Classifications for Cesarean Section: A Systematic Review
Maria Regina Torloni1*, Ana Pilar Betran2, Joao Paulo Souza2, Mariana Widmer2, Tomas Allen3, Metin
Gulmezoglu2, Mario Merialdi2
1Department of Obstetrics, Sao Paulo Federal University and Brazilian Cochrane Centre, Sao Paulo, Brazil, 2Department of Reproductive Health and Research, World
Health Organization, Geneva, Switzerland, 3Department of Knowledge Management and Sharing, World Health Organization, Geneva, Switzerland
Background: Rising cesarean section (CS) rates are a major public health concern and cause worldwide debates. To propose
and implement effective measures to reduce or increase CS rates where necessary requires an appropriate classification.
Despite several existing CS classifications, there has not yet been a systematic review of these. This study aimed to 1)
identify the main CS classifications used worldwide, 2) analyze advantages and deficiencies of each system.
Methods and Findings: Three electronic databases were searched for classifications published 1968–2008. Two reviewers
independently assessed classifications using a form created based on items rated as important by international experts.
Seven domains (ease, clarity, mutually exclusive categories, totally inclusive classification, prospective identification of
categories, reproducibility, implementability) were assessed and graded. Classifications were tested in 12 hypothetical
clinical case-scenarios. From a total of 2948 citations, 60 were selected for full-text evaluation and 27 classifications
identified. Indications classifications present important limitations and their overall score ranged from 2–9 (maximum
grade=14). Degree of urgency classifications also had several drawbacks (overall scores 6–9). Woman-based classifications
performed best (scores 5–14). Other types of classifications require data not routinely collected and may not be relevant in
all settings (scores 3–8).
Conclusions: This review and critical appraisal of CS classifications is a methodologically sound contribution to establish the
basis for the appropriate monitoring and rational use of CS. Results suggest that women-based classifications in general, and
Robson’s classification, in particular, would be in the best position to fulfill current international and local needs and that
efforts to develop an internationally applicable CS classification would be most appropriately placed in building upon this
classification. The use of a single CS classification will facilitate auditing, analyzing and comparing CS rates across different
settings and help to create and implement effective strategies specifically targeted to optimize CS rates where necessary.
Citation: Torloni MR, Betran AP, Souza JP, Widmer M, Allen T, et al. (2011) Classifications for Cesarean Section: A Systematic Review. PLoS ONE 6(1): e14566.
Editor: Fernando Althabe, Institute for Clinical Effectiveness and Health Policy (IECS), Argentina
Received June 30, 2010; Accepted December 15, 2010; Published January 20, 2011
Copyright: ? 2011 Torloni et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no support or funding to report. The authors were personally salaried by their institutions during the period of writing, though no
specific salary was set aside or given for the writing of this paper.
Competing Interests: Academic conflict of interest: Five authors of the present study have published a study on CS in Latin America using one of the
classifications evaluated in the present systematic review. Betran AP, Gulmezoglu AM, Robson M, Merialdi M, Souza JP et al. (2009) WHO global survey on maternal
and perinatal health in Latin America: classifying caesarean sections. Reprod Health 6: 18.
* E-mail: email@example.com
The worldwide rise in cesarean section (CS) rates is becoming a
major public health concern and cause of considerable debate due
to potential maternal and perinatal risks, cost issues and inequity in
access.[1–4] The increase in CS rates observed in many developed
and middle-income countries contrasts sharply with the very low
rates in numerous low-resource settings, along with lack of access to
emergency obstetric care. According to recent data, in Middle
Africa, only 1.8% of all live birth deliveries occur by CS, compared
to 24.3% in North America and 31% and in Central America.
The main determinants of this disparity and specific reasons for the
increase in CS rates in most of the world remain unclear.
In order to propose and implement effective measures to reduce
or increase CS rates where necessary, it is first essential to identify
what groups of women are undergoing CS and investigate the
underlying reasons for trends in different settings. This requires the
use of a classification system that can best monitor and compare
CS rates in a standardized, reliable, consistent and action-oriented
manner. Such a classification system should be applicable
internationally and useful for clinicians and public health
authorities. Ideally, such a system should be simple, clinically
relevant, accountable, replicable and verifiable.
Over the last decades, several CS classification systems have been
created and proposed for different purposes.[6–12] However, to our
knowledge, therehasnotbeen a systematicreviewofthe existingCS
classification systems, analyzing advantages and deficiencies of each
system.Thisgapmotivated thepresentstudy.Webelieve thisreview
is a necessary step in the process of developing a standardized and
internationally accepted methodological framework for monitoring,
auditing, analyzing and comparing CS rates.
The objectives of this study were 1) to identify the main
available classification systems for CS through a systematic review
of the literature, and 2) to analyze qualitatively and compare the
advantages and deficiencies of each system through a pre-defined
comparative framework based on criteria recognized as important
by an international panel of experts.
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This study has two components: 1) an enquiry to experts about
critical characteristics of a classification for CS, and 2) a systematic
review of the literature to identify and critically appraise available
1) Questionnaire to panel of experts
by email or personally and asked to collaborate with this study by
answering a questionnaire on classifications of CS (Figure S1). They
were asked to grade a total of 18 proposed characteristics of a
classification system for CS from 1 to 9 (1=not important;
9=essential). These characteristics were divided into four main
domains (See Table 1): i) General characteristics, ii) Requirements,
equipment, necessary skills, iii) Use, and iv) Number and content of
categories. Their answers were tabulated in an Excel spreadsheet and
ranked according to frequency.Results fromthis analysisprovided the
2) Systematic Review
Types of studies.
practical (i.e. actually tested in patients) CS classification system or
model was eligible for inclusion in this review, regardless of the
level (e.g. facility, regional, national) in which it was applied. We
included studies regardless of whether or not the main purpose of
the manuscript was to propose a classification (i.e. the classification
could be a secondary outcome in the study).
classification systems for low-risk or unselected/general obstetric
patients were included.
Any study that described a theoretical or
Type of classification systems.
system described in sufficient detail to be understandable and
replicable was accepted. Any system or model that systematically
grouped or organized CS, obstetric populations or other items
(traits, characteristics, variables, attributes) potentially related to the
performance of CS into categories was considered a classification.
Whenever a classification was presented in more than one
publication, data were extracted initially from the original source
and complemented, if necessary, with information presented on
subsequent publications that reported on its use.
Search strategy for identification of studies.
electronic databases were searched (MEDLINE, EMBASE and
LILACS) for articles published from inception to November 26
2008. The search strategy used the following general terms,
expanded and adapted for each database: "classification" or
"taxonomy" or "nomenclature" or "terminology" and "cesarean
section" or "cesarean delivery" or "abdominal delivery" (exact terms
presented in Figure S2).
There were no language or country restrictions. Classic review
articles, textbooks and published letters were also examined for
potentially eligible studies. We checked the references of all articles
chosen for full-text evaluation. Experts were contacted and emails
sent to authors of potentially eligible studies, inquiring about
details, unpublished material and their knowledge of other
relevant studies on CS classification.
Screening and data extraction.
downloaded into Reference ManagerH software version 10. The
citations were organized and duplicates deleted. Two investigators
searches to select potentially relevant citations based on title and
abstracts, according to the criteria defined above. Discrepancies
Any type of CS classification
All citations identified were
Table 1. Questionnaire on characteristics of classifications for caesarean sections: grade given by experts.*
I. General characteristicsGrade#
1. Easy to understand8.5 (1.2)
2. Categories clearly defined and unambiguous8.6 (0.8)
3. Categories mutually exclusive7.3 (1.9)
4. Categories totally inclusive6.9 (2.8)
5. Categories identifiable prospectively 7.6 (1.5)
6. Reproducible and consistent 8.6 (0.6)
II. Requirement, equipment, skills
7. Guidance on how to deal with cases that have missing information7.7 (1.4)
8. Implementation possible without sophisticated equipment/hardware/software7.7 (1.8)
9. No extensive training/education needed for data collection 6.9 (2.3)
10. Information necessary for classification easy to obtain/readily available8.0 (1.5)
11.Minimal burden of data collection7.6 (1.5)
12. Capable of being locally adapted/modified6.9 (2.5)
13. Can be incorporated in routine data collection systems (e.g. billing and accounting) 7.4 (1.9)
14. Useful for clinicians 8.3 (1.6)
15. Useful for epidemiologists, public health specialists & researchers8.4 (0.9)
16. Useful to change clinical practice 8.5 (0.7)
17. Useful at local and national level8.2 (1.2)
18. Applicable worldwide8.0 (1.5)
*Each item was rated from 1 to 9 (1=not important; 9=essential).
#Mean (standard deviation).
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were resolved through consensus. When a citation was considered
relevant or when title/abstract was deemed insufficient for decision
on inclusion/exclusion, the full texts were retrieved and evaluated.
All articles selected at first screening were read and abstracted
individually by the two reviewers using a structured data-extraction
form specifically created for this review (Figure S3). Data extracted
were compared and discussed by the two reviewers and a final
extraction form was compiled. Information extracted from each
article included: 1) main purpose of classification, 2) type of study
(theoretical versus clinical), 3) characteristics of study and site
(setting, CS rate, number of cases, inclusion/exclusion criteria), 4)
general characteristics of the system, 5) requirements and skills for
implementation, 6) potential use of the classification, 7) specific
characteristicsoftheclassification,8)main strengths and weaknesses
of the system reported by the authors, and 9) main strengths and
weaknessesof the system as per reviewers. When data in the original
publication were not sufficiently detailed, authors were contacted
for additional information. In order to assure consistency in the
assessment of the classifications over time, the reviewers compared
newly extracted with previously extracted articles and forms.
Semi-qualitative evaluation of classifications.
strengths and weaknesses of each classification system. Seven specific
domains (ease of use, clarity, exclusiveness of categories, inclusiveness
of classification, possibility of using classification prospectively,
reproducibility and requirements for implementation) were graded
(2=good;1=median;0=poor).The final grade of eachclassification
ranged from 0 to 14, the higher the grading the better the
independently by the two reviewers, the answers were compared
and discussed until a consensus was reached.
To assess each classification beyond a theoretical model, we
created a set of 12 different clinical case-scenarios (Figure S4).
After reading and extracting data from each classification system,
the two reviewers independently tested the classification using
these 12 clinical cases. As opposed to the data extraction, the
results of these case scenarios were not compared, reviewed or
discussed between the reviewers since we aimed to assess inter-
rater agreement. Performance of each classification was assessed
by: a) the agreement between the two reviewers in classifying each
case in one of the proposed categories (reproducibility); b) the
possibility of including each of the 12 cases in no more than one of
the categories proposed by the classification (exclusiveness); and c)
the ability to include each of the 12 cases into a specific category
1) Questionnaire to panel of experts
Of the 46 experts contacted, 38 returned the questionnaire on
CS classifications (82% response rate). For each of the first three
domains: (i) general characteristics, (ii) requirements, equipment
and skills, and (iii) use of the classification, the median grade was
either 8 or 9 (over a maximum score of 9). Table 1 presents the
average grade given to each of the questions in these domains.
According to the experts, a CS classification should provide clearly
defined and unambiguous categories, the data needed should be
easy to obtain and it should be useful to help change clinical
practice. Two-thirds of the experts (25/38) answered that ideally, a
classification should have "between 6 and 10" main categories,
while the rest suggested "5 at the most" (data not shown).
2) Systematic Review
The search strategy yielded 1076 citations in the Medline and
EMBASE and 1872 in LILACS. A total of 60 were selected for
full-text evaluation (Figure 1). A total of 20 relevant studies were
Figure 1. Flow chart of the process of identifying and selecting classifications.
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retrieved and 27 different classifications were included (Table 2);
one study presented three classifications and two studies [13,14]
presented two classifications each. These 27 classifications were
grouped into 4 general types, according to the main unit being
classified: indication (N=12),[4,7,15–24] degree of urgency
and other systems (N=6).[4,13,30–32] Table 2 presents the
main characteristics and performance of the 27 classifications,
the overall score obtained and the results of the 12 case
Table 2. Main characteristics of 27 classifications for caesarean section and results from the 12 case-scenarios.
Main Characteristics* Case-scenarios (N=12)#
in . .1
Althabe 2004 22021119 1788
Anderson 1984 20220129880
Calvo 2009 22021018 58580
Prytherch 2007 22001027 33858
RCOG 2001 (a) 2002102742500
NICE 2004 21001127---
Gregory 1994 10201116 2580
Nico 1990 11021005 83170
Stanton 2008 20001025 50 588
20001025 4228 33
Cisse 1998 10001024834242
Kushtagi 2008 10000012
Van Dillen 2009 (a) 20221029 3300
21120028 67 428
Lucas 2000 20120027 58420
Van Dillen 2009
20201027 170 17
Huissoud 2009 20200026 50 1725
Robson 2001 2222222 14000
Denk 2006 2222221 13880
Cleary 1996 2220222 12800
Lieberman 1998 1001111533250
RCOG 2001 (b) 21002128---
RCOG 2001 (c) 210011227---
ICD 10 1992 10120015 5080
WHO 2004 200200154280
Guidotti 2008 20001003---
Code: 2=good, =regular, 0= poor, ; - = not applicable.
1-Easy: how much effort or time it takes to understand main concepts, logic and rules of the classification.
2-Clarity: clear, objective, precise and unambiguous definitions given for each category.
3- Mutually exclusive: each unit being classified by the system (e.g. woman or CS) can only be placed in a single of the existing categories.
4- Totally inclusive: Each and every unit being classified can be placed in at least one of the categories.
5- Prospective identification of categories: allows classification of the patient into one of the categories before she is taken to the operating theater.
6- Reproducibility: probability that the same case would be classified in the same category by different raters.
7- Implementability: human and material requirements needed to introduce and maintain the classification in continuous use.
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Table 3 shows the main general strengths and weaknesses of
each the 4 general types of classifications. Outlines of each of the
27 classifications are provided in Figure S5.
Indication based classifications.
details of the 12 classifications that belong to this category. Four
[19,20,23,24] of the twelve indication classifications presented only
theoretical models.The other
18,21,22] were tested on actual patients in studies with sample
sizes ranging from 498 to 454,668 deliveries and CS rates from 0.6
to 25%. Only three classifications [15,16,22] provided clearly
defined and unambiguous categories. For example, Althabe et
al proposed a CS classification along with a guideline
containing specific, precise and clear definitions for indications
such as dystocia, acute intrapartum fetal distress and several
maternal indications, whereas Anderson’s classification also
used these same terms but did not provide any details or
parameters on how to decide that this was indeed the indication
for the CS. Therefore, Althabe’s classification was considered clear
in its definition of categories, while Anderson’s was considered
unclear. On the other hand, Anderson’s classification provided
clear hierarchical rules on how to classify a woman with more than
one indication for CS (for e.g. a case with previous CS and
dystocia), while Althabe’s classification did not provide instructions
on how to deal with such cases, which could theoretically be
classified in more than one category. This lead us to grade the
system proposed by Anderson as being mutually exclusive, while
Althabe’s classification scored poorly on this characteristic. Only
two classifications offered mutually exclusive categories[7,18] and
five were totally inclusive.[4,7,15,16,21], meaning that each and
every possible indication could be placed in at least one of the
categoriesprovided by the
classifications were judged easy to implement.[4,7,17,20,22–24]
None of the classifications allowed prospective identification for all
categories and in two classifications[7,19] less than half of the
Table 4 presents the main
authors.Over halfof these
categories could be prospectively identifiable. This refers to the
possibility of including a woman into one of the existing indication
categories provided by the authors before she is actually taken to
Anderson’s[7,15] obtained the best overall grade for this group
of classifications (9 out of a maximum of 14 points).
Urgency based classifications.
characteristics of these classifications. All five classifications based
on degree of urgency had been tested in real life, in studies with
sample sizes ranging from 18 to 407 cases in settings with CS rates
ranging from 17.7% to 27%. All were judged easy to understand
and implement. Three had mutually exclusive categories,[14,25]
and two were totallyinclusive.[13,14,26]
classifications allowed prospective identification for all categories
and in two, less than half of the categories proposed could be
prospectively identifiable. Van Dillen’s classification obtained
the best overall grade (9 out of a possible maximum of 14)
characteristics of all four women-based classifications. These were
tested in real life, with samples ranging from 2876 to 222,013 births,
in settings with CS rates ranging from 7.9% to 31%. Three
classifications presented mutually exclusive categories,[6,27,28] two
were totally inclusive,[6,28] and two were judged very easy to
implement.[6,27] Although the 10-group (Robson’s) classification
received the maximum grade in this type of classification, the 8-
group (Denk) and the case-mix (Cleary) classifications also
obtained high grades (Table 2).
Other types of classifications.
classifications was just a theoretical model that was not tested in
real life; the other five were tested in studies involving from 137
to 32,222 cases in settings with CS rates ranging from 23% to 35%.
These classifications proposed from 3 to 21 main categories and up
classifications, Althabe and
Table 5 presents the main
Table 6 presents the main
The six other types of
Table 7.One ofthese
Table 3. Main types of Classification Systems for cesarean section: general strengths and weaknesses.
and main question StrengthsWeaknesses
Information usually routinely collected in any maternity,
therefore it is easy to implement.
Allows to look at the contribution of:
N maternal vs fetal indications
N absolute vs relative indications
No clear uniform definitions for common indications (e.g. fetal distress, failure
to progress, dystocia).
Poor reproducibility unless clear diagnostic definitions are given and rules on
hierarchy of classification (for cases with .1 indication)
Categories are not mutually exclusive (could be .1 primary indication)
Not totally inclusive (unless large number or "Other indications" category exist)
"Other Indications" category makes data analysis difficult
Not very useful to change clinical practice
Degree of urgency
Conceptually easy, almost intuitive
Could improve communication between professionals
(obstetricians, anesthesiologists, nurses) and ultimately
improve maternal-perinatal outcomes
Does not provide clear definitions for each of the categories
Poor reproducibility unless clear definitions are given and staff is trained
Cut-offs proposed (time to delivery) are subjective and not evidence-based.
Not very useful to change clinical practice
Limited utility for policy makers, epidemiologists, public health specialists
Conceptually easy and clearly defined categories
Information routinely collected in most maternities,
easy to implement
Mutually exclusive and most are totally inclusive
Prospective, allows modifications in clinical practice
Tested in different countries and in large datasets
Does not look at the reason for performing CS on that woman
The case-mix ones are not totally inclusive; they analyze only a portion of all
women delivering by CS at a facility
BY WHOM and
Address important but neglected details often
that could compromise clinical outcomes and should
receive more investment
Offer valuable info for administrators and policy makers
Some need adjustment, improvement, clearer definitions
Several are just theoretical models and have not been tested in real life
Some of the data required not usually collected in most maternities; would
require some effort to be implemented; limited utility for clinicians
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to 39 subcategories. None of these classifications had mutually
exclusive categories and two were totally inclusive.[30,32]
This review identified 27 classification systems which were
grouped into 4 general types, based on the main unit being
classified. Classifications based on indications for CS were the
most frequent type. The main question answered by this type of
classification is "why" the CS was being performed, an information
routinely registered and available in any maternity, therefore
making this type of system easy to implement in any setting. On
the negative side, almost all of the models in this group of
classifications had categories that are not mutually exclusive and
had low reproducibility. Due to these main drawbacks, the
disagreement between reviewers in the case-scenarios was high
(see Table 2); in six classifications there was disagreement in at
least 6 of the 12 case-scenarios. Main weaknesses of these systems
include: a) poor/unclear definitions for some of the most common
conditions that lead to CS (e.g. dystocia, fetal distress) and
therefore questionable inter-rater reproducibility; b) categories not
mutually exclusive, implying that there would need to be some
kind of hierarchy guideline to classify cases with .1 primary
indication; c) not being totally inclusive, unless an extensive list of
indications is provided or an ‘‘Other indications’’ category is
created; and d) not be very useful to change clinical practice, since
most of the indications are not prospectively identifiable (Table 3).
This type of classifications proposed the largest number of
categories, although some, such as Anderson’s were quite
simple. This specific classification, together with Althabe’s had the
highest rating in this group. Unlike others in this group,
Anderson’s classification was judged easy to understand and
implement, had a good inter-rater reproducibility and was all
inclusive. A unique asset of this model was that it presented clear
hierarchical rules for classifying cases with .1 indication for CS
which made the categories mutually exclusive.
Table 4. Classifications for caesarean sections based on indications.
Author, year, name N of major/subcategories: main categoriesSpecial Characteristic
Althabe, 2004, Mutually
Exclusive Clinical Indication
System for Non-emergency
8/0: Extreme emergency, previous CS, dystocia,
intrapartum acute fetal distress, podalic presentation,
maternal causes, fetal causes, Other
Gives detailed definitions and flow charts for most proposed categories
(unpublished material obtained from authors). Tested on real patients.
Anderson & Lomas, 1984,
Causal Model for Indications
5/0: Previous CS, breech, dystocia, fetal distress, otherSimple, few and well defined categories. One of the few classifications
which gives clear hierarchical decision rules.Tested on real patients.
Calvo 2009, Mallorca
Multifaceted System for
Classification of CS
2/17: Prescheduled CS, emergency CS Good definitions for most indications but may be difficult to implement
in developing countries. Tested on real patients.
Prytherch 2007 Modified
Unmet Obstetric Needs
5/6: Antepartum haemorrhage, malpresentations,
Ruptured uterus, cephalo-pelvic
disproportion/obstructed labour, .2 previous CS
Simple and short, useful in settings with low CS rates. Covers only CS
related to absolute maternal indications. Tested on real patients.
RCGO, 2001, Primary
indications for CS
211/0 Relatively easy but lacks clear definitions in some categories and
hierarchical rules for classifying cases with .1 indication. Tested on real
NICE, 2004 Evidence based
8/0: Breech, multiple pregnancy, preterm birth,
SGA, PP, cephalopelvic disproportion in labour,
mother-to-child transmission of maternal infections,
Incomplete. Could help to evaluate degree of adherence to evidence-
based recommendations in different settings. Not tested on real
Gregory, 1994 Indications for
5/21: Breech, dystocia, fetal distress, elective
repeat CS, other
Conceptually easy. Tries to analyse and compare elective repeat CS
versus repeat CS for medical reasons. Tested on real patients.
Nico, 1990, CS indications
with dystocia or not.
3/6: Programmed CS, not programmed CS but
not due to failure to progress, CS for failure to
progress or dystocia
Gives clear definitions for several types of dystocia, an important
indication for CS. Tested on real patients.
Stanton, 2008 Absolute
and non-absolute maternal
indications for CS
2/13: Absolute maternal indications (hierarchical),
Non absolute indications (non hierarchical)
Conceptually easy to understand and useful for developing countries.
Could improve if more detailed definitions were given for each of the
categories, along with examples. Not tested on real patients.
Unmet Needs Network,
2000 Absolute maternal
indications for CS
4/13: Malpresentations and malpositions, antepartum
haemorrhage, maternal diseases, fetal reasons
Conceptually easy, useful from public health, helps detect underuse of
CS. Clearer definitions of categories would improve reproducibility.
Tested on real patients.
Cisse 1993, Senegalese 3
groups of indications for CS
3/9: Obligatory, prudent, necessaryRelatively easy, meaningful in countries/settings with very low CS rates.
Clearer definitions of categories would improve reproducibility. Tested
on real patients.
Kushtagi 2008, Documentation
of indication for delivery and
2/5: Indication for termination, Indication for CSSimple and easy, focuses on conceptual distinctions in trying to
understand reasons that lead to CS. Not tested on real patients.
CS: Caesarean section, NICE: National Institute for Clinical Excellence, PP: Placenta praevia, RCOG: Royal College of Obstetricians and Gynecologists, Subcat: Subcategory,
VD: Vaginal delivery.
1. Breech, malpresentation/unstable lie, multiple pregnancy, presumed fetal compromise, cord prolapse, chorioamnionitis, other fetal, PP actively bleeding, PP not
actively bleeding, antepartum/intrapartum haemorrhage, placental abruption, pre-eclampsia/eclampsia, maternal medical disease, failure to progress (induction/in
labour), previous CS, uterine rupture, maternal request, previous poor obstetric outcome, previous physically or emotionally traumatic VD, previous infertility, other
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Classifications based on degree of urgency for CS were also
theoretically easy to understand and implement due to the reduced
number of categories proposed (Table 2). This type of classifica-
tion, which basically answers "when" (or how quickly) the CS
should be performed, could improve communication between
health professionals (nurses, obstetricians, anesthesiologists) thus
potentially lead to better maternal and perinatal outcomes. A weak
point of several of these classifications is the lack of clear and
unambiguous definitions for each of the proposed categories,
which could compromise inter-rater reproducibility, comparability
and interpretation. Three of the five presented 50% or more of
disagreement between reviewers in the case-scenarios. Addition-
ally, the cut-offs (time to delivery intervals) proposed to define each
category are subjective and not evidence-based. Finally, the
amount of information provided by these systems is very limited
and therefore this type of classification would have to be
complemented by other types, in order to be more useful.
Classifications based on woman characteristics basically tell
us "who" is being submitted to CS, based on maternal and
pregnancy characteristics. These represented 4/27 systems
identified. Most of these classifications are conceptually easy and
simple, have relatively few, and clearly defined categories which
are mutually exclusive and allow cases to be prospectively
identified upon admission, which could be useful to change
clinical practice. Due to all these characteristics, these classifica-
tions could be easily implemented and would be highly
reproducible as shown with the high agreement in the case
scenarios (Table 2). Although most of these classifications are
totally inclusive, the case-mix types are not since they only assess
CS in a subgroup of women with a specific set of predefined
characteristics, such as Cleary’s "standard primipara". Rob-
son’s 10 group, along with Denk’s 8 group classifications
got the highest overall theoretical ratings and also performed very
well on the practical case scenarios.
Other types of classifications, which represented 6/27
classifications, address questions such as "where" the CS is being
performed, "by whom", "how" (under what conditions and
circumstances) or combinations of questions. By focusing on
aspects often overlooked by other classifications, these systems
provide administrators and with useful information about aspects
that could affect maternal and perinatal outcomes and perhaps
need more attention and investment. However, some of these
classifications would need improvement and clearer definitions of
some categories. Moreover, several of these systems are only
theoretical and have never been tested in real setting. Since some
of the data required are not usually collected in most maternities,
these systems would require some effort and time to be
implemented and not all items in these classifications will be
relevant or applicable in all settings.
Based on the methodology used in this systematic review,
Anderson’s and Althabe’s classifications obtained the
highest grades and the best performance for indication-based
classifications. This can be attributed to the fact that these two
classifications provide very clear definitions of categories and
precise decision rules or hierarchy on how to classify a case with
.1 indication into a single specific category. In the degree of
urgency systems, Van Dillen 2009a was the best rated
classification. Robson’s 10-group model was in first place
among the women-based classifications and obtained the highest
overall grade and best performance on the case-scenarios.
Each of these classifications offer intrinsic advantages and
disadvantages and could be considered more or less useful
depending on the objectives of the user. The two classifications
with the best overall scores in this group (Robson and Denk [6,28])
are easy to understand, clear, mutually exclusive, totally inclusive,
reproducible and allow prospective identification of categories.
Additionally, they offer flexibility to adapt to different clinical
settings, important aspects if one wishes to implement modifications
Table 5. Classifications for caesarean sections based on degree of urgency.
Major categories/subcategories: Description of major
categories Special Characteristic
Van Dillen 2009 (a)
Urgency of CS classification
based on clinical definition with
N 1: immediate threat to the life of mother or fetus
N 2: Maternal or fetal compromise but not immediately
N 3: The mother needs early delivery but there is no
maternal or fetal compromise
N 4: Delivery timed to suit the mother or the staff
Relatively easy and an improvement over simple binary
classification. Could improve if more detailed definitions
were given for each of the categories, along with examples.
A total of 79 doctors tested it on 18 theoretical case-
Nicopoullos 2003, Priority
of delivery by CS
N Crash (10–20 min)
N Urgent (up to 30 min)
N Emergency (up to 2 h)
N Elective (no time limit)
Simple, few and well defined categories. However, offers no
evidence to support the cut-offs proposed for each
category. Tested on real patients.
Lucas 2000, Urgency of
CS classification based on
Same as Van Dillen but with less definitions and guidelines
for use. Conceptually easy but needs to exemplify better the
clinical situations that would be classified under each
category. Tested on real patients.
Van Dillen 2009 (b)
Traditional Binary System for
Degree of Urgency
N 1ary: if vaginal delivery was not intended
N 2ary: if vaginal delivery was attempted
Simple and easy, but offers very limited amount of
information. Could improve if more detailed definitions
were given for each of the categories, along with example. A
total of 79 doctors tested it on 18 theoretical case-scenarios.
Color codes for
N green: non-urgent CS (up to 1 h interval)
N yellow: urgent (,30 minutes)
N red: extremely urgent (,15 minutes)
Conceptually easy and simple. Could improve
communication between staff and ultimately improve
maternal and perinatal outcomes. Tested on real patients.
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in clinical protocols to decrease or increase CS rates. Robson’s
classification offers the possibility of subdividing three of its main
categories into subcategories. Namely women at term with a
singleton, cephalic, term fetus being submitted to a CS either after
induction (groups 2a-nulliparas and 4a-multiparas) or electively
(groups 2b-nulliparas or 4b-nulliparas), and women with either one
or more than one previous CS (group 5a and 5b, respectively).
These subdivisions would provide important information and help
to understand differences between different settings or at the same
setting over time, in these 3 categories. Despite the fact that the ‘‘10-
group classification’’ would actually become a ‘‘13-group classifica-
tion’’, these subdivisions do not add any substantial amount of work
since the information needed is routinely available in maternal
charts. A problem with the women-based classifications is that they
do not present why (indications) or when (degree of urgency) the CS
was performed, which are also important aspects.
After a thorough and careful analysis of a large number of
classifications and systems for ceasarean deliveries, we acknowl-
edge the fact that, at the present, there is no single ideal
classification for all settings and that would fulfill the expectations
and needs of every health professional. The choice of a specific
classification will depend on the main objectives of the
professionals who are going to use it. However, given the flexibility
of some of the existing classifications, we believe it would be
possible to create a hybrid model based on the woman-
characteristics system with additional layers of other classifications
for each of the individual categories proposed in the woman’s
classification. For instance, Van Dillen and/or a modified
version of Anderson’s indication system could be used within
each of the 10 (or 13) categories proposed by Robson or the 8
categories proposed by Denk. This would allow comparison of
degree of urgency for CS as well as indications in a homogeneous
group of women, for example multiparas at term in spontaneous
labor with a singleton cephalic fetus (Robson’s group 3a), which
represent a large proportion of all deliveries in any setting.
This systematic review had several strong points, starting with
its uniqueness. This is the first study specifically designed to
retrieve, analyze and critically appraise existing classifications for
CS. We developed a broad search strategy, in order to capture the
largest possible number of publications on this topic. We tried to
reduce bias by using a panel of experts to determine what variables
to analyze and two independent reviewers to extract data and test
each classification in practical case-scenarios.
Potential limitations included difficulties in retrieving articles
through electronic databases, possibly due to the lack of
appropriate keywords to index this topic. We also acknowledge
the possible existence of other unpublished CS classifications that
could not be located, despite efforts to contact experts.
Table 6. Classifications for caesarean sections based on women’s characteristics.
Author, year Major categories/subcategories: Description of major categories Special Characteristic
The 10 group system.
1: Nulliparous, single cephalic term, spontaneous labour
2: Nulliparous single cephalic term, induced or CS before labour
3: Multiparous no previous scar, single cephalic term, spontaneous labour
4: Multiparous no previous scar, single cephalic term, induced or CS before labour
5: All multiparous 1 or more previous scar, single cephalic term
6: All nulliparous, single breech
7: All multiparous, single breech including those with previous scars
8: All multiple pregnancies including those with previous scars
9: All singleton pregnancies in transverse or oblique lie, including women
with previous scars
10: All women with single cephalic preterm pregnancy, including women
with previous scars
Conceptually easy, clearly defined categories
that are totally inclusive, mutually exclusive;
little room for misunderstanding or
misclassification. All info is easily available
from medical records. Could be easy to
implement in both high and low resource
settings. Prospective classification allows for
changes in clinical management. However,
does not specify reason for CS. Tested on real
8 group system
N Standard nullipara,
N Standard multipara,
N Malpresentation nullipara
N Malpresentation multipara,
N All multiple gestation,
N Standard with prior CS,
N All other with prior CS
Same as Robson 2001. The idea of separating
1aryfrom repeat CS is simple and may have
benefits. Tested on real patients.
White, 20–34 year-old, height .155 cm, with singleton cephalic fetus .37
weeks, in the unit at which she originally booked, excluding cases with pre-existing
diseases or complications of pregnancy.
Conceptually easy, well defined parameters.
Analyzes a specific group of women that
represent a large fraction of the population
delivering in most maternities. Not totally
inclusive and definition is very regional (e.g., it
would be irrelevant for African countries).
Would therefore need to be adapted to
different settings. Tested on real patients.
Case mix model for
adjusting CS rates
N Multipara with no previous CS
N Multipara with one or more previous CS.
It proposes a matrix, mixing women’s
characteristics and some indications. Would
allow fair comparisons between facilities of
different levels. However, requires a step of
‘‘standardization’’ which involves statistical
expertise and software. Tested on real
CS Classifications Review
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Additionally, despite the use of strict methodology and double data
extraction at all steps of the systematic review, there is always
potential for subjectivity in the semi-qualitative assessment of the
classifications. We also acknowledge that the scoring system
presented on Table 2 may have limitations. To the best of our
knowledge, there are no validated tools for assessing the
characteristics of any classification system. This led us to create
such a tool, which we tried to keep as simple and objective as
possible. However, the use of only three possible grades for each of
the domains of the classifications, although straightforward and
easy, may be questionable.
Overall, we detected a basic need for clear, unambiguous and
precise definitions for common obstetrical diagnoses and terms
used to define categories in many of the classifications.
Standardization of these terms is an essential step to improve
inter-rater reproducibility and allow consistent and reliable
comparison of information at the same setting over time and
between different settings at various levels (local, regional and
national). Specifically, in the indication classifications, terms/
diagnoses such as fetal distress, dystocia, failure to progress,
cephalo-pelvic disproportion, obstructed labor, macrosomia, failed
induction and failed trial of labor would need to be more clearly
defined using unambiguous and preferably evidence-based
terminology. Furthermore, it would be preferable to avoid the
need for sophisticated equipments or technology (such as
electronic fetal monitors or scalp pH) not routinely available in
low-resource settings. Despite a few discrepancies, the terms and
definitions used in the degree of urgency classifications (for e.g.
urgent, emergency, crash, scheduled and elective) tend to be more
precisely defined but none of them are evidence-based. Therefore,
there is a need to conduct studies that assess if there are any
significant differences in maternal and perinatal morbidity and
mortality according to the time interval between decision to
incision (or actual delivery). Only then would it be possible to
establish more precise cut-offs used to define each of these
In the context of international recognition of the difficulties in
understanding and controlling the increase and inequitable use of
CS worldwide, this systematic review suggests that, among all
classifications identified, women-based classifications in general,
and Robson’s classification, in particular, would be in the best
position to fulfill current international and local needs, and that
efforts to develop an internationally applicable CS classification
would be most appropriately placed in building upon this
classification. The dissemination and implementation of a single
CS classification system will allow auditing, analyzing and
comparing rates of CS across different hospitals, cities, countries
and regions. With a clear understanding of why, when, where,
how and on whom CS are being performed, it would then be
possible to propose and implement effective strategies and actions
specifically targeted at high-risk groups, and thus possibly reduce
or increase the rate of CS in order to continue improving maternal
and perinatal outcomes.
tional panel of experts to rate items considered important in a
classificaiton for cesarean sections.
Survey questionnaire. Questionnaire sent to interna-
Table 7. Other types of classifications for caesarean sections.
Author, year Major categories/subcategories: Description of major categoriesSpecial Characteristic
RCOG 2001, CS according
to organizational and
Size of maternity unit, presence of neonatal intensive care unit,
being a tertiary referral center, affiliation with a medical school,
availability of 24-hour anaesthetist
Looks at important factors generally overlooked Easy
system with clear and well defined categories; data easily
available at most settings. Could be useful to compare
similar settings as to rates of CS, indications or types of
patients. Tested on real patients.
RCOG 2001, Potentially
PP, placental abruption, at full cervical dilation, in obese women,
for preterm delivery ,32 weeks, for multiple pregnancy, in
women with multiple previous CS
Simple and easy to implement. Could be useful to audit
quality/quantity of human resources available in different
settings and over time and see how this impacts maternal
and perinatal morbidity and mortality. Tested on real
obstetric care in
Indication, name of surgeon, grade of surgeon, name of assistant,
name of anaesthetist, type of anaesthetic, skin incision time, skin
incision type, surgical findings, uterine incision type, engagement of
presenting part, fetal delivery, placental delivery, uterine cavity check,
presence of paediatrician, adnexal check, estimate of blood loss,
post-op care plan.
It tries to standardize the documentation on CS. Important
as a legal instrument in cases of litigation and allows
auditing and improvement of care. Tested on real patients.
ICD 10 classification
Single delivery by elective CS; single delivery by emergency CS; single
delivery by cesarean hysterectomy; other single delivery by CS; single
delivery by CS, unspecified; multiple delivery, all by CS; other multiple
delivery by combination of methods
Few categories, therefore simple, easy and quick to fill in,
well known internationally. However it is of limited clinical
relevance. Tested on real patients.
Elective CS, no labour; emergency CS, no labour; intrapartum CS
Simple and easy, but offers very limited amount of
information. Could improve if more detailed definitions
were given for each of the categories, along with
examples. Tested on real patients.
Safety of CS in resource
Necessity for a CS, maternal condition, fetal condition, surgical team,
surgical procedure, anaesthesia procedure, surgical Instruments,
anaesthesia equipment, operative theater conditions, drugs, maternal
post-operative care, neonatal post-operative care
Conceptually easy. Takes into account other elements
beyond indication that can affect outcomes of CS.
However, since necessary data is not routinely collected, it
would require some effort and training to implement. Not
tested on real patients.
CS Classifications Review
PLoS ONE | www.plosone.org9 January 2011 | Volume 6 | Issue 1 | e14566
Found at: doi:10.1371/journal.pone.0014566.s001 (0.07 MB Download full-text
used for systematic review.
Found at: doi:10.1371/journal.pone.0014566.s002 (0.03 MB
Search Strategy for CS classifications. Search strategy
appraise existing Cesarean section classifications.
Found at: doi:10.1371/journal.pone.0014566.s003 (0.08 MB
Data extraction form used to analyse and critically
created to test the existing classifications for Cesarean sections.
Found at: doi:10.1371/journal.pone.0014566.s004 (0.03 MB
Clinical case scenarios. Twelve clinical case scenarios
included in the systematic review.
Outline of the 27 classifications for Cesarean sections
Found at: doi:10.1371/journal.pone.0014566.s005 (0.20 MB
Found at: doi:10.1371/journal.pone.0014566.s006 (0.06 MB
The views expressed are solely those of the authors and do not necessarily
reflect the decisions or stated policy of the World Health Organization.
Conceived and designed the experiments: MRT APB JPS MW MG MM.
Performed the experiments: MRT APB. Analyzed the data: MRT APB
JPS MW TJA MG MM. Contributed reagents/materials/analysis tools:
TJA. Wrote the paper: MRT APB JPS MW TJA MG MM.
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