Predictors of spinal trauma care and outcomes in a resource-constrained environment: a decision tree analysis of spinal trauma surgery and outcomes in Tanzania

Andreas LeidingerDepartment of Neurosurgery, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain;

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 MD, PhD
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Scott L. ZuckermanDepartment of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee;

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 MD, MPH
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Yueqi FengBiostatistics and Data Science, Cornell University, New York, New York;

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Yitian HeBiostatistics and Data Science, Cornell University, New York, New York;

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Xinrui ChenBiostatistics and Data Science, Cornell University, New York, New York;

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Beverly CheseremAga Khan University Hospital, Nairobi, Kenya;

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Linda M. GerberDepartments of Public Health and

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Noah L. LessingSchool of Medicine, University of Maryland, Baltimore, Maryland;

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Hamisi K. ShabaniDepartment of Neurosurgery, Muhimbili Orthopaedic Institute, Dar es Salaam, Tanzania; and

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Roger HärtlNeurology and Neurological Surgery, Weill Cornell Medical College, New York, New York;

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Halinder S. MangatDepartment of Neurology, Division of Neurocritical Care, University of Kansas Medical Center, Kansas City, Kansas

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 MD, MSc
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OBJECTIVE

The burden of spinal trauma in low- and middle-income countries (LMICs) is immense, and its management is made complex in such resource-restricted settings. Algorithmic evidence-based management is cost-prohibitive, especially with respect to spinal implants, while perioperative care is work-intensive, making overall care dependent on multiple constraints. The objective of this study was to identify determinants of decision-making for surgical intervention, improvement in function, and in-hospital mortality among patients experiencing acute spinal trauma in resource-constrained settings.

METHODS

This study was a retrospective analysis of prospectively collected data in a cohort of patients with spinal trauma admitted to a tertiary referral hospital center in Dar es Salam, Tanzania. Data on demographic, clinical, and treatment characteristics were collected as part of a quality improvement neurotrauma registry. Outcome measures were surgical intervention, American Spinal Injury Association (ASIA) Impairment Scale (AIS) grade improvement, and in-hospital mortality, based on existing treatment protocols. Univariate analyses of demographic and clinical characteristics were performed for each outcome of interest. Using the variables associated with each outcome, a machine learning algorithm-based regression nonparametric decision tree model utilizing a bootstrapping method was created and the accuracy of the three models was estimated.

RESULTS

Two hundred eighty-four consecutively admitted patients with acute spinal trauma were included over a period of 33 months. The median age was 34 (IQR 26–43) years, 83.8% were male, and 50.7% had experienced injury in a motor vehicle accident. The median time to hospital admission after injury was 2 (IQR 1–6) days; surgery was performed after a further median delay of 22 (IQR 13–39) days. Cervical spine injury comprised 38.4% of the injuries. Admission AIS grades were A in 48.9%, B in 16.2%, C in 8.5%, D in 9.5%, and E in 16.6%. Nearly half (45.1%) of the patients underwent surgery, 12% had at least one functional improvement in AIS grade, and 11.6% died in the hospital. Determinants of surgical intervention were age ≤ 30 years, spinal injury level, admission AIS grade, delay in arrival to the referral hospital, undergoing MRI, and type of insurance; admission AIS grade, delay to arrival to the hospital, and injury level for functional improvement; and delay to arrival, injury level, delay to surgery, and admission AIS grade for in-hospital mortality. The best accuracies for the decision tree models were 0.62, 0.34, and 0.93 for surgery, AIS grade improvement, and in-hospital mortality, respectively.

CONCLUSIONS

Operative intervention and functional improvement after acute spinal trauma in this tertiary referral hospital in an LMIC environment were low and inconsistent, which suggests that nonclinical factors exist within complex resource-driven decision-making frameworks. These nonclinical factors are highlighted by the authors’ results showing clinical outcomes and in-hospital mortality were determined by natural history, as evidenced by the highest accuracy of the model predicting in-hospital mortality.

ABBREVIATIONS

AIS = ASIA Impairment Scale; ASIA = American Spinal Injury Association; BP = blood pressure; HIC = high-income country; ISS = Injury Severity Score; LMIC = low- and middle-income country; MOI = Muhimbili Orthopaedic Institute; MVA = motor vehicle accident; TBI = traumatic brain injury.

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  • 1

    Corley J, Barthélemy EJ, Lepard J, et al. Comprehensive policy recommendations for head and spine injury care in low- and middle-income countries. World Neurosurg. 2019;132:434436.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2

    Lessing NL, Zuckerman SL, Lazaro A, et al. Cost-effectiveness of operating on traumatic spinal injuries in low-middle income countries: a preliminary report from a major East African referral center. Global Spine J. 2022;12(1):1523.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3

    Ryan SL, Sen A, Staggers K, Luerssen TG, Jea A. A standardized protocol to reduce pediatric spine surgery infection: a quality improvement initiative. J Neurosurg Pediatr. 2014;14(3):259265.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Rubiano AM, Carney N, Chesnut R, Puyana JC. Global neurotrauma research challenges and opportunities. Nature. 2015;527(7578):S193S197.

  • 5

    Stricsek G, Ghobrial G, Wilson J, Theofanis T, Harrop JS. Complications in the management of patients with spine trauma. Neurosurg Clin N Am. 2017;28(1):147155.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6

    Lessing NL, Mwesige S, Lazaro A, et al. Pressure ulcers after traumatic spinal injury in East Africa: risk factors, illustrative case, and low-cost protocol for prevention and treatment. Spinal Cord Ser Cases. 2020;6(1):48.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7

    Smart LR, Mangat HS, Issarow B, et al. Severe traumatic brain injury at a tertiary referral center in Tanzania: epidemiology and adherence to Brain Trauma Foundation Guidelines. World Neurosurg. 2017;105:238248.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8

    Magogo J, Lazaro A, Mango M, et al. Operative treatment of traumatic spinal injuries in Tanzania: surgical management, neurologic outcomes, and time to surgery. Global Spine J. 2021;11(1):8998.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9

    Schenck H, Wu X, Gerber LM, et al. Impact of CT scan utilization on surgical management and outcome in patients with severe traumatic brain injury at a tertiary care referral Hospital in Tanzania. Presented at: Intensive Care Medicine Experimental Conference: 30th Annual Congress of the European Society of Intensive Care Medicine, ESICM.

    • Search Google Scholar
    • Export Citation
  • 10

    Santos MM, Qureshi MM, Budohoski KP, et al. The growth of neurosurgery in East Africa: Challenges. World Neurosurg. 2018;113:425435.

  • 11

    Mangat HS, Schöller K, Budohoski KP, et al. Neurosurgery in East Africa: foundations. World Neurosurgery. 2018;113:411424.

  • 12

    Vaca SD, Kuo BJ, Nickenig Vissoci JR, et al. Temporal delays along the neurosurgical care continuum for traumatic brain injury patients at a tertiary care hospital in Kampala, Uganda. Neurosurgery. 2019;84(1):95103.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13

    Marcoux J, Bracco D, Saluja RS. Temporal delays in trauma craniotomies. J Neurosurg. 2016;125(3):642647.

  • 14

    Maine RG, Kajombo C, Purcell L, Gallaher JR, Reid TD, Charles AG. Effect of in-hospital delays on surgical mortality for emergency general surgery conditions at a tertiary hospital in Malawi. BJS Open. 2019;3(3):367375.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15

    Mangat HS, Wu X, Gerber LM, et al. Severe traumatic brain injury management in Tanzania: analysis of a prospective cohort. J Neurosurg. 2021;135(4):11901202.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16

    Chang M, Canseco JA, Nicholson KJ, Patel N, Vaccaro AR. The role of machine learning in spine surgery: the future is now. Front Surg. 2020;7:54.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17

    Rovlias A, Kotsou S. Classification and regression tree for prediction of outcome after severe head injury using simple clinical and laboratory variables. J Neurotrauma. 2004;21(7):886893.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18

    Facchinello Y, Beauséjour M, Richard-Denis A, Thompson C, Mac-Thiong JM. Use of regression tree analysis for predicting the functional outcome after traumatic spinal cord injury. J Neurotrauma. 2021;38(9):12851291.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19

    Bae JM. The clinical decision analysis using decision tree. Epidemiol Health. 2014;36:e2014025.

  • 20

    Podgorelec V, Kokol P, Stiglic B, Rozman I. Decision trees: an overview and their use in medicine. J Med Syst. 2002;26(5):445463.

  • 21

    Goulet J, Richard-Denis A, Mac-Thiong JM. The use of classification and regression tree analysis to identify the optimal surgical timing for improving neurological outcomes following motor-complete thoracolumbar traumatic spinal cord injury. Spinal Cord. 2020;58(6):682688.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Vaccaro AR, Oner C, Kepler CK, et al. AOSpine thoracolumbar spine injury classification system: fracture description, neurological status, and key modifiers. Spine (Phila Pa 1976). 2013;38(23):20282037.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23

    O’Boynick CP, Kurd MF, Darden BV II, Vaccaro AR, Fehlings MG. Timing of surgery in thoracolumbar trauma: is early intervention safe? Neurosurg Focus. 2014;37(1):E7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24

    Fehlings MG, Tetreault LA, Wilson JR, et al. A clinical practice guideline for the management of acute spinal cord injury: introduction, rationale, and scope. Global Spine J. 2017;7(3)(suppl):84S94S.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25

    Leidinger A, Kim EE, Navarro-Ramirez R, et al. Spinal trauma in Tanzania: current management and outcomes. J Neurosurg Spine. 2019;31(1):103111.

  • 26

    Burney RE, Waggoner R, Maynard FM. Stabilization of spinal injury for early transfer. J Trauma. 1989;29(11):14971499.

  • 27

    Leidinger A, Extremera P, Kim EE, Qureshi MM, Young PH, Piquer J. The challenges and opportunities of global neurosurgery in East Africa: the Neurosurgery Education and Development model. Neurosurg Focus. 2018;45(4):E8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28

    Elhadi M, Alsoufi A, Abusalama A, et al. Epidemiology, outcomes, and utilization of intensive care unit resources for critically ill COVID-19 patients in Libya: a prospective multi-center cohort study. PLoS One. 2021;16(4):e0251085.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29

    Schell CO, Khalid K, Wharton-Smith A, et al. Essential emergency and critical care: a consensus among global clinical experts. BMJ Global Health. 2021;6(9):e006585.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30

    Lalwani S, Singh V, Trikha V, et al. Mortality profile of patients with traumatic spinal injuries at a level I trauma care centre in India. Indian J Med Res. 2014;140(1):4045.

    • Search Google Scholar
    • Export Citation
  • 31

    Bhaumik S. Use of evidence for clinical practice guideline development. Trop Parasitol. 2017;7(2):6571.

  • 32

    Fehlings MG, Rabin D, Sears W, Cadotte DW, Aarabi B. Current practice in the timing of surgical intervention in spinal cord injury. Spine (Phila Pa 1976). 2010;35(21 suppl):S166S173.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33

    Furlan JC, Noonan V, Cadotte DW, Fehlings MG. Timing of decompressive surgery of spinal cord after traumatic spinal cord injury: an evidence-based examination of pre-clinical and clinical studies. J Neurotrauma. 2011;28(8):13711399.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34

    Maschmann C, Jeppesen E, Rubin MA, Barfod C. New clinical guidelines on the spinal stabilisation of adult trauma patients—consensus and evidence based. Scand J Trauma Resusc Emerg Med. 2019;27(1):77.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 35

    Lan M, Lessing NL, Nyamsaya S, Matemu A, Zuckerman SL, Shabani HK. Prehospital care of trauma patients in Tanzania: medical knowledge assessment and proposal for safe transportation of neurotrauma patients. Spinal Cord Ser Cases. 2020;6(1):32.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36

    Leidinger A, Kim EE, Navarro-Ramirez R, et al. Spinal trauma in Tanzania: current management and outcomes. J Neurosurg Spine. 2019;31(1):103111.

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