacri•inent
Function
Score•
high • prob-
ebility of
poor out-
COIH ia 50t
Robel Scr ..ning 16 20 18 46 16 36 51 12 19 6 4 59 48 14 4 0.3
et el., 1973 to Predict BB LB HL LL
Bigh-Riak
lleonet•••
high • 10+
lov • G-9
4 group• high/high
with pre- low/high
netel end high/low
intre~rtua lov/low
.:ore a
TABLE 2 Continued
Ability of High- and Low-Riak Score• to Predict a Given Outcome!
Pravalance of ---
Rial! •-natal C!!!!l!licationa Low Birth wei9ht !LBW! Per ina tal Death
• low- t low- t low-
Titl.. and riak riak riak
Reference
Soor•• for
Riak ,,, ,,, ,,,
high MdiUII low inci ••n• •pee
(t)
fal+
(t)
fal- with
probl- ,., "' ,,, ,,, ,.,
inci aena apec fal+ fal- with
problea (t) ,,, ,., ,,, ,,,
inci aena apec fal+ fal- with
problea
"' "' "'
llobe 1, 1!176 llobel'• 16 23 45
16 16 37 51 12 18 6 3 54 47 14 2 0.2
updated HH LBBL LL High Low
sue (Group• defined by Poor weight gain 48 7
being at high or
low riakl
Robel, 1!179 IIObel' 81 18 82 54 72 28 46 12 ~
high • 10+ (Prenatal factor• only) U'l
C»
low • 0-9 94 28 72 6 6
(Prenatal and intrapartUII)
Sokol Robel'•• 26 20 23 31 3 82 31 24 0 0
et al., high • 10+
1977 low • 0-9
4 group•
with pre-
natal and
intrapa~:-
tua ~:iaka
Sokol Robel'• Ca..-ca.pad110n
et al., aodifiedl
U79 (not known) Bigh-~:iak group • 46t death rate
Low-dak group • 12t death rate
Chik llobel'•· Not known 33 93 87 13 7 4
et al., aodifiedl (One ainute Apga~: a• outcoae1
1979 diacdai- ~:iak end aonito~:ing data)
nant func-
tion aco~:ea
UHd
Winter• llobel'•• 41 59 48 52 70 30 48 39
et al., high • 40+
1979 low • 0-39
lteaane~: social- 55 45 u 72 48 52 28 7 2.2 75 46 54 25 1
et al., Medical Rial! (Infant death• only)
1973 Boor••
high • 2+
handicapa,
l aocial •
l Mdical
L
•-lnakl No ~1~~-· 16 22 62 39 63 3.
·~
4 2
et. al., •ul&ivaci- e.5+ o-5
lt73 •t.•80oc•• 0.5
hl9h ecoce (Scoce foe low
• hl9h rlek1 binh -19ht
aiiOUnt ae outcc.e)
variee with
ou~e
Donahue and 'l'Otal Riak 25 50 25 33 43 29 16 16 22
lfen, 1973 Score, (Neonatal deeth• only)
•ultivuiete
ecore quer-
tilee UMd
for rieka
high • upper
251
low • lower
25\
Haeri No titlea 12 88 3 28 ag 11 72 2
et al., 3 eyetHe,
1974 ueed herea
high • 4+
low • 0.3
Helliday Haeri'e 26 36 38 7 64 40 23 13 2.5 1.4 67 38 25 6 0.2
et al., Scoring (Neonatal tranefer to lerge hoepitel) (Neonatel deathe only)
1980 Syete••
high • 7-16
...s • 4-6
low • D-3
Stellbera
et al.,
HPLH£
&corea
llot known
Popule- Morbid- Popule- Perina tel ....
Ul
1975 high • HP 30+ tion (I) ity (I) tion I + infent
HPLII 40+
•ultivariate
H+P
H+P+I:t+N
16
u
31
51 H+P 16
deathe •
40
"'
ecoring H+P+I:t+N u 73
Coradello No Titlll llot known? 19 58 86 l4 42 10
et al., high • 51+ (Riek aeMeeed at delivery)
1!175 low • o-5o
6 77 78 22 23 2
(Riek aeMeeed prenatally)
Ale end Bra•elton 40 60 28 80 76 24 20 9
Bra•elton, Method a (Neurologically abno...al at
1!175 high • not 7 yean of age)
eta ted
Ja-• PHR-IJP!! 44 56 54 60 76 24 40 38
et al., Monitoring
1976 Bcore1 •ul-
tiveriate
ecoring a
high • 51+
low • o-5o
Pedrick, No titlea 0,6 39 60 1.8 9 60 0.4 30 0.9
1976 high • 5+ (Pr i•iperae 1 (Pri•iperae, eerly geetetion
...s • 1-4 only)
low • 0
160
~ !
. t
..!.-
-
.
. ........"'
~ -=~
...
,..._
-...
...
+
...
(;
·-
•
c-
~~
..
...
... ...- i;
•
.. I
:!~ ....
........
...... "'
'"'O~.c.a
........ o
... ,..._
I
... -
1 ,..._-
8
c
...
...
+
: !,;
...
0
..•
·-
•
~
1
·-
••
...
c-
t
s ... -
I!;
•
•
J ...
...
~
...-
..,_
I
i J
...
...
..,_
+
... -
...
"'
...
...
j
.... ....
•
c-
~~ ...
"'
i•
... - ....
I
~
1!"
.:~
••
.= !
•
.. ...
...
.. .
.Ill
...
i
.
...
:
• .
....-
'2': •
:;;
1 ....
161
the screening parameters of the risk assessment methods reviewed,
1953-1980, and outlined in Table 2.
The scoring for risk is described in detail because it often
varies--even when one researcher is using the method of another. Por
exa.ple, Wilson and Sill (1973) used a high score of 0-40, whereas the
originators, Nesbitt and Aubry (1969), used a high score of 0-70. Like-
wise, Bebb et al. (1980) used a high score of 4+ when applying the aye-
tea designed by Goodwin et al. (1969), who used a high score of 7+. The
cbosen cut-off points, i.e., 0-40 or 0-70, 4+ or 7+, affect the propor-
tion of the population declared to be at high risk. Thus, the variation
between studies in which the same methods were allegedly used diminishes
comparability but enhances the possibility of ascertaining which cut-off
points are .ast effective (assuming other aspects of study methodology
are coaparable). The presentation of high-, medium-, and low-risk
inforaation in Table 2 facilitates such comparisons.
Scores are provided for middle-level risk, but details of sensi-
tivity and false positive rates are given for the highest risk group
only. Specificity, false negative rates, and percentage of low-risk
waaen experiencing the outcome refer to the lowest risk group examined
by the author. The issue of nonconventional birth settings would
usually apply to the lowest risk women. Por the sake of simplicity,
the middle-risk group is excluded because the values for this group lie
between the two extremes.
Screening parameters cannot be properly evaluated without informa-
tion on the proportion of the group at each level of risk and on the
outcome factor (disease). Frequencies in each category affect the
accuracy of prediction. The incidence rate is provided for the outcome
measures displayed in Table 2, i.e., neonatal complications, low birth
weight, and perinatal death. A measure of incidence rather than preva-
lence was used because these conditions do not endure as long as condi-
tions such as cancer or diabetes. (Incidence rates refer to the number
of new cases of a disease in a specific time period for a population at
riskJ prevalence rates refer to the number of existing cases of a
disease at a specific time for the total population.) The incidence
rate is given for the entire population studied irrespective of the
level of risk.
Predictive value is especially sensitive to the incidence (or
prevalence) of the outcome. Because the predictive value is actually
the incidence rate of the outcome for a certain risk group, it often
airrors the incidence rate in the general population. Where it does
not miaic the population rate, there are probably significant differ-
ences between that risk group and the expected rate. In Table 2 the
predictive value of the low-risk assignment is presented in reverse,
that is, the percentage of the low risk group that experiences the
undesirable outcome is given because pregnant women assessed as low
risk are slated for less exhaustive diagnostic monitoring.
Authors varied as to which outcomes they considered important.
Specific outcomes and the number of publications in which they were
reported are as followss
162
Neonatal or perinatal mortality 20
Neonatal morbidity 14
Early gestational age at birth 7
Low Apgar score 7
Low birth weight 6
Intrapartum complications 2
Maternal complications 1
In the studies reviewed, perinatal mortality received the greatest
amount of attention. Most of the authors included at least one of the
following three outcomesa neonatal complications, low birth weight,
and perinatal death (see Table 2).
FINDINGS
The interplay between incidence of conditions, sensitivity, and
predictive value is illustrated in Table 2. Richards and Roberts
(1967) point out that if 5 percent of a population is at high risk, the
incidence of an outcome must be 16 times higher in the high-risk group
than in the low-risk group before the sensitivity of the risk assess-
ment can reach 80 percent, the acceptable minimum. The Apgar (1953)
score fits this criteria: 6 per'cent of the group was declared high
risk, the incidence of perinatal death is 1.2/100, the sensitivity of
the score is 92 percent, and 22 percent of the high-risk group died
versus 0.1 percent of the low-risk group. The death rate is 22 times
higher in the high risk group. Data from Nesbitt and Aubry (1969)
indicate that sensitivity is not necessarily influenced by the incidence
of the outcome while predictive value clearly is affected. The inci-
dence rate of low birth weight is 13 percent and the incidence of
perinatal death is 3 percent, but the sensitivity of the high-risk
label is the same, 43 percent. Predictive value, on the other hand,
varies with incidencer the predictive value of the high-risk assignment
with low birth weight as the outcome is 20 percent, and with perinatal
death it is 4 percent.
The role of sensitivity is to permit correct assignment of women
with undesirable outcomes to a high-risk group prior to actual ful-
fillment of the outca.e. Thus, the more sensitive a measure, the more
often a woman will be correctly identified as high risk. Frequently a
trade-off must be made between sensitivity and specificity, an increase
in one may yield a decrease in the other. Robel's method had a sensi-
tivity of 37 percent with specificity of 51 percent using 126 factors
and a dichotomized scoring system. In order to increase sensitivity, a
multivariate scoring technique was applied to the data using 39 factorsr
the yield was a sensitivity of 94 percent but specificity decreased to
28 percent. The rate of false negatives also decreased from 18 percent
to 6 percent, but this represents an improvement for obstetric risk
assessaent because fewer women are incorrectly assigned to a low-risk
group.
Among the methods which used neonatal complications as an outcome,
163
the highest sensitivity (94 percent) vas achieved by Robel's method in
1979 with aultivariate scoring, followed by Edwards et al. (75 percent)
in 1979 and by Nesbitt and Aubry (47 percent) in 1969. The latter two
methods eaplQ¥ed arbitrary weights for the risk factors. There is only
a slight indication of correlation between the number of risk factors
assessed and the level of sensitivity. Any real association is aasked
by the differences in the populations studied.
Specificity is increased when fetal monitoring is included. Chik
et al. (1979) used Robel's method, plus fetal monitoring, to achieve
sensitivity and false negative rates siailar to those Robel's method
achieved with aultivariate scoring. However, the specificity is auch
higher with the method of Chik et al.: 87 percent versus 28 percent.
Indeed, monitoring seems to carry a high specificity with itJ yet, when
used alone, it appears to have a high false negative rate. For exa.ple,
the method of James et al. (1976) yields a 40 percent false negative
rate while Chik et al. (1979), using monitoring and Robel's risk assess-
aent scheme, have only a 7 percent false negative rate.
Low birth weight vas an outcome variable for very few (six) of the
reviewed articles. Only two of them contain enough information to per-
ait ca.parisons. Nesbitt and Aubry (1969) attained a sensitivity of 43
percent with their index, which vas applied only at the initial prenatal
visit. Later, Aubry and Pennington (1973) added a labor index that in-
creased sensitivity (63 percent) and specificity (82 percent) but also
increased the rate of false negatives (37 percent). The method of
Kaminski et al. (1973), using aultivariate scoring, did not improve on
that of Aubry and Pennington (1973). The proportion of women labeled
low risk who deliver a low birth weight infant is small when
information about labor is included.
Risk assessment activities have tended to concentrate on prediction
of perinatal or neonatal mortality. Apgar's (1953, 1966) scoring system
has the highest level of sensitivity (92 percent) and one of the highest
levels of specificity (77 percent) of all the systems reviewed for pre-
dicting neonatal mortality. This accuracy is due to the direct observa-
tion of the neonate at birth, which is necessary to obtain the Apgar
score. The other systems use inforaation available during the prenatal
period and attempt to predict perinatal outcome long before the infant
appears in the delivery rooa. They are subject to less accuracy than
the Apgar score.
The methods of Nesbitt and Aubry (1969) and Goodwin et al. (1969)
achieved similar sensitivity (43 percent and 46 percent) using prenatal
information only. Robel's (1976) systea, which includes the prenatal-
through-delivery period, improved the sensitivity to 54 percentJ it
also improved the specificity (47 percent). Three studies (Goodwin et
al., l969J Bebb et al., 1980J Morrison and Olsen, 1979), using somewhat
ca.parable methodology, eaployed the Goodwin et al. instrument but used
varying cut-off points to assign high risk. The originators of the
scheme achieved the lowest levels of accuracy (sensitivity, 46 percentJ
specificity, 28 percent). Their cut-off point of 7+ eliainates false
negatives because it vas assigned with knowledge of the level of risk
at which no .ore deaths occurred. Morrison and Olsen's (1979) method
has a very high false negative rate (30 percent) as well as a high
164
level of specificity (70 percent). Examination of the study methods of
each investigation suggests the strength of the approach of Hebb et al.
(1980) and indicates that its screening parameters are probably the
best representation of the method's power.
The multivariable instrument of Robel et al. (1973) has been used
by several investigators other than the orginators Chik et al. (1979),
Sokol et al. (1979, 1980), and Winterset al. (1979). All of these
groups have similar study designs. Winters et al. (1979) did not
ascertain mortality. Comparing the findings of Sokol et al. (1979)
with those of Bobel et al. (1976), it is interesting to note that the
screening parameters produced by Sokol and associates are better than
Robel's: the sensitivity is 82 percent versus 54 percentJ the false
negative rate is 0 percent versus 2 percent. However, as sensitivity
increased to 82 percent, the specificity decreased to 31 percent for
Sokol's study, compared to 47 percent in Robel's study. The incidence
rates for mortality were equal. Sokol et al. (1979) had 26 percent of
their group at high/high risk while the similar figure in the Robel et
al. (1976) study was 16 percent. Both investigative teams used the same
cut-off points for high risk. Probably the two populations studied
varied in other ways to account for some of the differences in the
parameters. Several authors (Bobel, 1978J Stembera et al., 1975J
Winterset al., 1979) have suggested that cut points will have to be
determined for each population to which a risk assessment is applied.
None of the methods reviewed place many women with perinatal deaths
at low risk incorrectly. The predictive value of a low-risk label for
subsequent perinatal death is high, i.e., 98 percent of women in the
low-risk group have live infants at the end of the perinatal period.
Only the method of Donahue and Wan (1973) carries an unacceptable level
of risk. Possibly, this is due to the assignment of weights based on
prematurity, not mortality, as the outcome variable. Sokol et al.
(1977) have noted that inclusion of the intrapartum risk assessment
greatly enhances the prediction of perinatal death. Stembera et al.
(1975) show similar improvement, rather dramatically. Using only
historical and prenatal factors the predictability is 40 percentJ it
rises to 73 percent when factors for the entire pregnancy, labor, and
neonatal period are included.
SCREENING CRITERIA IN UNCONVENTIONAL SETTINGS
Risk assessment is used as a screening tool in developing countries to
decide where limited resources will be allocated (World Health Organ-
ization, 1978). In Great Britain, women were booked for delivery at
home, in general practioners' clinics, or in hospitals. The bookings
were based on characteristics predisposing to probleas in the d~livery
(Butler and Alberman, 1969). Risk factors are assessed in the United
States when families desire delivery in unconventional birth settings
that do not have major life-supporting equipment immediately available.
Use of risk criteria by lay midwives is not well documented in the
literature, although personal communication with several midwives
suggests that, when criteria are used, they are applied vigorously.
165
Bennetts (1982) studied 11 nonhospital childbearing centers admin-
istered by certified nurse midwives throughout the United States in
1981 (see Appendix C). Every center has admission criteria baaed
partly on risk assessment. Only one center had no written criteria at
the tl.e of the study, a risk assessment vas carried out by the cer-
tified midwife for admission to the center.
The factors assessed by the nonhospital childbearing centers are
analogous to those in Table 1, but the centers tended to vary in the
degree to which the factors were applied. Five of the centers used
absolute criteria for admission, that is, the mere presence of certain
factors obviates delivery in the center. The remaining centers em-
ployed a risk scoring system similar to those in Tables 1 and 2.
A woman labelled low risk and acceptable for delivery at a center
may develop ca.plicationa during pregnancy, labor, or delivery, or the
neonate may have a problem. Therefore, intrapartum and postpartum
transfer criteria exist. These criteria are baaed partly on the
resources a center has for handling an emergency and partly on the risk
a ca.plication implies for further, more serious outcomes.
Bennetts (1982) sampled recorda from each center and obtained
information about the proportion of women who began labor in a child-
bearing center and were transferred. This transfer rate can serve as
an indicator of the predictive value rate of low-risk women to beCome
high risk. Thus, it is similar to the rate in Table 2: the percentage
of low-risk women who experienced an unfavorable outcome.
According to Bennetts' data, 10 percent of women had complications
before labor and withdrew from the centers. Another 15 percent of
those who began labor in the centers developed complications during or
after labor and were transferred. Only one percent of infanta required
transfer. The predictive value of low-risk labelling by the time labor
begins is 85 percent because 15 percent of women required transfer.
Rote that COdMOnly used risk assessment methods are aimed at predicting
perinatal mortality and not maternal or intrapartum ca.plicationa. In
Table 3 the rates in the childbearing centers compare favorably with
tboae of Nesbitt and Aubry (1969), especially for neonatal problema.
Of interest is the fact that 14 percent of the transfers from the
centers to hospitals experienced no actual complication during labor or
delivery (Bennetts, 1982). The datum is testimony to the false
positive rate of aa.e of the risk assessment methods used.
DISCUSSION AND SUMMARY
weakness in Current Methods
1. Only one of the 33 papers presented in Table 1 included informa-
tion on the ethnic group of study participants. The major demographic
factors of age and ethnic group have been virtually ignored in develop-
ing weights fo~ risk factors. Inattention to epidemiological factors
probably contributes to the inability to apply the same methods in dif-
ferent populations and obtain similar predictability. Separate weight-
166
Table 3 Risk of Complications in Pregnancy
Percent of Low Birth Weight with
Maternal Intrapartua Neonatal
Study Complications Complications Complications
Bennetts, 1982 10 15 l
Nesbitt and Aubry, 1969 24 15 4
Wilson and Sill, 1973 7
(cesarean
section only)
ing and scoring systeas should be developed for each age group, ethnic
group, and social level at least.
2. Past pregnancy history is a large co.ponent of .oat risk
assessment •ethods reviewed. These methods are better at screening
aultigravada women for risk than primigravida women• e.g., Pedrick's
(1976) method for predicting early gestational age bad a sensitivity
rate 64 percent higher when applied to •ultiparae women than when it
was applied to pri•iparae women. Separate risk assessments need to be
developed for primigravida women.
3. Reliability or repeatability of obstetric risk factor assess-
ment is rarely addressed in the literature, yet women can be incorrectly
labelled through misuse of the instruaent. Robel et al. (1973) include
a handbook of definitions and instructions in the way to use their
forms. Other authors (Edwards et al., 1979' Baeri, 1974) prefer aiapler
approaches. However, reliability in application of screening criteria
is especially important when assessment is aade only once in the
prenatal period.
4. Expectations for what a risk assessment can do are often •is-
aligned with the technique's real capability. In using the risk assess-
ment approach, it is important to recall that the risk factors and
weights are derived fro. population or grouped data. Most of the
accusations of bar• associated with using the risk approach are due to
lack of appreciation for the •ecological fallacy• (Parmelee and Baber,
1973' Richards and Roberts, 1967' Wilson and Schifrin, 1980).
The risk inherent in any group may not apply to an individual
member of the group. The fallacy is that the probabilistic risk of an
outcome is assigned to an individual' i.e., whatever is true for the
group is supposed to be true for the individual group member. However,
the individual may or aay not suffer the undesirable outco.e. It is
fair to say, •This person may be at higher risk,• but is incorrect to
say, •This person will experience the outooae because of the presence
of these risk factors.• The predicted risk of a neonatal death in
167
Bobel's high/high risk group is 11 percent. The neonate's actual risk
is either 0 percent or 100 percent. The neonate will either survive or
dier the neonate will not partially die or be ll percent dead. Thus,
even though a woman belongs to a particular group, she may not suffer
any undesirable outcome. The reverse is also possibler a woman
possessing none of the known risk factors for neonatal death aay lose
her infant.
In obstetrics, death is a rare event and therein lies the need to
exaaine realistically the probability of poor outcomes. The perfor-
aance of screening to assign correctly women who will have no problems
during pregnancy and child birth to a low-risk group should be seriously
considered. From the point of view of alternative birth centers, high
false negative rates vis-a-vis perinatal death are anatheaa to the con-
cept of women delivering out of hospital. The main risk is two percent
or less, and among all women labelled low risk, fewer than 3 per 1,000
will experience a perinatal death. This is much lower than the national
perinatal mortality rate.
Very little can be gleaned from existing literature on risk assess-
.ent methods regarding successful prediction of maternal/intrapartum
complications or neonatal morbidity. In general, false negatives are
high--usually over 20 percent of women or their infants experiencing
undesirable outcomes are incorrectly assigned to a low-risk group.
More work must be done in this area. From Bennetts' (1981) study it is
also evident that 14 percent of women transferred for predicted
co.plications do not experience any ca.plications. At this time,
aorbidity in pregnancy and neonates cannot be predicted as accurately
as death.
Summary
Thirty-three risk assessment articles were reviewed in detail, com-
prising 19 methods of assigning levels of risk for undesirable outcomes
in pregnancy. The predictive power of the methods as screening tools
was exaained. Most of the methods are based on the prediction of
perinatal death, which hampers their utility for predicting less severe
outcomes.
Three aajor systems emerge from the literature: (l) the Nesbitt
and Aubry (1969) Maternal-child Health Care Index plus the Aubry and
Pennington (1973) Labor Index, (2) the Goodwin et al. (1969) Antepartum
Fetal Risk Scoring system, and (3) Hobel's (1973) Problem-oriented Risk
Assessment system. Numerous other authors proffer their methods, but
they are all similar to one of the three major ones. Factors used by
each system are similarr it is the importance, or weight, given to each
factor and how it is derived that varies. Generally, systems that
include prenatal and intrapartum information appear most successful,
i.e., strike a good balance between sensitivity and specificity.
The cut points for declaring risk level are important and probably
should be derived for each population, as should the weights. However,
weighting of factors is problematic because we have no •pure• measure
of risk--i.e., associating a characteristic with a negative outcome
168
prompts intervention, which interrupts the causal chain and distorts
the relation of the factor to the outcome. This is as it should be,
but predictive power of risk assessment methods will be more inaccurate
because of it.
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