Investigators developed an automated method to categorize maternal morbidity, finding that infection and hypertension account for nearly 45% of nontransfusion-related complications.
A study published in Obstetrics & Gynecology introduced a hierarchical algorithm to identify the primary underlying conditions that lead to severe maternal morbidity (SMM). By applying this tool to large administrative datasets, researchers determined that the leading causes of non-fatal maternal complications differ significantly from the primary causes of pregnancy-related mortality in the United States.
The Centers for Disease Control and Prevention (CDC) utilizes an SMM index to list major complications, such as organ failure or the need for blood transfusions. However, this index traditionally lacks the ability to pinpoint the specific underlying medical condition that triggered the complication. To address this gap, investigators developed a systematic method using International Classification of Diseases, Tenth Revision (ICD-10) codes to categorize SMM cases by their primary cause.
The researchers developed the algorithm via a combination of medical record reviews and iterative analyses of datasets over an 8-year period between 2016 and 2024. To ensure accuracy, the team compared the algorithm's automated assignments against detailed manual medical record abstractions for 604 SMM cases. This validation process demonstrated a 94.5% concordance rate between the algorithm and the clinical reviews.
Following validation, the algorithm was applied to the 2016–2020 California hospital discharge dataset, which included 43,897 SMM cases, and the National Inpatient Sample (NIS), which included 63,880 cases. The study examined both total SMM and nontransfusion SMM, the latter of which excludes cases where a blood transfusion is the only indicator of morbidity.
In the California dataset, hemorrhage (including both placental and other types) was the most frequent primary underlying condition, accounting for 50.5% of all SMM cases and 38.3% of nontransfusion SMM. Severe hypertensive disorders and infections were also identified as significant contributors, as, together, the 2 conditions accounted for 31.2% of total SMM and 44.9% of nontransfusion SMM cases, respectively.
Other medical conditions represented 12.9% of total SMM and 19.8% of nontransfusion cases. Cardiovascular conditions were relatively uncommon as the primary driver of morbidity, identified in 2.4% of total SMM and 4.3% of nontransfusion SMM cases. Results from the NIS data were found to be similar to these findings.
The study highlighted a substantial disconnect between the conditions that cause severe illness and those that lead to death. When comparing SMM data to 2017–2019 figures from the CDC’s Pregnancy Mortality Surveillance System, researchers found that hemorrhage, hypertensive disorders, and infection were far more common in morbidity cases than in mortality cases. Specifically, while hemorrhage caused 50.5% of SMM, it was responsible for only 12.1% of maternal deaths.
Reference:
Main EK, McCormick EK, Tomlinson MW, et al. Development and Application of an Algorithm to Identify the Primary Underlying Condition for Cases of Severe Maternal Morbidity. Obstetrics & Gynecology. doi:10.1097/AOG.0000000000006299
