Skei Nina Vibeche, Damås Jan Kristian, Gustad Lise Tuset
Department of Intensive Care and Anesthesia, Nord-Trondelag Hospital Trust, Levanger, Norway.
The Mid-Norway Centre for Sepsis Research, Institute of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
PLoS One. 2025 Mar 19;20(3):e0320054. doi: 10.1371/journal.pone.0320054. eCollection 2025.
In observational studies that use administrative data, it is essential to report technical details such as the number of International Classification of Disease (ICD) coding fields extracted. This information is crucial for ensuring comparability between studies and for avoiding truncation bias in estimates, particularly for complex conditions like sepsis. Specific sepsis codes (explicit sepsis) are suggested to be identified by extracting 15 diagnosis fields, while for implicit sepsis, which comprises an infection code combined with acute organ failure, the number of diagnosis field remains unknown.
The objective was to explore the necessary number of diagnosis fields to capture explicit and implicit sepsis.
We conducted a study utilizing The Norwegian Patient Register (NPR), which encompasses all medical ICD-10 codes from specialized health services in Norway. Data were extracted for all adult patients with hospital discharges registered with explicit and implicit sepsis codes from all Norwegian hospitals between 2008 through 2021.
Out of 317,705 sepsis admissions, we identified 105,499 ICD-10 codes for explicit sepsis, while implicit sepsis was identified through 270,346 codes for infection in combination with 240,789 codes for acute organ failure. Through our analysis, we found that 55%, 37%, and 10% of the explicit, infection, and acute organ failure codes, respectively, were documented as the main diagnosis. The proportion of explicit and infection codes peaked in the primary diagnosis field, while for acute organ failure codes, this was true in the third secondary diagnosis field. Notably, the cumulative proportion reached 99% in diagnosis field 10 for explicit codes and in diagnosis field 13 for implicit codes.
Expanding the utilization of multiple diagnosis fields can enhance the comparability of data in epidemiological studies, both internationally and within countries. To make truncation bias visible, reporting guidelines should specify the number of diagnosis fields when extracting ICD-10 codes.
在使用行政数据的观察性研究中，报告技术细节至关重要，例如提取的国际疾病分类（ICD）编码字段数量。这些信息对于确保研究之间的可比性以及避免估计中的截断偏差至关重要，特别是对于败血症等复杂病症。建议通过提取15个诊断字段来识别特定的败血症编码（明确败血症），而对于包含感染编码与急性器官功能衰竭相结合的隐性败血症，诊断字段数量尚不清楚。
目的是探索捕获明确和隐性败血症所需的诊断字段数量。
我们利用挪威患者登记处（NPR）进行了一项研究，该登记处包含挪威专科医疗服务机构的所有医疗ICD-10编码。提取了2008年至2021年期间挪威所有医院登记有明确和隐性败血症编码的所有成年出院患者的数据。
在317,705例败血症入院病例中，我们识别出105,499个明确败血症的ICD-10编码，而隐性败血症是通过270,346个感染编码与240,789个急性器官功能衰竭编码相结合识别出来的。通过我们的分析，我们发现分别有55%、37%和10%的明确、感染和急性器官功能衰竭编码被记录为主诊断。明确和感染编码的比例在主要诊断字段中达到峰值，而对于急性器官功能衰竭编码，在第三个次要诊断字段中达到峰值。值得注意的是，明确编码在诊断字段10中累计比例达到99%，隐性编码在诊断字段13中达到99%。
扩大多个诊断字段的使用可以提高国际和国内流行病学研究中数据的可比性。为了使截断偏差可见，报告指南应在提取ICD-10编码时指定诊断字段数量。
