BACKGROUND:The expansion of science has resulted in an increased information flow and in an exponentially growing number of connections between knowledge in different research fields. In this study, we used methods of scientometric analysis to obtain a conceptual network that forms the structure of active scientific research fields in anesthesia. METHODS:We extracted from the Web of Science (Institute for Scientific Information) all original articles (n = 3275) including their references (n = 79,972) that appeared in 2003 in all 23 journals listed in the Institute for Scientific Information Journal Citation Reports under the subject heading "Anesthesiology." After identification of highly cited references (> or = 5), pairs of co-cited references were created and grouped into uniformly structured clusters of documents using a single linkage and variable level clustering method. In addition, for each such cluster of documents, we identified corresponding front papers published in 2003, each of which co-cited at least two documents of the cluster core. Active anesthetic research fields were then named by examining the titles of the documents in both the established clusters and in their corresponding front papers. These research fields were sorted according to the proportion of recent documents in their cluster core (immediacy index) and were further analyzed. RESULTS:Forty-six current anesthetic research fields were identified. The research field named "ProSeal laryngeal mask airway" showed the highest immediacy index (100%) whereas the research fields "Experimental models of neuropathic pain" and "Volatile anesthetic-induced cardioprotection" exhibited the highest level of co-citation strength (level 9). The research field with the largest cluster core, containing 12 homogeneous papers, was "Postoperative nausea and vomiting." The journal Anesthesia & Analgesia published most front papers while Anesthesiology published most of the fundamental documents used as references in the front papers. CONCLUSIONS:Using co-citation analysis, we identified distinct homogenous clusters of highly cited documents representing 46 active current anesthetic research fields and determined multiple nets of knowledge among them.