Dr. Hindin obtained his MD from the University of Pennsylvania Perelman School of Medicine in Philadelphia, Pennsylvania. He completed his general surgery training at Temple University School of Medicine, also in Philadelphia, and subsequently completed fellowship in surgical critical care at Stanford University School of Medicine. Dr. Hindin is currently a Clinical Assistant Professor of Surgery at Stanford University in the section of Trauma and Critical Care Surgery and at the VA Palo Alto. Dr. Hindin also serves as Assistant Director of Stanford University’s Biodesign Faculty Fellowship, a university-wide program that trains faculty members from medicine, engineering, and other schools in the process of creating health technology innovation, from needs-finding to commercialization.

Dr. Hindin has a particular interest in training physicians to leverage story-based skills to increase the effectiveness of their communication. He has previously developed and taught a semester-long storytelling course at Stanford Biodesign, which trains physicians and engineers to create more effective pitches when seeking venture funding.

Clinical Focus

  • General Surgery

Academic Appointments

Professional Education

  • Residency: Temple University Hospital Dept of Surgery (2019) PA
  • Fellowship: Stanford University Surgical Critical Care Fellowship (2022) CA
  • Board Certification: American Board of Surgery, General Surgery (2020)
  • Internship: Hospital of the University of Pennsylvania General Surgery Residency (2012) PA
  • Medical Education: Perelman School of Medicine University of Pennsylvania (2011) PA

All Publications

  • Rib fracture fixation in a patient on veno-venous extracorporeal membrane oxygenation following a motor vehicle collision. Trauma surgery & acute care open Fawzy, Y., Hindin, D., Faliks, B., Tung, J., Forrester, J. D. 2022; 7 (1): e001004

    View details for DOI 10.1136/tsaco-2022-001004

    View details for PubMedID 36389118

    View details for PubMedCentralID PMC9664310

  • Surgical Infection Society: Chest Wall Injury Society Recommendations for Antibiotic Use during Surgical Stabilization of Traumatic Rib or Sternal Fractures to Reduce Risk of Implant Infection. Surgical infections Forrester, J. D., Bukur, M., Dvorak, J. E., Faliks, B., Hindin, D., Kartiko, S., Kheirbek, T., Lin, L., Manasa, M., Martin, T. J., Miskimins, R., Patel, B., Pieracci, F. M., Ritter, K. A., Schubl, S. D., Tung, J., Huston, J. M. 2022; 23 (4): 321-331


    Background: Surgical stabilization of rib fractures is recommended in patients with flail chest or multiple displaced rib fractures with physiologic compromise. Surgical stabilization of rib fractures (SSRF) and surgical stabilization of sternal fractures (SSSF) involve open reduction and internal fixation of fractures with a plate construct to restore anatomic alignment. Most plate constructs are composed of titanium and presence of this foreign, non-absorbable material presents opportunity for implant infection. Although implant infection rates after SSRF and SSSF are low, they present a challenging clinical entity often requiring prolonged antibiotic therapy, debridement, and potentially implant removal. Methods: The Surgical Infection Society's Therapeutics and Guidelines Committee and Chest Wall Injury Society's Publication Committee convened to develop recommendations for antibiotic use during and after surgical stabilization of traumatic rib and sternal fractures. Clinical scenarios included patients with concomitant infectious processes (sepsis, pneumonia, empyema, cellulitis) or sources of contamination (open chest, gross contamination) incurred as a result of their trauma and present at the time of their surgical stabilization. PubMed, Embase, and Cochrane databases were searched for pertinent studies. Using a process of iterative consensus, all committee members voted to accept or reject each recommendation. Results: For patients undergoing SSRF or SSSF in the absence of pre-existing infectious process, there is insufficient evidence to suggest existing peri-operative guidelines or recommendations are inadequate. For patients undergoing SSRF or SSSF in the presence of sepsis, pneumonia, or an empyema, there is insufficient evidence to provide recommendations on duration and choice of antibiotic. This decision may be informed by existing guidelines for the concomitant infection. For patients undergoing SSRF or SSSF with an open or contaminated chest there is insufficient evidence to provide specific antibiotic recommendations. Conclusions: This guideline document summarizes the current Surgical Infection Society and Chest Wall Injury Society recommendations regarding antibiotic use during and after surgical stabilization of traumatic rib or sternal fractures. Limited evidence exists in the chest wall surgical stabilization literature and further studies should be performed to delineate risk of implant infection among patients undergoing SSSRF or SSSF with concomitant infectious processes.

    View details for DOI 10.1089/sur.2022.025

    View details for PubMedID 35522129

  • Scalable Deep Learning Algorithm to Compute Percent Pulmonary Contusion among Patients with Rib Fractures. The journal of trauma and acute care surgery Choi, J., Mavrommati, K., Li, N. Y., Patil, A., Chan, K., Hindin, D. I., Forrester, J. D. 2022


    Pulmonary contusion exists along a spectrum of severity, yet is commonly binarily classified as present or absent. We aimed to develop a deep learning algorithm to automate percent pulmonary contusion computation and exemplify how transfer learning could facilitate large-scale validation. We hypothesized our deep learning algorithm could automate percent pulmonary contusion computation and that greater percent contusion would be associated with higher odds of adverse inpatient outcomes among patients with rib fractures.We evaluated admission-day chest computed tomography (CT) scans of adults aged ≥18 years admitted to our institution with multiple rib fractures and pulmonary contusions (2010-2020). We adapted a pre-trained convolutional neural network that segments 3-dimensional lung volumes and segmented contused lung parenchyma, pulmonary blood vessels, and computed percent pulmonary contusion. Exploratory analysis evaluated associations between percent pulmonary contusion (quartiles) and odds of mechanical ventilation, mortality, and prolonged hospital length-of-stay using multivariable logistic regression. Sensitivity analysis included pulmonary blood vessel volumes during percent contusion computation.A total of 332 patients met inclusion criteria (median 5 rib fractures), among whom 28% underwent mechanical ventilation and 6% died. The study population's median (IQR) percent pulmonary contusion was 4(2-8)%. Compared to the lowest quartile of percent pulmonary contusion, each increasing quartile was associated with higher adjusted odds of undergoing mechanical ventilation (OR[95%CI]: 1.5[1.1-2.1]) and prolonged hospitalization (OR[95%CI]: 1.6[1.1-2.2]), but not with mortality (OR[95%CI]: 1.1 [0.6-2.0]. Findings were similar on sensitivity analysis.We developed a scalable deep learning algorithm to automate percent pulmonary contusion calculating using chest CTs of adults admitted with rib fractures. Open code sharing and collaborative research is needed to validate our algorithm and exploratory analysis at large scale. Transfer learning can help harness the full potential of big data and high-performing algorithms to bring precision medicine to the bedside.IV.

    View details for DOI 10.1097/TA.0000000000003619

    View details for PubMedID 35319542