You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:

- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.
- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.
- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.

Please format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.

As an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:

[["artesunate", "artemether", "COMB"], ["Nifedipine", "Labetalol", "Prazosin", "POS"]]

The paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.

In your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.

paragraph: Proton Pump Inhibitor Co-Therapy in Patients with Atrial Fibrillation Treated with Oral Anticoagulants and a Prior History of Upper Gastrointestinal Tract Bleeding. The risk of gastrointestinal bleeding (GIB) can be mitigated by proton pump inhibitor (PPI) co-therapy in patients with atrial fibrillation (AF) treated with anticoagulants. We aimed to evaluate the effect of PPIs on the risk of GIB in Asian patients with AF, treated with oral anticoagulants (OACs), and with a prior history of upper GIB. ### methods Using a nationwide claims database, OAC-naïve patients with AF and a history of upper GIB before initiating OAC treatment between January 2010 and April 2018 were included. Patients were categorized into 10 groups according to the index OAC ( warfarin , rivaroxaban , dabigatran , apixaban , and edoxaban ) and whether or not they received PPI co-therapy , and were followed up for incidence of major GIB . ### results Among a total of 42,048 patients, 40% were prescribed PPIs as co-therapy with OACs. Over a median 0.6 years (interquartile ranges 0.2-1.7 years) of follow-up, rivaroxaban use without PPIs showed the highest crude incidence of major GIB (2.62 per 100 person-years), followed by the use of warfarin without a PPI (2.20 per 100 person-years). Compared to the patients without PPI use, PPI co-therapy was associated with a significantly lower risk of major GIB, by 40% and 36%, in the rivaroxaban and warfarin groups, respectively. In dabigatran, apixaban, and edoxaban users, PPI co-therapy did not show a significant reduction in the risk of major GIB. ### conclusion Among patients with AF receiving anticoagulant treatment and with a prior history of upper GIB, PPI co-therapy was associated with a significant reduction in the risk of major GIB in patients treated with rivaroxaban and warfarin.

sentence: Patients were categorized into 10 groups according to the index OAC ( warfarin , rivaroxaban , dabigatran , apixaban , and edoxaban ) and whether or not they received PPI co-therapy , and were followed up for incidence of major GIB .
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