Please assess the completion status of the following clinical trial:

Trial Title: Pain Outcomes After Anterior Cruciate Ligament Reconstruction With Posterior Capsular Marcaine Injection

Study Design Characteristics:
- Allocation: RANDOMIZED
- Intervention Model: PARALLEL
- Observational Model: None
- Primary Purpose: TREATMENT
- Time Perspective: None
- Masking: SINGLE
- Phase: None
- Number of Arms: 2.0

Eligibility Criteria:
Inclusion Criteria:~* Adult individuals (ages 18-60), both sexes, submitted to elective ACL reconstructions with or without partial menisectomies of the medial or lateral meniscus~Exclusion Criteria:~* Multiligamentous injury or revision surgery~* Known narcotic/substance abuse or regular opiate use~* Known allergy to any medication or anesthetic being used in this study~* Patients with pre-existing diabetic or femoral neropathy~* INTRAOPERATIVELY- if chrondral microfractures, inside-out or outside-in meniscal repairs were performed (\*\*\*Since these additional surgeries within the joint may increase the perceived level of pain post-op\*\*\*)

- Gender: ALL
- Minimum Age: 18 Years
- Maximum Age: 80 Years
- Healthy Volunteers: t

Study Arms:
- No Injection (Type: PLACEBO_COMPARATOR): These patients will receive standard of care when undergoing anterior cruciate ligament reconstruction and will NOT be receiving a posterior capsular knee injection of Marcaine 0.5%.~They will be monitored for pain control and pill intake while in the PACU and the first four days post-operatively the same as the patients in the INJECTION Arm of the study.
- Injection (Type: EXPERIMENTAL): These patients will receive standard of care when undergoing anterior cruciate ligament reconstruction but will additionally be receiving a one-time posterior capsular knee injection of Marcaine 0.5% (20cc) during the surgery.~They will be monitored for pain control and pill intake while in the PACU and the first four days post-operatively the same as the patients in the NO injection Arm of the study.

Based on this trial design, predict the completion outcome and termination type (if applicable).