| Literature DB >> 35285377 |
Dan Gao1, Yan Lou1, Yingchun Cui1, Shengmao Liu1, Wenpeng Cui1, Guangdong Sun1.
Abstract
OBJECTIVE: Hypocalcemia after parathyroidectomy (PTX) results in tetany, diarrhea, cardiac arrhythmia, and even sudden death. However, a meta-analysis or systematic evaluation of risk factors with the occurrence and development of hypocalcemia in patients with secondary hyperparathyroidism (SHPT) after PTX has never been performed.Entities:
Keywords: Secondary hyperparathyroidism; hypocalcemia; meta-analysis; risk factors
Mesh:
Year: 2022 PMID: 35285377 PMCID: PMC8928856 DOI: 10.1080/0886022X.2022.2048856
Source DB: PubMed Journal: Ren Fail ISSN: 0886-022X Impact factor: 2.606
Figure 1.The flow diagram of the study identification and inclusion and exclusion process.
The general characteristics of the included studies.
| Study | Year | Country | Design | Study period | Sample size | Case/controls | Surgical method | Hypocalcemiastandard (mmol/L) | Risk factors |
|---|---|---|---|---|---|---|---|---|---|
| Guang Yang | 2018 | China | Case-control | 2013.01–2017.04 | 252 | 180/72 | PTX + AT | <2.000 | ①③ |
| Jorge l.Fonseca-Correa | 2021 | Mexico | Case-control | 2003.10–2019.10 | 87 | 67/20 | PTX | <1.870 | ③⑩ |
| KittraweeKritmetapak | 2020 | Thailand | Case-control | 2014.01–2020.01 | 130 | 107/23 | PTX | <2.100 | ①③④⑥ |
| Lo-Yi Ho | 2017 | China | Case-control | 2004.01–2014.02 | 62 | 17/45 | T-PTX | <2.100 | ①⑥⑨ |
| M.Hamouda | 2013 | Tunisia | Case-control | – | 70 | 48/22 | PTX | <2.000 | ③⑥⑦ |
| Mingjun Wang | 2020 | China | Case-control | 2016.10–2018.10 | 114 | 87/27 | PTX + AT | <2.100 | ①③④⑧ |
| Ping Wen | 2020 | China | Case-control | 2008.01–2018.12 | 1095 | 811/284 | T-PTX | <1.780 | ③④ |
| Poh Guan Tan | 2020 | Malaysia | Case-control | 2007.01–2014.12 | 68 | 25/43 | PTX | <2.000 | ③⑥ |
| Wan-Chuan Tsai | 2015 | China | Case-control | 2001.02–2012.09 | 420 | 157/263 | PTX | <1.875 | ②③④ |
| Wei Gong | 2021 | China | Case-control | 2013.05–2020.02 | 87 | 18/69 | PTX + AT | <2.100 | ③④⑥ |
| Yifei Ge | 2019 | China | Case-control | 2015.07–2017.12 | 115 | 101/14 | PTX + AT | <2.100 | ①③ |
| Ying Wei (reference #8) | 2020 | China | Cohort | 2018.03–2019.05 | 286 | 76/210 | WMA/TPTX | <1.875 | WMA:①③⑦ |
| TPXT:①③⑪ | |||||||||
| Ying Wei (reference #16) | 2020 | China | Cohort | 2015.07–2018.05 | 204 | 45/159 | MWA | <1.875 | model.1:①④⑧ |
| model.2:①④⑧ |
PTX: parathyroidectomy; T-PTX:total-parathyroidectomy;PTX + AT: parathyroidectomy with forearm autograft; MWA: microwave ablation. ①preoperative serum calcium ②preoperative serum phosphorus ③preoperative ALP ④preoperative intact parathormone ⑤Pruritus ⑥Age ⑦preoperative serum albumin ⑧Weight of resected glands ⑨Body weight ⑩Males ⑪Volume of resected glands.
Quality assessment of studies included in this meta-analysis by Newcastle-Ottawa Scale.
| Study | Year | Selection | Comparability | Exposure/Outcome | Quality evaluation |
|---|---|---|---|---|---|
| Guang Yang | 2018 | ★★★★ | ★★ | ★★ | 8 |
| Jorge l.Fonseca-Correa | 2021 | ★★★ | ★ | ★★★ | 7 |
| KittraweeKritmetapak | 2020 | ★★★★ | ★ | ★★★ | 8 |
| Lo-Yi Ho | 2017 | ★★★ | ★★ | ★★ | 7 |
| M.Hamouda | 2013 | ★★★ | ★★ | ★★ | 7 |
| Ying Wei (reference #16) | 2020 | ★★★★ | ★★ | ★★ | 8 |
| Mingjun Wang | 2020 | ★★★★ | ★ | ★★ | 7 |
| Ping Wen | 2020 | ★★★★ | ★ | ★★★ | 8 |
| Poh Guan Tan | 2020 | ★★★ | ★★ | ★★★ | 8 |
| Wan-Chuan Tsai | 2015 | ★★★ | ★★ | ★★ | 7 |
| Wei Gong | 2021 | ★★★ | ★★ | ★★★ | 8 |
| Yifei Ge | 2019 | ★★★ | ★★ | ★★★ | 8 |
| Ying Wei (reference #08) | 2020 | ★★★ | ★★ | ★★ | 7 |
Figure 2.Forest plot of preoperative serum calcium.OR = odds ratio.
Sensitivity analysis for the meta-analysis of preoperative serum calcium by excluding one study at a time.
| Study | Results of meta-analysis | Heterogeneity of study design | |||
|---|---|---|---|---|---|
| OR (95%CI) | χ2 | ||||
| Original Meta Study | 0.19 (0.11,0.31) | <0.00001 | 18.10 | 0.01 | 61 |
| (delete)Guang Yang | 0.20 (0.13,0.32) | <0.00001 | 14.53 | 0.02 | 59 |
| (delete)Lo-Yi Ho | 0.20 (0.13,0.33) | <0.00001 | 14.65 | 0.02 | 59 |
| (delete)Ying Wei (#16) (model.1) | 0.17 (0.09,0.33) | <0.00001 | 17.70 | 0.007 | 66 |
| (delete)Ying Wei (#08)(MWA) | 0.19 (0.11,0.33) | <0.00001 | 17.28 | 0.008 | 65 |
| (delete)Ying Wei (#08)(TPTX) | 0.16 (0.09,0.28) | <0.00001 | 13.94 | 0.03 | 57 |
| (delete)KittraweeKritmetapak | 0.16 (0.09,0.29) | <0.00001 | 16.36 | 0.01 | 63 |
| (delete)Ying Wei (#16) (model.2) | 0.17 (0.09,0.33) | <0.00001 | 17.56 | 0.007 | 66 |
| (delete)Mingjun Wang | 0.22 (0.14,0.36) | <0.00001 | 12.64 | 0.05 | 53 |
Figure 3.Forest plot of age. OR = odds ratio.
Sensitivity analysis for the meta-analysis of age by excluding one study at a time.
| Study | Results of meta-analysis | Heterogeneity of study design | |||
|---|---|---|---|---|---|
| OR (95%CI) | χ2 | ||||
| Original Meta Study | 0.97 (0.87,1.10) | 0.66 | 21.97 | 0.00002 | 82 |
| (delete)KittraweeKritmetapak | 1.00 (0.90,1.10) | 0.95 | 14.21 | 0.003 | 79 |
| (delete)Lo-Yi Ho | 0.98 (0.81,1.20) | 0.86 | 19.66 | 0.0002 | 85 |
| (delete)M.Hamouda | 0.97 (0.86,1.08) | 0.54 | 18.83 | 0.0003 | 84 |
| (delete)Poh Guan Tan | 0.96 (0.76,1.21) | 0.71 | 21.26 | <0.0001 | 86 |
| (delete)Wei Gong | 0.93 (0.82,1.05) | 0.22 | 11.39 | 0.010 | 74 |
Figure 4.Forest plot of preoperative ALP.OR = odds ratio.
Sensitivity analysis for the meta-analysis of preoperative ALP by excluding one study at a time.
| Study | Results of meta-analysis | Heterogeneity of study design | |||
|---|---|---|---|---|---|
| OR (95%CI) | χ2 | I2(%) | |||
| Original Meta Study | 1.01 (1.01,1.02) | 0.0002 | 126.22 | <0.00001 | 90 |
| (delete)Guang Yang | 1.01 (1.00,1.02) | 0.005 | 112.20 | <0.00001 | 90 |
| (delete)Jorge l.Fonseca-Correa(model.1) | 1.01 (1.01,1.02) | 0.0002 | 122.43 | <0.00001 | 91 |
| (delete)Jorge l.Fonseca-Correa(model.2) | 1.01 (1.01,1.02) | 0.0002 | 120.98 | <0.00001 | 91 |
| (delete)KittraweeKritmetapak | 1.01 (1.01,1.02) | 0.0003 | 123.51 | <0.00001 | 91 |
| (delete)M.Hamouda | 1.01 (1.01,1.02) | 0.0002 | 124.09 | <0.00001 | 91 |
| (delete)Mingjun Wang | 1.01 (1.01,1.02) | 0.0002 | 121.75 | <0.00001 | 91 |
| (delete)Ping Wen | 1.01 (1.00,1.02) | 0.0004 | 73.4 | <0.00001 | 85 |
| (delete)Poh Guan Tan | 1.02 (1.01,1.03) | <0.0001 | 125.48 | <0.00001 | 91 |
| (delete)Wan-Chuan Tsai | 1.01 (1.00,1.02) | 0.008 | 98.96 | <0.00001 | 89 |
| (delete)Wei Gong | 1.01 (1.01,1.02) | 0.0003 | 121.22 | <0.00001 | 91 |
| (delete)Yifei Ge | 1.00 (1.00,1.00) | 0.002 | 119.64 | <0.00001 | 91 |
| (delete)Ying Wei(#08)(MWA) | 1.02 (1.01,1.03) | <0.0001 | 126.22 | <0.00001 | 91 |
| (delete)Ying Wei(#08)(TPTX) | 1.02 (1.01,1.04) | <0.0001 | 122.62 | <0.00001 | 91 |
Figure 5.Forest plot of preoperative iPTH. OR = odds ratio.
Sensitivity analysis for the meta-analysis of preoperative iPTH by excluding one study at a time.
| Study | Results of meta-analysis | Heterogeneity of study design | |||
|---|---|---|---|---|---|
| OR (95%CI) | χ2 | ||||
| Original Meta Study | 1.38 (1.20,1.58) | <0.00001 | 101.99 | <0.00001 | 94 |
| (delete)KittraweeKritmetapak | 1.36 (1.19,1.55) | <0.00001 | 97.98 | <0.00001 | 95 |
| (delete)Ying Wei (#16) (model.1) | 1.25 (1.09,1.42) | 0.001 | 75.56 | <0.00001 | 93 |
| (delete)Ying Wei (#16) (model.2) | 1.23 (1.09,1.40) | 0.001 | 72.97 | <0.00001 | 93 |
| (delete)Mingjun Wang | 2.51 (1.47,4.29) | 0.0008 | 95.60 | <0.00001 | 95 |
| (delete)Ping Wen | 1.26 (1.12,1.41) | <0.0001 | 63.96 | <0.00001 | 92 |
| (delete)Wan-Chuan Tsai | 2.51 (1.46,4.33) | 0.0009 | 101.31 | <0.00001 | 95 |
| (delete)Wei Gong | 1.37 (1.18,1.57) | <0.0001 | 98.69 | <0.00001 | 95 |