AST classification of proximal humeral fractures: introduction and interobserver reliability assessment

  • Christian Cuny
  • Cedric Baumann
  • Julien Mayer
  • Didier Guignand
  • M’barek Irrazi
  • Aboubekr Berrichi
  • Nicolas Ionescu
  • Francis Guillemin
Original Article



This article introduces an alphanumeric AST (Articular, Surgical neck, Tuberosities) classification of proximal humeral fractures, based on the number, localization, and displacement of articular and extra-articular fragments. All possible cases of proximal humeral fractures can be assessed from a single figure using this classification. The aim of the study was thus to describe the AST classification and to assess interobserver reliability.


This classification is based on a single figure, allowing an easy description of the anatomic variants of different proximal humeral fractures. The severity of the fracture is determined by the fragment displacement in angular degrees and the major linear displacement in millimeters. AST reproducibility was assessed and compared with Neer, AO, and Duparc classifications, commonly used in clinical practice. The interobserver agreement was measured with Cohen’s kappa coefficients and their 95% confidence intervals.


Thirteen independent observers analyzed a total of 64 X-rays. Overall kappa coefficients were 0.34, 0.29, 0.24, and 0.25 for AST, Neer, AO, and Duparc classifications, respectively.


The AST classification, which is easier to use because it is based on only one figure, is at least as reproducible as other proximal humeral fracture classifications.


Proximal humeral fractures Classification Interobserver reliability 


Proximal humeral fractures show considerable morbidity rates. Classification systems can be used to guide treatment and to select the best possible conservative or surgical management strategy. Unfortunately, classifications of proximal humeral fractures show poor intra- and interobserver reliability [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]. We developed a new proximal humeral fractures classification system, the AST (Articular, Surgical neck, and Tuberosities), which relies on the articular and extra-articular characteristics of the fractures lines and displacement of the fragments. We then conducted an interobserver reproducibility study to assess the concordance between this classification and three other commonly used classifications: Neer, AO, and Duparc [12, 13, 14, 15, 16].

Materials and methods

AST classification

All possible cases of proximal humeral fractures can be labeled from a single figure using this alphanumeric classification (Fig. 1). Type A fractures correspond to articular fractures, meaning articular or anatomical neck fractures of Boehler’s classification [17]. A1 fractures are non-displaced fractures of the anatomical neck. A2 fractures show limited displacement, with the cephalic fragment still in contact with the metaphysis (Fig. 2). This is equivalent to a cephalo-tuberosity Level II fracture of Duparc or a valgus impacted fracture of Jakob [15]. A3 fractures present an important displacement and, in particular, a loss of contact between the cephalic and metaphyseal fragments (Fig. 3). A3 fractures, or “disengaged” fractures, represent the most complex type of fractures, leading to the interruption or serious compromising of cephalic vascularization. Contrary to other classifications, the AST classification does not principally rely on the number of fragments [12, 13]. A2 fractures usually present two tubercular fragments, but they could also present only one tubercular fragment. Similarly, it is possible to encounter an A3 fracture without tubercular fragment. The isolated fracture of the anatomical neck corresponds to a genuine decapitation. Vascularization is totally interrupted, leading to a situation of indisputable gravity. A2 and A3 articular fractures may also be associated with dislocation. In this case, the letter “D” will be added (e.g., A2D or A3D). Type S fractures, for surgical neck, correspond to extra-articular fractures (Fig. 4), indicating surgical neck fractures of Boehler’s classification [17]. The fracture line may be unique, and in this case, the fracture is simply called “S.” If there is a second line with detachment of the greater tuberosity, the fracture is called “ST,” with T in upper case (Fig. 5). In rare cases, the second fracture line can go through the lesser tuberosity. In this case, the fracture is called “St” with t in lower case. From the above designations, A2, A3, S, and ST are the most frequently encountered fractures in common clinical practice. The other fractures are less common and include T in their label. The isolated fracture of greater tuberosity is called “T” (upper case) (Fig. 6). The very rare isolated fracture of lesser tuberosity is called “t” (lower case). There are also two kinds of fractures with a transverse line of the humeral head after a dislocation. TAS correspond to simple trans-articular fractures, which are cephalo-metaphyseal fractures starting from the dislocation notch and descending to the metaphysis. The letter “D” will be added in case of dislocation (Fig. 7). Unlike Duparc’s classification, the anterior and posterior characteristic of the notch is not specified. Finally, TAC correspond to trans-articular comminuted fractures and are equivalent to Head Splitting Fractures of Neer’s classification. Each term and its corresponding illustration are summarized in Fig. 1, which is easy to memorize. For most authors, the severity of proximal humeral fractures is associated with displacement, rather than the number of fragments [11, 18, 19]. The AST classification allows for the quantifying of the displacement of fragments. In everyday clinical practice, the displacement of fragments of a proximal humeral fracture will be assessed from at least two X-ray views, frontal and lateral. The frontal view is taken from ¾, with the forearm parallel to the X-rays. The lateral view is taken from ¾, with the forearm parallel to the radiologic plate and perpendicular to the X-rays. Under these conditions, on the frontal view, the humeral head inclination is 45° in comparison with the diaphyseal axis of the humerus. On the lateral view, the inclination of the humeral head is 60° from the diaphyseal axis, corresponding to 30° with the horizontal (humeral head retroversion). The AST classification allows for measuring humeral head tilting, in comparison with a reference inclination of 45° frontal and 30° lateral. This lateral X-ray is important because the tilt and translation are often more significant than on a frontal X-ray. Tilt measurement is recorded in degrees (Fig. 8). Similarly, in case of surgical neck fracture, the angle between the fragments is assessed in degrees (Fig. 9). Also, AST quantifies displacement by measuring the linear distance between fragments. The major linear displacement of a fragment from its anatomical position is expressed in millimeters. Beyond classification purposes, this assessment guides the surgical strategy.
Fig. 1

AST classification

Fig. 2

“A2” articular valgus impacted

Fig. 3

“A3” articular disengaged

Fig. 4

“S” surgical neck

Fig. 5

“ST” surgical neck with three fragments

Fig. 6

“T” greater tuberosity

Fig. 7

“TASD” trans-articular simple dislocated

Fig. 8

“A2-40°-10 mm” (Articular impacted with 40° of cephalic tilting and 10 mm of linear displacement)

Fig. 9

“S-60°-20 mm” (Surgical neck with an angle of 60° and 20 mm of linear displacement)

Other classifications

Neer, AO, and Duparc classifications are three commonly used methods in clinical practice. Neer’s classification was proposed in 1970 and is currently the most used internationally [12, 13]. The Neer scheme uses Codman’s figure, which individualizes four parts (head, two tuberosities, and metaphysis). Neer’s classification is based on one figure, showing the different kinds of fractures. Half of the picture shows fracture dislocation, and the term “Part” is use by Neer for a displacement of at least 45° and/or 1 cm. The AO classification was proposed in 1989 [14, 15]. It is alphanumeric according to usual terminology and distinguishes unifocal extra-articular fractures (A), bi-focal extra-articular fractures (B), and articular fractures (C). A number is associated with each letter to describe the gravity of the displacement. Duparc’s classification was published in 1976 [16]. It sorts fractures into two major groups: articular and extra-articular. Articular fractures correspond to the anatomical neck. “C” stands for cephalic and “T” for tuberosity. They can be isolated or associated with tubercular fractures. Duparc’s classification distinguishes CT1, which are not displaced; CT2, which are displaced and impacted; and CT3, which are disengaged. CT4 are complex articular fractures associated with dislocation. Fractures from the notch are individualized in case of dislocation and are classified in posterior and anterior dislocations. Extra-articular types correspond to isolated lesser or greater tuberosity fractures and under tuberosity fractures, with description of the fracture line in comparison with the humeral head. Under tuberosity fractures with an intermediate fragment of the greater or lesser tuberosity are separated.


A reproducibility study was performed by asking independent observers to characterize radiographic images using the AST, Neer, AO, and Duparc classifications. Patients consecutively operated on at our institution over the study period were included in the analysis. X-rays of proximal humeral fractures were selected and printed on CDs. Most X-rays included frontal and lateral views. Thirteen observers were invited to analyze the X-rays and classify the fractures according to four classifications: AST, Neer, AO, and Duparc. The observers were all orthopedic surgeons with an interest in shoulder surgery. Three were shoulder specialists. Five observers were currently working in the department where the AST classification originated (intra-institutional), and the other eight surgeons were from other institutions (extra-institutional). The first author, who designed the AST classification, did not take part in this study.


In order to guarantee independency of reading between the four classifications, different orders for filling the grid were assigned to each participant (ABCD, BCDA, CDAB, etc.) using a randomized list.

Statistical analysis

The first step of the analysis was the description of the observers’ readings, using the four classifications. The second step was the study of multi-observer reliability in each of the four classifications for each participant. Concordance between participants was assessed with the multiple observer Kappa coefficients and their 95% confidence interval, according to Fleiss [20] and applied to the following:
  • Each classification with a simple Kappa coefficient for binary variables;

  • The overall classification with a weighted Kappa coefficient for multiple modality variables.

The rule used to interpret reliability was proposed by Landis and Koch in 1977 [21]. Finally, the institution of the participants was investigated as a source of possible confusion. We used a z test to compare Kappa coefficients. The statistical threshold for significance was set at 0.05. Statistical analyses were performed with the SAS software, version 9.1 (SAS Institute Inc., 2002).


A total of 64 X-rays were included in the study. Overall kappa coefficients were 0.34, 0.29, 0.24, and 0.25 for AST, Neer, AO, and Duparc classifications, respectively. The results of inter-observer reliability (n = 13) are presented in Table 1. AST kappa is at least as good as the other studied classifications, by intra- or extra-institution judges (0.38 and 0.32, respectively). AST and Duparc’s classifications presented similar kappa values, which were significantly higher than the kappa for AO and Neer classifications. Kappa coefficients were significantly higher in the intra-institutional group than in the extra-institutional group, for AST (P = 0.006), AO (P = 0.0003), and Duparc (P = 0.001) classifications. The highest inter-observer reliability was observed with intra-institutional judges for the AST and Duparc (k = 0.38) classifications. The concordance among the four proximal humeral fractures classifications was poor and depended on the comparison of classifications and on the institution of the participants.
Table 1

Inter-observer reliability for observers belonging (intra-) or not (extra-) to the institution where the AST classification was designed


Kappa [IC 95%]

P value*

Overall sample




0.24 [0.22; 0.26]

0.28 [0.24; 0.32]

0.20 [0.18; 0.22]



0.34 [0.32; 0.36]

0.38 [0.34; 0.42]

0.32 [0.30; 0.34]



0.25 [0.23; 0.27]

0.38 [0.34; 0.42]

0.31 [0.29; 0.33]



0.29 [0.27; 0.31]

0.29 [0.25; 0.33]

0.27 [0.23; 0.31]


* z test



The potential clinical usefulness of the AST classification is mainly based on its simplicity of use and on the evaluation of fracture gravity by quantification of the displacement of fragments. The simplicity of use is due to the utilization of a single figure (Fig. 1), representing all possible proximal humeral fractures. This figure includes pictures and an alphanumeric denomination of the fractures. It is especially interesting that four out of 10 pictures (A2, A3, S, ST) represent most fractures encountered in clinical practice. This classification is based on the articular or extra-articular localization of the fracture line, rather than the number of fragments. Type A fractures are articular fractures, and Type S fractures are extra-articular fractures. Regarding articular fractures, the severity of lesions is assessed by the displacement, rather than the number of fragments [16, 18, 19]. Usually, articular fractures are associated with both tuberosities, but exceptions may occur. Three-fragment fractures can also be encountered in clinical practice, as described by J. Duparc and Tamai [11, 16]. The number of fragments is not essential in the AST classification, which is better in terms of simplicity. Another potential clinical relevance is the measurement of displacement. Displacement is evaluated by two numbers, which are the cephalic tilting angle for an articular fracture, or the angulation for an extra-articular fracture, and the major linear displacement of the fragments in millimeters. These two numbers, which are easy to define, allow surgeons to quantify the severity of the lesion in addition to the common and simple denomination of each case. In our institution, we usually operate on the fracture when there is at least 30° of tilt and/or 1 cm of linear displacement, compared with the 45° and 10 mm proposed by Neer’s classification. Another study showed that a tuberosity fragment must be operated on when there is at least 5 mm of displacement [22].


According to our results, the AST classification is at least as reproducible as the three other classifications evaluated in this study. The kappa indexes obtained should be compared with those reported in the literature, which are all rather poor [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 23]. Some authors insist on the relevance of a training course in order to improve comprehension and reproducibility in Neer’s system [3, 4, 24]. In particular, two authors stated that the poor reproducibility observed with Neer’s classification was due to its complexity [4, 25]. They proposed a simplification but did not show significant improvement considering reproducibility. Others authors considered that tomodensitometry does not improve comprehension of these fractures [2, 7, 23]. On the contrary, Edelson proposed a classification based on 3D CT pictures for five types of fractures [5]. Another study analyzed the reproducibility of a complex classification called MTM, although the authors concluded that it was unusable because of the poor reproducibility and that a simplification was necessary [1]. Many authors insist that displacement is a good indicator of the gravity of these fractures [11, 18, 19]. It seems that reproducibility is acceptable for minor displacements, but it becomes unacceptable for major displacements. Tamai et al. after studying 22 operated complex fractures divided into three and four parts, noticed that eight out of 22 fractures did not correspond to any usual classification type—particularly some of the three fragments fractures [11]. This argument supports the use of the AST classification because it is not based on the number of fragments.


The AST is a classification system developed by the authors for the last 10 years and is already being used in clinical practice for proximal humeral fractures. This new classification is easy to use and is based on a single figure (Fig. 1) including all types of proximal humeral fractures. The severity of the fracture is assessed by the displacement of fragments. This study shows an inter-observer reproducibility at least as good as the three other classifications most often used in current clinical practice.



We would like to thank the physicians who participated in this study for their extraordinary help, and for the reading, classification, and analysis of four different classifications of a total of 64 X-rays of proximal humeral fractures: Dr Beau—Metz, Dr Berrichi—Metz, Dr Boughrebi—Amiens, Dr Camus—Dunkerque, Dr Dujardin—Orléans, Dr Favreul—Lyon, Pr Galois—Nancy, Dr Ionescu—Metz, Dr Irrazi—Metz, Dr Kany—Toulouse, Dr Khalife—Metz, Pr Roussignol—Rouen, Dr Schenk—Strasbourg, Dr Schwartz—Colmar, Dr Scarlat—Toulon, Dr Seboiu—Metz, Pr Simon—Lyon, Dr Travers—Lyon, as well as the talented Mrs L. Collette—Bruxelles, for the figures.

Conflict of interest

The authors have no conflict of interest to declare.


  1. 1.
    Bahrs C, Schmal H, Lingenfelter E, Rolauffs B, Weise K, Dietz K et al (2008) Inter- and intraobserver reliability of the MTM-classification for proximal humeral fractures: a prospective study. BMC Musculoskelet Disord 9:21PubMedCrossRefGoogle Scholar
  2. 2.
    Brorson S, Bagger J, Sylvest A, Hrøbjartsson A (1995) Neer’s classification system: a critical appraisal. J Trauma 38:257–260CrossRefGoogle Scholar
  3. 3.
    Brorson S, Bagger J, Sylvest A, Hrøbjartsson A (2002) Improved interobserver variation after training of doctors in the Neer system. A randomised trial. J Bone Joint Surg Br 84:950–954PubMedCrossRefGoogle Scholar
  4. 4.
    Brorson S, Hróbjartsson A (2008) Training improves agreement among doctors using the Neer system for proximal humeral fractures in a systematic review. J Clin Epidemiol 61:7–16PubMedCrossRefGoogle Scholar
  5. 5.
    Edelson G, Kelly I, Vigder F, Reis ND (2004) A three-dimensional classification for fractures of the proximal humerus. J Bone Joint Surg Br 86:413–425PubMedCrossRefGoogle Scholar
  6. 6.
    Mahadeva D, Mackay DC, Turner SM, Drew S, Costa ML (2008) Reliability of the Neer classification system in proximal humeral fractures: a systematic review of the literature. Eur J Orthop Surg Traumatol 18:415–424CrossRefGoogle Scholar
  7. 7.
    Sallay PI, Pedowitz RA, Mallon WJ, Vandemark RM, Dalton JD, Speer KP (1997) Reliability and reproducibility of radiographic interpretation of proximal humeral fracture pathoanatomy. J Shoulder Elbow Surg 6:60–69PubMedCrossRefGoogle Scholar
  8. 8.
    Shrader MW, Sanchez-Sotelo J, Sperling JW, Rowland CM, Cofield RH (2005) Understanding proximal humerus fractures: image analysis, classification, and treatment. J Shoulder Elbow Surg 14:497–505PubMedCrossRefGoogle Scholar
  9. 9.
    Siebenrock KA, Gerber C (1993) The reproducibility of classification of fractures of the proximal end of the humerus. J Bone Joint Surg Am 75:1751–1755PubMedGoogle Scholar
  10. 10.
    Sjödén GO, Movin T, Aspelin P, Güntner P, Shalabi A (1999) 3D-radiographic analysis does not improve the Neer and AO classifications of proximal humeral fractures. Acta Orthop Scand 70:325–328PubMedCrossRefGoogle Scholar
  11. 11.
    Tamai K, Hamada J, Ohno W, Saotome K (2002) Surgical anatomy of multipart fractures of the proximal humerus. J Shoulder Elbow Surg 11:421–427PubMedCrossRefGoogle Scholar
  12. 12.
    Neer CS (1970) Displaced proximal humeral fractures. I. Classification and evaluation. J Bone Joint Surg Am 52:1077–1089PubMedGoogle Scholar
  13. 13.
    Neer CS. Four Segment Classification (2008) In shoulder reconstruction. W.B. Saunders, Philadelphie, pp. 366–370Google Scholar
  14. 14.
    Jakob RP, Kristiansen T, Mayo K, Ganz R, Müller ME (1984) Classification and aspects of treatment of fractures of the proximal humerus. Bateman and WelshGoogle Scholar
  15. 15.
    Jakob RP, Miniaci A, Anson PS, Jaberg H, Osterwalder A, Ganz R (1991) Four-part valgus impacted fractures of the proximal humerus. J Bone Joint Surg Br 73:295–298PubMedGoogle Scholar
  16. 16.
    Duparc J, Largier A (1976) Fracture-dislocations of the upper end of the humerus. Rev Chir Orthop Reparatrice Appar Mot 62:91–110PubMedGoogle Scholar
  17. 17.
    Boehler J (1935) Boehler (The treatment of fractures), 4th edn. Williams Wood, BaltimoreGoogle Scholar
  18. 18.
    Court-Brown CM, Cattermole H, McQueen MM, Impacted valgus fractures (B1.1) of the proximal humerus (2002) The results of non-operative treatment. J Bone Joint Surg Br 84:504–508PubMedCrossRefGoogle Scholar
  19. 19.
    Lee CK, Hansen HR (1981) Post-traumatic avascular necrosis of the humeral head in displaced proximal humeral fractures. J Trauma 21:788–791PubMedCrossRefGoogle Scholar
  20. 20.
    Fleiss JL (1971) Measuring nominal scale agreement among many raters. Psychol Bull 76:378–382CrossRefGoogle Scholar
  21. 21.
    Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174PubMedCrossRefGoogle Scholar
  22. 22.
    Duparc F, Huten D (1998) Conservative treatment of fractures of the upper end of the humerus. Rev Chir Orthop Reparatrice Appar Mot 84(Suppl 1):121–189PubMedGoogle Scholar
  23. 23.
    Sjödén GO, Movin T, Güntner P, Aspelin P, Ahrengart L, Ersmark H et al (1997) Poor reproducibility of classification of proximal humeral fractures. Additional CT of minor value. Acta Orthop Scand 68:239–242PubMedCrossRefGoogle Scholar
  24. 24.
    Kristiansen B, Andersen UL, Olsen CA, Varmarken JE (1988) The Neer classification of fractures of the proximal humerus. An assessment of interobserver variation. Skeletal Radiol 17:420–422PubMedCrossRefGoogle Scholar
  25. 25.
    Sidor ML, Zuckerman JD, Lyon T, Koval K, Cuomo F, Schoenberg N (1993) The Neer classification system for proximal humeral fractures. An assessment of interobserver reliability and intraobserver reproducibility. J Bone Joint Surg Am 75:1745–1750PubMedGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Christian Cuny
    • 1
  • Cedric Baumann
    • 2
  • Julien Mayer
    • 1
  • Didier Guignand
    • 1
  • M’barek Irrazi
    • 1
  • Aboubekr Berrichi
    • 1
  • Nicolas Ionescu
    • 1
  • Francis Guillemin
    • 2
  1. 1.Department of Orthopaedics and TraumatologyCHR Metz Bon-SecoursMetz CedexFrance
  2. 2.Department of Clinical Epidemiology, CHU NancyVandoeuvre-lès-NancyFrance

Personalised recommendations