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SPSS Analysis of Pain Factors in Rotator Cuff Repair
Author(s) -
Yi Zhou,
Huali Chen,
Jing Wang,
Hui Wu,
Yuanjie Zeng,
Xiaohui Yi,
Yan Zhang
Publication year - 2021
Publication title -
journal of chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.436
H-Index - 50
eISSN - 2090-9063
pISSN - 2090-9071
DOI - 10.1155/2021/8491846
Subject(s) - medicine , anesthesia , analgesic , poisson regression , wilcoxon signed rank test , surgery , mann–whitney u test , population , environmental health
In this study, the matched case-control study was used. Nineteen cases of severe pain in the early postoperative period among 55 patients were set as the observation group, and 57 cases of simultaneous rotator cuff repair without severe pain were matched in a 1 : 3 ratio as the control group. Patients’ general information, disease characteristics, anesthesia and analgesia scheme, and operation information were collected. Frequency statistics, Wilcoxon signed rank sum test, regulatory effect analysis, and Poisson regression analysis were performed on these data. Some findings are included in the analysis. (1) There was a markable difference of 0.01 between the preoperative 48 h maximum pain value and the postoperative 48 h maximum pain value in the observation group. (2) There was a markable difference of 0.01 between the size and shape of the wound tear and the maximum pain value at 48 h after operation in the observation group. (3) When the number of opioid use affected the maximum pain value at 48 h after operation, the regulatory variables (type, quantity, and number of days of postoperative analgesics) were at different levels, and the impact amplitude had markable differences. (4) Age has a markable negative impact on the postoperative hospital stay. (5) The operation duration has a markable positive relationship with the postoperative hospital stay. (6) The analgesic pump had a markable positive impact on the postoperative hospital stay. (7) The location of injury did not affect the postoperative hospital stay.

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