Background. Healing of tibia fractures occurs over a wide time range of months, with a number of risk factors contributing to prolonged healing. In this prospective, multicentre, observational study, we investigated the capability of FRACTING (tibia FRACTure prediction healING days) score, calculated soon after tibia fracture treatment, to predict healing time. Methods. The study included 363 patients. Information on patient health, fracture morphology, and surgical treatment adopted were combined to calculate the FRACTING score. Fractures were considered healed when the patient was able to fully weight-bear without pain. Results. 319 fractures (88%) healed within 12 months from treatment. Forty-four fractures healed after 12 months or underwent a second surgery. FRACTING score positively correlated with days to healing: r = 0.63 (p < 0.0001). Average score value was 7.3 ± 2.5; ROC analysis showed strong reliability of the score in separating patients healing before versus after 6 months: AUC = 0.823. Conclusions. This study shows that the FRACTING score can be employed both to predict months needed for fracture healing and to identify immediately after treatment patients at risk of prolonged healing. In patients with high score values, new pharmacological and nonpharmacological treatments to enhance osteogenesis could be tested selectively, which may finally result in reduced disability time and health cost savings.

Can Clinical and Surgical Parameters Be Combined to Predict How Long It Will Take a Tibia Fracture to Heal? A Prospective Multicentre Observational Study: The FRACTING Study / Massari, Leo; Benazzo, Francesco; Falez, Francesco; Cadossi, Ruggero; Perugia, Dario; Pietrogrande, Luca; Aloj, Domenico Costantino; Capone, Antonio; D'Arienzo, Michele; Cadossi, Matteo; Lorusso, Vincenzo; Caruso, Gaetano; Ghiara, Matteo; Ciolli, Luigi; La Cava, Filippo; Guidi, Marco; Castoldi, Filippo; Marongiu, Giuseppe; La Gattuta, Alessandra; Dell'Omo, Dario; Scaglione, Michelangelo; Giannini, Sandro; Fortina, Mattia; Riva, Alberto; De Palma, Pier Luigi; Gigante, Antonio Pompilio; Moretti, Biagio; Solarino, Giuseppe; Lijoi, Francesco; Giordano, Giovanni; Londini, Pier Giorgio; Castellano, Danilo; Sessa, Giuseppe; Costarella, Luciano; Barile, Antonio; Borrelli, Mariano; Rota, Attilio; Fontana, Raffaele; Momoli, Alberto; Micaglio, Andrea; Bassi, Guido; Cornacchia, Rossano Stefano; Castelli, Claudio; Giudici, Michele; Monesi, Mauro; Branca Vergano, Luigi; Maniscalco, Pietro; Bulabula, M'Putu; Zottola, Vincenzo; Caraffa, Auro; Antinolfi, Pierluigi; Catani, Fabio; Severino, Claudio; Castaman, Enrico; Scialabba, Carmelo; Tovaglia, Venceslao; Corsi, Pietro; Friemel, Paolo; Ranellucci, Marco; Caiaffa, Vincenzo; Maraglino, Giovanni; Rossi, Roberto; Pastrone, Antonio; Caldora, Patrizio; Cusumano, Claudio; Squarzina, Pier Bruno; Baschieri, Ugo; Demattè, Ettore; Gherardi, Stefano; De Roberto, Carlo; Belluati, Alberto; Giannini, Antonio; Villani, Ciro; Persiani, Pietro; Demitri, Silvio; DI Maggio, Bruno; Abate, Guglielmo; De Terlizzi, Francesca; Setti, Stefania. - In: BIOMED RESEARCH INTERNATIONAL. - ISSN 2314-6133. - 2018(2018), pp. 1-7. [10.1155/2018/1809091]

Can Clinical and Surgical Parameters Be Combined to Predict How Long It Will Take a Tibia Fracture to Heal? A Prospective Multicentre Observational Study: The FRACTING Study

Cadossi, Ruggero;Catani, Fabio;Rossi, Roberto;
2018

Abstract

Background. Healing of tibia fractures occurs over a wide time range of months, with a number of risk factors contributing to prolonged healing. In this prospective, multicentre, observational study, we investigated the capability of FRACTING (tibia FRACTure prediction healING days) score, calculated soon after tibia fracture treatment, to predict healing time. Methods. The study included 363 patients. Information on patient health, fracture morphology, and surgical treatment adopted were combined to calculate the FRACTING score. Fractures were considered healed when the patient was able to fully weight-bear without pain. Results. 319 fractures (88%) healed within 12 months from treatment. Forty-four fractures healed after 12 months or underwent a second surgery. FRACTING score positively correlated with days to healing: r = 0.63 (p < 0.0001). Average score value was 7.3 ± 2.5; ROC analysis showed strong reliability of the score in separating patients healing before versus after 6 months: AUC = 0.823. Conclusions. This study shows that the FRACTING score can be employed both to predict months needed for fracture healing and to identify immediately after treatment patients at risk of prolonged healing. In patients with high score values, new pharmacological and nonpharmacological treatments to enhance osteogenesis could be tested selectively, which may finally result in reduced disability time and health cost savings.
2018
1
7
Can Clinical and Surgical Parameters Be Combined to Predict How Long It Will Take a Tibia Fracture to Heal? A Prospective Multicentre Observational Study: The FRACTING Study / Massari, Leo; Benazzo, Francesco; Falez, Francesco; Cadossi, Ruggero; Perugia, Dario; Pietrogrande, Luca; Aloj, Domenico Costantino; Capone, Antonio; D'Arienzo, Michele; Cadossi, Matteo; Lorusso, Vincenzo; Caruso, Gaetano; Ghiara, Matteo; Ciolli, Luigi; La Cava, Filippo; Guidi, Marco; Castoldi, Filippo; Marongiu, Giuseppe; La Gattuta, Alessandra; Dell'Omo, Dario; Scaglione, Michelangelo; Giannini, Sandro; Fortina, Mattia; Riva, Alberto; De Palma, Pier Luigi; Gigante, Antonio Pompilio; Moretti, Biagio; Solarino, Giuseppe; Lijoi, Francesco; Giordano, Giovanni; Londini, Pier Giorgio; Castellano, Danilo; Sessa, Giuseppe; Costarella, Luciano; Barile, Antonio; Borrelli, Mariano; Rota, Attilio; Fontana, Raffaele; Momoli, Alberto; Micaglio, Andrea; Bassi, Guido; Cornacchia, Rossano Stefano; Castelli, Claudio; Giudici, Michele; Monesi, Mauro; Branca Vergano, Luigi; Maniscalco, Pietro; Bulabula, M'Putu; Zottola, Vincenzo; Caraffa, Auro; Antinolfi, Pierluigi; Catani, Fabio; Severino, Claudio; Castaman, Enrico; Scialabba, Carmelo; Tovaglia, Venceslao; Corsi, Pietro; Friemel, Paolo; Ranellucci, Marco; Caiaffa, Vincenzo; Maraglino, Giovanni; Rossi, Roberto; Pastrone, Antonio; Caldora, Patrizio; Cusumano, Claudio; Squarzina, Pier Bruno; Baschieri, Ugo; Demattè, Ettore; Gherardi, Stefano; De Roberto, Carlo; Belluati, Alberto; Giannini, Antonio; Villani, Ciro; Persiani, Pietro; Demitri, Silvio; DI Maggio, Bruno; Abate, Guglielmo; De Terlizzi, Francesca; Setti, Stefania. - In: BIOMED RESEARCH INTERNATIONAL. - ISSN 2314-6133. - 2018(2018), pp. 1-7. [10.1155/2018/1809091]
Massari, Leo; Benazzo, Francesco; Falez, Francesco; Cadossi, Ruggero; Perugia, Dario; Pietrogrande, Luca; Aloj, Domenico Costantino; Capone, Antonio; D'Arienzo, Michele; Cadossi, Matteo; Lorusso, Vincenzo; Caruso, Gaetano; Ghiara, Matteo; Ciolli, Luigi; La Cava, Filippo; Guidi, Marco; Castoldi, Filippo; Marongiu, Giuseppe; La Gattuta, Alessandra; Dell'Omo, Dario; Scaglione, Michelangelo; Giannini, Sandro; Fortina, Mattia; Riva, Alberto; De Palma, Pier Luigi; Gigante, Antonio Pompilio; Moretti, Biagio; Solarino, Giuseppe; Lijoi, Francesco; Giordano, Giovanni; Londini, Pier Giorgio; Castellano, Danilo; Sessa, Giuseppe; Costarella, Luciano; Barile, Antonio; Borrelli, Mariano; Rota, Attilio; Fontana, Raffaele; Momoli, Alberto; Micaglio, Andrea; Bassi, Guido; Cornacchia, Rossano Stefano; Castelli, Claudio; Giudici, Michele; Monesi, Mauro; Branca Vergano, Luigi; Maniscalco, Pietro; Bulabula, M'Putu; Zottola, Vincenzo; Caraffa, Auro; Antinolfi, Pierluigi; Catani, Fabio; Severino, Claudio; Castaman, Enrico; Scialabba, Carmelo; Tovaglia, Venceslao; Corsi, Pietro; Friemel, Paolo; Ranellucci, Marco; Caiaffa, Vincenzo; Maraglino, Giovanni; Rossi, Roberto; Pastrone, Antonio; Caldora, Patrizio; Cusumano, Claudio; Squarzina, Pier Bruno; Baschieri, Ugo; Demattè, Ettore; Gherardi, Stefano; De Roberto, Carlo; Belluati, Alberto; Giannini, Antonio; Villani, Ciro; Persiani, Pietro; Demitri, Silvio; DI Maggio, Bruno; Abate, Guglielmo; De Terlizzi, Francesca; Setti, Stefania
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