Posterior approach, fracture diagnosis and ASA class III–IV are associated with increased risk of revision for dislocation after total hip arthroplasty: An analysis of 33,337 operations from the Finnish Arthroplasty Register.

Background & Aims Dislocation is one of the most common reasons for revision surgery after primary total hip arthroplasty (THA). Both patient related and surgical factors may influence the risk of dislocation. In this study we evaluated risk factors for dislocation revision after THA based on revised data contents of the Finnish Arthroplasty Register (FAR). Materials and Methods We analysed 33,337 primary THAs performed between May 2014 and January 2018 in Finland. Cox proportional hazards regression was used to estimate hazard ratios with 95% confidence intervals for first dislocation revision using 18 potential risk factors as covariates, such as age, sex, diagnosis, hospital volume, surgical approach, head size, BMI, ASA class, and fixation method. Results During the study period there were 264 first time revisions for dislocation after primary THA. Hazard ratio for dislocation revision was 3.1 (CI 1.7–5.5) for posterior compared to anterolateral approach, 3.0 (CI 1.9–4.7) for THAs performed for femoral neck fracture compared to THAs performed for osteoarthritis, 2.0 (CI 1.0–3.9) for ASA class III–IV compared to ASA class I, and 0.5 (0.4–0.7) for 36 mm femoral head size compared to 32 mm head size. Conclusion Special attention should be paid on patients with fracture diagnoses and ASA class III–IV. Anterolateral approach and 36 mm femoral heads decrease dislocation revision risk and should be considered for high risk patients.Lonkan kokotekonivelleikkauksen jälkeinen sijoiltaanmenoriski on suurin ensimmäisten kolmen kuukauden aikana tekonivelleikkauksesta. Ensimmäisen vuoden aikana leikkauksesta sijoiltaanmenoja tapahtuu 66–69 %:ia. Sijoiltaanmenon vuoksi ensimmäisiä uusintaleikkauksia tehdään 17–21 %:ia lonkan kokotekonivelleikkauksen jälkeen. Sijoiltaanmenoriski on yleensä uusintaleikkauksen jälkeen suurempi verrattuna primaarileikkaukseen. Sijoiltaanmenoriskiin yhdistetyt riskitekijät on pyritty luokittelemaan sekä potilas- että leikkausriippuvaisiin tekijöihin, mutta käytännössä useat eri tekijät vaikuttavat samanaikaisesti sijoiltaanmenoriskiin. Tämän tutkimuksen tarkoituksena oli selvittää lonkan primaaritekonivelleikkauksen jälkeiseen sijoiltaanmenoriskiin yhteydessä olevat tekijät käyttämällä apuna uudistettua Suomen Endoproteesirekisterin tietokantaa. Tutkimusaineistoon sisällytettiin yhteensä 33 661 lonkan primaaritekonivelleikkausta vuosilta 2014–2018. Aineistoon sisältyi myös potilaita, joilta oli operoitu toinen tai molemmat lonkat. Tutkimuksen päätapahtumaksi määriteltiin mitkä tahansa tekonivelen osan poistot tai vaihdot, jotka johtuivat sijoiltaanmenosta. Sijoiltaanmenoriskiin yhteydessä olevat tekijät määritettiin Coxin yksi- ja monimuuttujamallien avulla. Ensimmäisiä uusintaleikkauksia sijoiltaanmenon takia tehtiin 265 kappaletta tutkimuksemme seuranta-aikana. Suurentunut riski sijoiltaanmenolle oli potilailla, jotka leikattiin taka-avauksessa ja joilla leikkaukseen johtanut syy oli reisiluun kaulan murtuma ja joiden ASA-luokka oli III–IV. Vastaavasti pienempi riski sijoiltaanmenolle oli tekonivelissä, joiden nupin halkaisija oli 36 mm verrattuna tekoniveliin, joiden nupin halkaisija oli 32 mm. Potilaan uusintaleikkausriskiä tekonivelen sijoiltaanmenon takia kasvattivat murtuma toimenpiteen syynä, taka-avaus, korkeampi ASA-luokka ja pienempi nuppikoko. Mikäli potilaalla on useampi edellä mainituista riskitekijöistä, tulisi niihin kiinnittää erityistä huomiota potilaan hoidossa, jotta tulevaisuudessa pystyttäisiin vähentämään lonkan tekonivelten sijoiltaanmenojen lukumäärää

Risk factors and risk prediction models for early complications following total hip arthroplasty

Treatment of end-stage hip osteoarthritis was revolutionized in the 1960s with the newly invented low-friction total hip arthroplasty (THA). Since then, an increasing number of both primary and revision THAs have been performed annually, especially over the past two decades. To achieve better outcomes, orthopedic surgeons should carefully select optimal patients and appropriate methods and devices. Risk prediction models have been developed to inform the surgeon and patient more precisely about the expected outcomes of the surgery. The use of such a tool could engage patients more closely in the decision-making process and guide surgeons in avoiding unnecessary risk. The aims of this doctoral thesis were: 1) to determine the risk factors for revision due to dislocation after primary THA; 2) to determine the risk factors for revision due to periprosthetic joint infection (PJI) after primary THA; 3) to develop risk prediction models for assessing the risk of the most common adverse outcomes after primary THA, based on versatile registry data from Finland; and 4) to develop risk prediction models for early revisions and death, and to evaluate the predictive potential of various machine learning algorithms for complications following primary THA, based on the Nordic Arthroplasty Register Association (NARA) dataset. ,, We found that posterior approach, fracture diagnosis, and American Society of Anesthesiologists class III–IV were associated with an increased risk of revision for dislocation after primary THA. The use of a 36 mm femoral head size decreased the risk of revision for dislocation. For PJI, we identified several modifiable variables increasing and decreasing the risk of revision. Especially patients with a high body mass index may be at even higher risk of developing infection than previously reported. We also successfully developed preoperative risk prediction models for PJI, dislocation, periprosthetic fracture, and death after primary THA. Based on the NARA dataset, we were able to demonstrate that complex risk prediction methods are not required to achieve maximum predictive potential. Hence, simpler models can improve usability. All the developed models can easily be used in clinical practice to serve individual risk estimations for adverse outcomes.--- Pitkälle edenneen lonkan nivelrikon hoito mullistui, kun moderni lonkan tekonivelleikkaus yleistyi 60-luvulla. Lonkan tekonivelen ensi- ja uusintaleikkausten määrät ovat kasvaneet merkittävästi erityisesti kahden viimeisen vuosikymmenen aikana. Uusintaleikkausten välttämiseksi ortopedien tulisi huolellisesti valita ensileikkaukseen sopivat potilaat sekä parhaat mahdolliset leikkausmenetelmät ja komponentit. Viime aikoina onkin kehitetty riskilaskureita, jotta sekä kirurgien että potilaiden ymmärrys odotettavissa olevasta lopputuloksesta paranisi. Riskilaskureiden avulla potilaat voidaan ottaa paremmin mukaan yhteiseen päätöksentekoon. Tässä väitöskirjatutkimuksessa selvitettiin riskitekijöitä lonkan tekonivelleikkauksen jälkeisille uusintaleikkauksille. Erityishuomion kohteena olivat tekonivelen sijoiltaanmenot sekä infektiot. Lisäksi kehitimme riskilaskurimalleja ennustamaan potilaskohtaista riskiä tyypillisimmille komplikaatioille ja kuolemalle lonkan ensitekonivelleikkauksen jälkeen. Tämä väitöskirja perustuu uudistetun Suomen Endoproteesirekisterin ja Pohjoismaisen tekonivelrekisterin tietoihin. Tutkimuksessa havaittiin taka-avauksen, reisiluun kaulan murtumadiagnoosin ja anestesiariskiluokkien III-IV altistavan uusintaleikkaukselle tekonivelen sijoiltaanmenon vuoksi. Käytettäessä 36 mm:n halkaisijan omaavia nuppeja sijoiltaanmenoriski oli matala. Lisäksi tunnistimme useita muuttujia, jotka olivat yhteydessä tekonivelen infektoitumiseen. Erityisesti potilaat, joilla on korkea painoindeksi, saattavat olla alttiimpia tekonivelinfektiolle, kuin mitä aikaisemmin on raportoitu. Kehitimme myös onnistuneesti riskilaskurimallit ennustamaan riskiä tekonivelen uusintaleikkaukselle infektion, sijoiltaanmenon ja periproteettisen murtuman johdosta sekä kuolemalle lonkan ensitekonivelleikkauksen jälkeen. Tärkeä havainto riskilaskurimallien kehityksessä oli myös se, että yksinkertaisilla menetelmillä pystytään ennustamaan riskiä yhtä hyvin kuin monimutkaisilla menetelmillä. Kaikkia kehittämiämme malleja voi käyttää kliinisen päätöksenteon tukena arvioimaan potilaskohtaista riskiä leikkauksen jälkeiselle epäsuotuisalle päätetapahtumalle

Risk factors for prosthetic joint infections following total hip arthroplasty based on 33,337 hips in the Finnish Arthroplasty Register from 2014 to 2018

Background and purpose - Periprosthetic joint infection (PJI) is a devastating complication and more information on risk factors for PJI is required to find measures to prevent infections. Therefore, we assessed risk factors for PJI after primary total hip arthroplasty (THA) in a large patient cohort. Patients and methods - We analyzed 33,337 primary THAs performed between May 2014 and January 2018 based on the Finnish Arthroplasty Register (FAR). Cox proportional hazards regression was used to estimate hazard ratios with 95% confidence intervals (CI) for first PJI revision operation using 25 potential patient- and surgical-related risk factors as covariates. Results - 350 primary THAs were revised for the first time due to PJI during the study period. The hazard ratios for PJI revision in multivariable analysis were 2.0 (CI 1.3-3.2) for ASA class II and 3.2 (2.0-5.1) for ASA class III-IV compared with ASA class I, 1.4 (1.1-1.7) for bleeding > 500 mL compared with 120 minutes compared with 45-59 minutes, and 2.6 (1.4-4.9) for simultaneous bilateral operation. In the univariable analysis, hazard ratios for PJI revision were 2.3 (1.7-3.3) for BMI of 31-35 and 5.0 (3.5-7.1) for BMI of > 35 compared with patients with BMI of 21-25. Interpretation - We found several modifiable risk factors associated with increased PJI revision risk after THA to which special attention should be paid preoperatively. In particular, high BMI may be an even more prominent risk factor for PJI than previously assessed.Peer reviewe

Risk factors for prosthetic joint infections following total hip arthroplasty based on 33,337 hips in the Finnish Arthroplasty Register from 2014 to 2018

Background and purpose - Periprosthetic joint infection (PJI) is a devastating complication and more information on risk factors for PJI is required to find measures to prevent infections. Therefore, we assessed risk factors for PJI after primary total hip arthroplasty (THA) in a large patient cohort.Patients and methods - We analyzed 33,337 primary THAs performed between May 2014 and January 2018 based on the Finnish Arthroplasty Register (FAR). Cox proportional hazards regression was used to estimate hazard ratios with 95% confidence intervals (CI) for first PJI revision operation using 25 potential patient- and surgical-related risk factors as covariates.Results - 350 primary THAs were revised for the first time due to PJI during the study period. The hazard ratios for PJI revision in multivariable analysis were 2.0 (CI 1.3-3.2) for ASA class II and 3.2 (2.0-5.1) for ASA class III-IV compared with ASA class I, 1.4 (1.1-1.7) for bleeding > 500 mL compared with 120 minutes compared with 45-59 minutes, and 2.6 (1.4-4.9) for simultaneous bilateral operation. In the univariable analysis, hazard ratios for PJI revision were 2.3 (1.7-3.3) for BMI of 31-35 and 5.0 (3.5-7.1) for BMI of > 35 compared with patients with BMI of 21-25.Interpretation - We found several modifiable risk factors associated with increased PJI revision risk after THA to which special attention should be paid preoperatively. In particular, high BMI may be an even more prominent risk factor for PJI than previously assessed.</p

Prediction of Early Adverse Events After THA : A Comparison of Different Machine-Learning Strategies Based on 262,356 Observations From the Nordic Arthroplasty Register Association (NARA) Dataset

Objective: Preoperative risk prediction models can support shared decision-making before total hip arthroplasties (THAs). Here, we compare different machine-learning (ML) approaches to predict the six-month risk of adverse events following primary THA to obtain accurate yet simple-to-use risk prediction models. Methods: We extracted data on primary THAs (N = 262,356) between 2010 and 2018 from the Nordic Arthroplasty Register Association dataset. We benchmarked a variety of ML algorithms in terms of the area under the receiver operating characteristic curve (AUROC) for predicting the risk of revision caused by periprosthetic joint infection (PJI), dislocation or periprosthetic fracture (PPF), and death. All models were internally validated against a randomly selected test cohort (one-third of the data) that was not used for training the models. Results: The incidences of revisions because of PJI, dislocation, and PPF were 0.8%, 0.4%, and 0.3%, respectively, and the incidence of death was 1.2%. Overall, Lasso regression with stable iterative variable selection (SIVS) produced models using only four to five input variables but with AUROC comparable to more complex models using all 32 variables available. The SIVS-based Lasso models based on age, sex, preoperative diagnosis, bearing couple, fixation, and surgical approach predicted the risk of revisions caused by PJI, dislocations, and PPF, as well as death, with AUROCs of 0.61, 0.67, 0.76, and 0.86, respectively. Conclusion: Our study demonstrates that satisfactory predictive potential for adverse events following THA can be reached with parsimonious modeling strategies. The SIVS-based Lasso models may serve as simple-to-use tools for clinical risk assessment in the future.Peer reviewe

Posterior approach, fracture diagnosis, and American Society of Anesthesiology class III-IV are associated with increased risk of revision for dislocation after total hip arthroplasty : An analysis of 33,337 operations from the Finnish Arthroplasty Register

BACKGROUND AND AIMS: Dislocation is one of the most common reasons for revision surgery after primary total hip arthroplasty. Both patient related and surgical factors may influence the risk of dislocation. In this study, we evaluated risk factors for dislocation revision after total hip arthroplasty based on revised data contents of the Finnish Arthroplasty Register. MATERIALS AND METHODS: We analyzed 33,337 primary total hip arthroplasties performed between May 2014 and January 2018 in Finland. Cox proportional hazards regression was used to estimate hazard ratios with 95% confidence intervals for first dislocation revision using 18 potential risk factors as covariates, such as age, sex, diagnosis, hospital volume, surgical approach, head size, body mass index, American Society of Anesthesiology class, and fixation method. RESULTS: During the study period, there were 264 first-time revisions for dislocation after primary total hip arthroplasty. The hazard ratio for dislocation revision was 3.1 (confidence interval 1.7-5.5) for posterior compared to anterolateral approach, 3.0 (confidence interval 1.9-4.7) for total hip arthroplasties performed for femoral neck fracture compared to total hip arthroplasties performed for osteoarthritis, 2.0 (confidence interval 1.0-3.9) for American Society of Anesthesiology class III-IV compared to American Society of Anesthesiology class I, and 0.5 (0.4-0.7) for 36-mm femoral head size compared to 32-mm head size. CONCLUSION: Special attention should be paid to patients with fracture diagnoses and American Society of Anesthesiology class III-IV. Anterolateral approach and 36-mm femoral heads decrease dislocation revision risk and should be considered for high-risk patients.publishedVersionPeer reviewe